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["rev0407"]
["Attachment1     “NII International Internship Program” Application Form 2025 2nd Call"]
[]
["Name of University/Institution:"]
["Country",{"$nulls":33},"1. Choose the name of the country where your home institution locates first."]
["Institute/University",{"$nulls":33},"2. Then choose the name of your home institution."]
[]
["Others",{"$nulls":33},"When you do not have the right name on the list, enter the name on \"others\"."]
["1. Candidate’s Information"]
["Name:",{"$nulls":19},"Date of birth:",{"$nulls":8},"Gender:"]
["FAMILY",{"$nulls":6},"GIVEN",{"$nulls":12},"yyyy/mm/dd",{"$nulls":8},"Male/Female"]
[{"$nulls":29},"drop-down",{"$nulls":5},"* NOTE *"]
["Master/Ph.D:",{"$nulls":13},"Nationality:",{"$nulls":20},"* Please fill in the boxes in GRAY."]
["choose from drop-down",{"$nulls":13},"choose from drop-down",{"$nulls":20},"* When a cell says \"(Choose from) drop-down\", please use a drop-down list."]
["E-mail:"]
["2. Supervisor’s Information at your university:",{"$nulls":34},"* Please fill in the form 2 as well."]
["Name:",{"$nulls":19},"Title/Position:"]
["FAMILY",{"$nulls":6},"GIVEN"]
[]
["Department:"]
[]
["E-mail:"]
["3. Curriculum Vitae:   *Please adjust the hight of rows if you need."]
["i. Higher Education "]
["Year:",{"$nulls":4},"Course:",{"$nulls":13},"School Name:"]
[]
[]
[]
[]
[]
["ii. Computer Skills"]
[]
[]
[]
[]
["iii. English Language Proficiency: "]
["*Please fill in your English level or appropriate English language proficiency test scores."]

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["4. Research Topics (select up to 3 topics from “list of research topics” and fill out in order)",{"$nulls":37},"Please confirm the No. you enter."]
["Order",null,null,"No.",null,"Research Area／Title of the research",{"$nulls":17},"Supervisor "]
[1,{"$nulls":4},{"$f":"IF(Topic1=\"\",\"\",IF(ISERROR(VLOOKUP(Topic1, Topic!$A$3:$J$101, 2,0)&\"\"),$AM$1, VLOOKUP(Topic1, Topic!$A$3:$J$101, 2,0)))","v":""},{"$nulls":17},{"$f":"IF(Topic1=\"\",\"\",IF(ISERROR(VLOOKUP(Topic1,Topic!$A$3:$J$101,6,0)&\"\"),\"\",VLOOKUP(Topic1,Topic!$A$3:$J$101,6,0)))","v":""}]
[{"$nulls":5},{"$f":"IF(Topic1=\"\",\"\",IF(ISERROR(VLOOKUP(Topic1,Topic!$A$3:$J$101,3,0)&\"\"),$AM$1,VLOOKUP(Topic1,Topic!$A$3:$J$101,3,0)))","v":""}]
[{"$nulls":23},{"$f":"IF(Topic1=\"\",\"\",IF(ISERROR(VLOOKUP(Topic1,Topic!$A$3:$J$101,5,0)&\"\"),\"\",VLOOKUP(Topic1,Topic!$A$3:$J$101,5,0)))","v":""}]
[]
[2,{"$nulls":4},{"$f":"IF(Topic2=\"\",\"\",IF(ISERROR(VLOOKUP(Topic2,Topic!$A$3:$J$101,2,0)&\"\"),$AM$1,VLOOKUP(Topic2,Topic!$A$3:$J$101,2,0)))","v":""},{"$nulls":17},{"$f":"IF(Topic2=\"\",\"\",IF(ISERROR(VLOOKUP(Topic2,Topic!$A$3:$J$101,6,0)&\"\"),\"\",VLOOKUP(Topic2,Topic!$A$3:$J$101,6,0)))","v":""}]
[{"$nulls":5},{"$f":"IF(Topic2=\"\",\"\",IF(ISERROR(VLOOKUP(Topic2,Topic!$A$3:$J$101,3,0)&\"\"),$AM$1,VLOOKUP(Topic2,Topic!$A$3:$J$101,3,0)))","v":""}]
[{"$nulls":23},{"$f":"IF(Topic2=\"\",\"\",IF(ISERROR(VLOOKUP(Topic2,Topic!$A$3:$J$101,5,0)&\"\"),\"\",VLOOKUP(Topic2,Topic!$A$3:$J$101,5,0)))","v":""}]
[{"$nulls":36},"id","result","message"]
[3,{"$nulls":4},{"$f":"IF(Topic3=\"\",\"\",IF(ISERROR(VLOOKUP(Topic3,Topic!$A$3:$J$101,2,0)&\"\"),$AM$1,VLOOKUP(Topic3,Topic!$A$3:$J$101,2,0)))","v":""},{"$nulls":17},{"$f":"IF(Topic3=\"\",\"\",IF(ISERROR(VLOOKUP(Topic3,Topic!$A$3:$J$101,6,0)&\"\"),\"\",VLOOKUP(Topic3,Topic!$A$3:$J$101,6,0)))","v":""},{"$nulls":12},"Blank",{"$f":"IF(OR($E$17=\"\",$Q$17=\"\"),1,\"\")","v":1},"Error: Please do not leave [From] and/or [To] blank."]
[{"$nulls":5},{"$f":"IF(Topic3=\"\",\"\",IF(ISERROR(VLOOKUP(Topic3,Topic!$A$3:$J$101,3,0)&\"\"),$AM$1,VLOOKUP(Topic3,Topic!$A$3:$J$101,3,0)))","v":""},{"$nulls":30},"Error",{"$f":"IF(ISERROR(Duration),1,IF(AND($E$17<>\"\",$Q$17<>\"\",N(Duration)<0),1,\"\"))","v":""},"Error: Please correct the duration you entered."]
[{"$nulls":23},{"$f":"IF(Topic3=\"\",\"\",IF(ISERROR(VLOOKUP(Topic3,Topic!$A$3:$J$101,5,0)&\"\"),\"\",VLOOKUP(Topic3,Topic!$A$3:$J$101,5,0)))","v":""},{"$nulls":12},"Over",{"$f":"IF(ISERROR(Duration),\"\",IF(N($AB$17)>=166,1,\"\"))","v":""},"Error: The internship period should be less than 165 days."]
[{"$nulls":36},"Less",{"$f":"IF(ISERROR(Duration),\"\",IF(AND(N($AB$17)<60,N($AB$17)>=1),1,\"\"))","v":""},"Error: The internship period should be more than 60 days."]
["5. Duration:",{"$nulls":4},{"$f":"IF($AL$11=1,blank,IF($AL$12=1,error,IF($AL$13=1,over,IF($AL$14=1,less,\"\"))))","v":"Error: Please do not leave [From] and/or [To] blank."}]
["*NOTICE: Internship period at NII must be 60 to 165 days."]
["From:",{"$nulls":11},"To:",{"$nulls":11},"Days:",null,null,{"$f":"(IF(OR($E$17=\"\",$Q$17=\"\"),\"\",N($Q$17-$E$17+1)))","v":""}]
[{"$nulls":4},"yyyy/mm/dd",{"$nulls":11},"yyyy/mm/dd"]
["6. Objectives of your “NII International Internship Program”"]

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[]
[{"$nulls":3},"Applicant",{"$nulls":8},"Supervisor",{"$nulls":4},"Topic",{"$nulls":4},"Duration"]
[null,null,"Call","Family","First","MOU_Country","MOU_Name","Date of Birth","Gender","Master/PhD","Nationality","Email","Family","First","Title","Dept","Email","Order by Applicant","Topic\n№","Supervisor","research area"," Title of the research ","From","To","Days"]
[null,null,2,{"$f":"app_family","v":0},{"$f":"app_first","v":0},{"$f":"'Form 1'!J5","v":0},{"$f":"app_inst","v":0},{"$f":"app_birth","v":"00:00:00"},{"$f":"app_gender","v":"drop-down"},{"$f":"app_status","v":"choose from drop-down"},{"$f":"app_nationality","v":"choose from drop-down"},{"$f":"email","v":0},{"$f":"'Form 1'!A19","v":0},{"$f":"'Form 1'!H19","v":0},{"$f":"'Form 1'!U19","v":0},{"$f":"'Form 1'!A21","v":0},{"$f":"'Form 1'!G22","v":0},1,{"$f":"Topic1","v":0},{"$f":"VLOOKUP(S4,Table_1[],5,0)","v":{"$error":"#N/A"}},{"$f":"VLOOKUP(S4,Table_1[],2,0)","v":{"$error":"#N/A"}},{"$f":"VLOOKUP(S4,Table_1[],3,0)","v":{"$error":"#N/A"}},{"$f":"from","v":"00:00:00"},{"$f":"to","v":"00:00:00"},{"$f":"N(X4-W4+1)","v":1}]
[{"$nulls":17},2,{"$f":"Topic2","v":0},{"$f":"VLOOKUP(S5,Table_1[],5,0)","v":{"$error":"#N/A"}},{"$f":"VLOOKUP(S5,Table_1[],2,0)","v":{"$error":"#N/A"}},{"$f":"VLOOKUP(S5,Table_1[],3,0)","v":{"$error":"#N/A"}},{"$f":"from","v":"00:00:00"},{"$f":"to","v":"00:00:00"},{"$f":"N(X5-W5+1)","v":1}]
[{"$nulls":17},3,{"$f":"Topic3","v":0},{"$f":"VLOOKUP(S6,Table_1[],5,0)","v":{"$error":"#N/A"}},{"$f":"VLOOKUP(S6,Table_1[],2,0)","v":{"$error":"#N/A"}},{"$f":"VLOOKUP(S6,Table_1[],3,0)","v":{"$error":"#N/A"}},{"$f":"from","v":"00:00:00"},{"$f":"to","v":"00:00:00"},1]

{"sheet":"MOU","index":3,"n_rows":32,"n_cols":20,"rows_kept":32,"hidden":true}
["country","name of institutions"]
["Choose from drop-down"]
["America","THE UNIVERSITY OF MICHIGAN-DEARBORN, COLLEGE OF ENGINEERING AND COMPUTER SCIENCE","College of Enginnering, University of Washington, Seattle","New Jersey Institute of Technology","International Computer Science Institute (ICI-Berkeley)","University of Southern California, Viterbi School of Engineering","North American Coordinating Council on Japanese Library Resources (NCC)","New Venture Fund(\"NVF\") on behalf of the Scholarly Publishing & Academic Resources Coalition (\"SPARC\")","Indiana University, School of Informatics, Computing, and Engineering","University of Illinois at Urbana Champaign","Language Technology Institute (LTI), Carnegie Mellon University","Center for Open Science (COS)","・・・","・・・","・・・","・・・","・・・","・・・"]
["Argentina","The Faculty of Exact and Natural Sciences of Buenos Aires University","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・"]
["Australia","The Faculty of Engineering and Information Technologies, The University of Sydney","School of Computing & Information Systems, Melbourne School of Engineering, The University of Melbourne","Royal Melbourne Institute of Technology","Monash University","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・"]
["Austria","The Vienna University of Technology (TU Wien)","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・"]
["Belgium","University of Namur","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・"]
["Brazil","Pontifical Catholic University of Campinas","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・"]
["Canada","School of Computer Science, McGill University","Polytechnique Montréal","Simon Fraser University","University of Alberta","Faculty of Mathematics, University of Waterloo","York University","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・"]
["Chile","Pontificia Universidad Católica de Chile (PUCC)","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・"]
["China","School of Information Science and Technology, Department of Automation, Tsinghua University","Tongji University","School of Computer Science, Peking University","The School of Electronic Information and Electrical Engineering of Shanghai Jiao Tong University","University of Science and Technology of China (USTC)","Institute of Computing Technology, Chinese Academy of Sciences","Institute of Scientific and Technical Information of China (ISTIC)","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・"]
["Czech","The Czech Technical University in Prague","Charles University","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・"]
["Egypt","The Egypt-Japan University of  Science and Technology(E-JUST)","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・"]
["Finland","Aalto University, School of Electrical Engineering and School of Science","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・"]
["France","Institut National de Recherche en Informatique et en Automatique (INRIA)","Grenoble INP","Université Grenoble Alpes (Université Joseph Fourier-Grenoble 1)","Laboratoire d'Informatique de Paris 6, Sorbonne Université (l'université Pierre et Marie Curie)","Institut National Polytechnique Toulouse (INP-ENSEEIHT)","The Central National de la Recherche Scientifique (CNRS)","Université Toulouse III - Paul Sabatier, Institut de Recherche en Informatique de Toulouse (IRIT)","Claude Bernard University Lyon 1","Université Paris Saclay, Graduate School of Computer Science (Université Paris Sud)","Université Côte d'Azur (University of Nice Sophia Antipolis)","Centre de Recherche en Informatique de Lens (CRIL)","Clermont Auvergne INP, School of Engineering ISIMA, LIMOS Laboratory (The Blaise Pascal University of Clermont-Ferrand)","the Nantes University, Laboratory of Digital Sciences of Nantes (LS2N)","Institut de Recherche en Informatique et Systemes Aleatoires (IRISA)","Ecole Normale Supérieure de Lyon (ENS Lyon)","EURECOM","Institut National des Sciences Appliquées de Lyon - INSA Lyon","・・・"]
["Germany","Faculty of Applied Computer Science, University of Augsburg","German Research Center for Artificial Intelligence (DFKI)","The University of Freiburg, the Faculty of Applied Sciences","The RWTH Aachen University, Faculty of Mathmatics, Computer Science and Natural Sciences","The German Academic Exchange Service (DAAD)","Saarland University","Technische Universität Berlin (TUB, TU Berlin)","Technische Universität Braunschweig (TU Braunschweig)","Department of Computer and Information Science, University of Konstanz","Technical University of Munich, the Department of Informatics and the Department of Electrical Engineering and Information Technology (TUM)","Georg-August-University of Göttingen, Institute of Computer Science, Centre for Computational Sciences, Campus Institute Data Science, Research Department of the State and University Library","HBZ","German National Library of Science and Technology (TIB)","German National Library of Medicine","The Faculty of Science at the University of Potsdam","Gesellschaft für wissenschaftliche Datenverarbeitung mbH Göttingen (GWDG)","University of Technology Nuremberg","Zuse Institute Berlin","・・・"]
["India","Indraprastha Institute of Information Technology, Delhi","・・・","・・・",null,"・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・"]
["Ireland","Dublin City University","Lero - the Irish Software Research Centre（The University of Limerick)","School of Computer Science and Statistics and ADAPT Centre, Trinity College Dublin","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・"]
["Italy","Politecnico di Milano, Dipartimento di Elettronica, Informazione e Bioingegneria","Torino University, Department of Computer Science","UNIVERSITA' DEGLI STUDI DI FERRARA (UNIFE)","Dipartimento di Informatica - Scienza e Ingegneria (DISI), Universita di Bologna","University of Florence, Department of Information Engineering, Department of Statistics, Computer Sciences and Applications","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・"]
["Korea","Department of Computer Science and Engineering, Seoul National University","Korea Education & Research Information Service (KERIS)","Korea Institute of Science and Technology Information (KISTI)","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・"]
["Norway","Department of Information Science and Media Studies of the University of Bergen (UiB)","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・"]
["Portugal","Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento em Lisboa (INESC-ID)","INESC Technology and Science (INESC TEC)","University of Minho","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・"]
["Saudi Arabia","King Abdullah University of Science and Technology (KAUST)","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・"]
["Singapore","School of Computing, National University of Singapore (NUS)","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・"]
["Spain","The Universitat Politècnica de Catalunya (UPC)","Universidad Politécnica de Madrid (UPM)","Universitat Politècnica de València (UPV)","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・"]
["Sweden","KTH Royal Institute of Technology","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・"]
["Swiss","Institute of Electrical and Micro Engineering and School of Computer and Communication Sciences, Ecole Polytechnique Federale de Lausanne (EPFL)","Universitá della Svizzera Italiana (USI)","University of Zurich (UZH)","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・"]
["Taiwan","Research Center for Information Technology Innovation, Academia Sinica","National Tsing Hua University, College of Electrical Engineering and Computer Science (NTHU EECS)","College of Electrical Engineering and Computer Science, National Taiwan Univeristy","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・"]
["Thailand","School of Engineering and Technology, Asian Institute of Technology","Department of Computer Engineering, Faculty of Engineering and Department of Mathematics and Computer Science, Faculty of Science, Chulalongkorn University","School of Information Science and Technology, Vidyasirimedhi Institute of Science and Technology (VISTEC)","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・"]
["The Netherlands","Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology","University of Amsterdam","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・"]
["United Kingdom","Faculty of Science, Technology, Engineering & Mathematics, The Open University","University of Bristol","University of Bath","The School of Informatics, University of Edinburgh","School of Computing, Newcastle University","Department of Computing at Imperial College London","The Department of Computer Science and The Mathematical Institute, Mathematical, Physical and Life Sciences Division, University of Oxford","The Department of Computer Science, Faculty of Engineering Science, University College London","Alan Turing Institute","Department of Computer Science & Technology, University of Cambridge","Cardiff University, School of Computer Science and Informatics","School of Computer Science, College of Engineering and Physical Sciences, University of Birmingham","Lancaster University","Queen Mary University of London","・・・","・・・","・・・"]
["Viet Nam","Hanoi University of Science and Technology(HUST), School of Information and Communications Technology","Vietnam National University - Ho Chi Minh city, University of Information Technology","Vietnam National University - Ho Chi Minh - University of Science (VNU-HCM-US)","VNU University of Engineering and Technology","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・","・・・"]

{"sheet":"drop-down","index":4,"n_rows":242,"n_cols":4,"rows_kept":242,"hidden":true}
["gender","status","ID","nation"]
["drop-down","Choose from drop-down",null,"Choose from drop-down"]
["male","Master",null,"Afghanistan"]
["female","Ph.D",null,"Albania"]
[{"$nulls":3},"Algeria"]
[{"$nulls":3},"American Samoa"]
[{"$nulls":3},"Andorra"]
[{"$nulls":3},"Angola"]
[{"$nulls":3},"Anguilla"]
[{"$nulls":3},"Antigua and Barbuda"]
[{"$nulls":3},"Argentina"]
[{"$nulls":3},"Armenia"]
[{"$nulls":3},"Aruba"]
[{"$nulls":3},"Australia"]
[{"$nulls":3},"Austria"]
[{"$nulls":3},"Azerbaijan"]
[{"$nulls":3},"Bahamas"]
[{"$nulls":3},"Bahrain"]
[{"$nulls":3},"Bangladesh"]
[{"$nulls":3},"Barbados"]
[{"$nulls":3},"Belarus"]
[{"$nulls":3},"Belgium"]
[{"$nulls":3},"Belize"]
[{"$nulls":3},"Benin"]
[{"$nulls":3},"Bermuda"]
[{"$nulls":3},"Bhutan"]
[{"$nulls":3},"Bolivia"]
[{"$nulls":3},"Bosnia and Herzegovina"]
[{"$nulls":3},"Botswana"]
[{"$nulls":3},"Brazil"]
[{"$nulls":3},"British Indian Territory"]
[{"$nulls":3},"British Virgin Islands"]
[{"$nulls":3},"Brunei"]
[{"$nulls":3},"Bulgaria"]
[{"$nulls":3},"Burkina Faso"]
[{"$nulls":3},"Burundi"]
[{"$nulls":3},"Cambodia"]
[{"$nulls":3},"Cameroon"]
[{"$nulls":3},"Canada"]
[{"$nulls":3},"Cape Verde"]
[{"$nulls":3},"Cayman Islands"]
[{"$nulls":3},"Central African Republic"]
[{"$nulls":3},"Chad"]
[{"$nulls":3},"Channel Islands"]
[{"$nulls":3},"Chile"]
[{"$nulls":3},"China"]
[{"$nulls":3},"Christmas Island"]
[{"$nulls":3},"Cocos Islands"]
[{"$nulls":3},"Colombia"]
[{"$nulls":3},"Comoros"]
[{"$nulls":3},"Congo"]
[{"$nulls":3},"Cook Islands"]
[{"$nulls":3},"Costa Rica"]
[{"$nulls":3},"Cote d'Ivoire "]
[{"$nulls":3},"Croatia"]
[{"$nulls":3},"Cuba"]
[{"$nulls":3},"Cyprus"]
[{"$nulls":3},"Czech Republic"]
[{"$nulls":3},"Democratic Republic of the Congo"]
[{"$nulls":3},"Denmark"]
[{"$nulls":3},"Djibouti"]
[{"$nulls":3},"Dominica"]
[{"$nulls":3},"Dominican Republic"]
[{"$nulls":3},"Ecuador"]
[{"$nulls":3},"Egypt"]
[{"$nulls":3},"El Salvador"]
[{"$nulls":3},"Equatorial Guinea"]
[{"$nulls":3},"Eritrea"]
[{"$nulls":3},"Estonia"]
[{"$nulls":3},"Ethiopia"]
[{"$nulls":3},"Faeroe Islands"]
[{"$nulls":3},"Falkland Islands"]
[{"$nulls":3},"Federated States of Micronesia"]
[{"$nulls":3},"Fiji"]
[{"$nulls":3},"Finland"]
[{"$nulls":3},"France"]
[{"$nulls":3},"French Guiana"]
[{"$nulls":3},"French Polynesia"]
[{"$nulls":3},"Gabon"]
[{"$nulls":3},"Gambia"]
[{"$nulls":3},"Georgia"]
[{"$nulls":3},"Germany"]
[{"$nulls":3},"Ghana"]
[{"$nulls":3},"Gibraltar"]
[{"$nulls":3},"Greece"]
[{"$nulls":3},"Greenland"]
[{"$nulls":3},"Grenada"]
[{"$nulls":3},"Guadeloupe Martinique"]
[{"$nulls":3},"Guam"]
[{"$nulls":3},"Guatemala"]
[{"$nulls":3},"Guinea"]
[{"$nulls":3},"Guinea-Bissau"]
[{"$nulls":3},"Guyana"]
[{"$nulls":3},"Haiti"]
[{"$nulls":3},"Honduras"]
[{"$nulls":3},"Hong Kong "]
[{"$nulls":3},"Hungary"]
[{"$nulls":3},"Iceland"]
[{"$nulls":3},"India"]
[{"$nulls":3},"Indonesia"]
[{"$nulls":3},"Iran"]
[{"$nulls":3},"Iraq"]
[{"$nulls":3},"Ireland"]
[{"$nulls":3},"Isle of Man"]
[{"$nulls":3},"Israel"]
[{"$nulls":3},"Italy"]
[{"$nulls":3},"Jamaica"]
[{"$nulls":3},"Japan"]
[{"$nulls":3},"Johnston Island"]
[{"$nulls":3},"Jordan"]
[{"$nulls":3},"Kashmir"]
[{"$nulls":3},"Kazakhstan"]
[{"$nulls":3},"Kenya"]
[{"$nulls":3},"Kiribati"]
[{"$nulls":3},"Kuwait"]
[{"$nulls":3},"Kyrgyz"]
[{"$nulls":3},"Lao People's Democratic Republic"]
[{"$nulls":3},"Latvia"]
[{"$nulls":3},"Lebanon"]
[{"$nulls":3},"Lesotho"]
[{"$nulls":3},"Liberia"]
[{"$nulls":3},"Libya"]
[{"$nulls":3},"Liechtenstein"]
[{"$nulls":3},"Lithuania"]
[{"$nulls":3},"Luxembourg"]
[{"$nulls":3},"Macau "]
[{"$nulls":3},"Madagascar"]
[{"$nulls":3},"Malawi"]
[{"$nulls":3},"Malaysia"]
[{"$nulls":3},"Maldives"]
[{"$nulls":3},"Mali"]
[{"$nulls":3},"Malta"]
[{"$nulls":3},"Marshall Islands"]
[{"$nulls":3},"Martinique"]
[{"$nulls":3},"Mauritania"]
[{"$nulls":3},"Mauritius"]
[{"$nulls":3},"Mayotte"]
[{"$nulls":3},"Mexico"]
[{"$nulls":3},"Midway Islands"]
[{"$nulls":3},"Moldova"]
[{"$nulls":3},"Monaco"]
[{"$nulls":3},"Mongolia"]
[{"$nulls":3},"Montenegro"]
[{"$nulls":3},"Montserrat"]
[{"$nulls":3},"Morocco"]
[{"$nulls":3},"Mozambique"]
[{"$nulls":3},"Myanmar"]
[{"$nulls":3},"Namibia"]
[{"$nulls":3},"Nauru"]
[{"$nulls":3},"Nepal"]
[{"$nulls":3},"Netherlands Antilles"]
[{"$nulls":3},"New Caledonia"]
[{"$nulls":3},"New Zealand "]
[{"$nulls":3},"Nicaragua"]
[{"$nulls":3},"Niger"]
[{"$nulls":3},"Nigeria"]
[{"$nulls":3},"Niue"]
[{"$nulls":3},"Norfolk Island"]
[{"$nulls":3},"North  Korea"]
[{"$nulls":3},"Northern Mariana Islands"]
[{"$nulls":3},"Norway"]
[{"$nulls":3},"Oman"]
[{"$nulls":3},"Pakistan"]
[{"$nulls":3},"Palau"]
[{"$nulls":3},"Panama"]
[{"$nulls":3},"Papua New Guinea"]
[{"$nulls":3},"Paraguay"]
[{"$nulls":3},"Peru"]
[{"$nulls":3},"Philippines"]
[{"$nulls":3},"Pitcairn "]
[{"$nulls":3},"Poland"]
[{"$nulls":3},"Portugal"]
[{"$nulls":3},"Puerto Rico"]
[{"$nulls":3},"Qatar"]
[{"$nulls":3},"Reunion"]
[{"$nulls":3},"Romania"]
[{"$nulls":3},"Russia"]
[{"$nulls":3},"Rwanda"]
[{"$nulls":3},"Saint Kitts and Nevis"]
[{"$nulls":3},"Saint Lucia"]
[{"$nulls":3},"Saint Vincent and the Grenadines"]
[{"$nulls":3},"Samoa"]
[{"$nulls":3},"San Marino"]
[{"$nulls":3},"Sao Tome and Principe"]
[{"$nulls":3},"Saudi Arabia"]
[{"$nulls":3},"Senegal"]
[{"$nulls":3},"Serbia"]
[{"$nulls":3},"Seychelles"]
[{"$nulls":3},"Sierra Leone"]
[{"$nulls":3},"Singapore"]
[{"$nulls":3},"Slovakia"]
[{"$nulls":3},"Slovenia"]
[{"$nulls":3},"Solomon Islands"]
[{"$nulls":3},"Somalia"]
[{"$nulls":3},"South Africa"]
[{"$nulls":3},"South Korea"]
[{"$nulls":3},"Spain"]
[{"$nulls":3},"Sri Lanka"]
[{"$nulls":3},"St. Helena ex. dep."]
[{"$nulls":3},"St. Pierre et Miquelon"]
[{"$nulls":3},"Sudan"]
[{"$nulls":3},"Suriname"]
[{"$nulls":3},"Svalbard"]
[{"$nulls":3},"Swaziland"]
[{"$nulls":3},"Sweden"]
[{"$nulls":3},"Swiss"]
[{"$nulls":3},"Syria"]
[{"$nulls":3},"Taiwan"]
[{"$nulls":3},"Tajikistan"]
[{"$nulls":3},"Tanzania"]
[{"$nulls":3},"Thailand"]
[{"$nulls":3},"The Democratic Republic of Timor-Leste"]
[{"$nulls":3},"The Former Yugoslav Republic of Macedonia"]
[{"$nulls":3},"The Netherlands"]
[{"$nulls":3},"The West Bank and Gaza Strip"]
[{"$nulls":3},"Togo"]
[{"$nulls":3},"Tokelau "]
[{"$nulls":3},"Tonga"]
[{"$nulls":3},"Trinidad and Tobago"]
[{"$nulls":3},"Tunisia"]
[{"$nulls":3},"Turkey"]
[{"$nulls":3},"Turkmenistan"]
[{"$nulls":3},"Turks and Caicos Islands"]
[{"$nulls":3},"Tuvalu"]
[{"$nulls":3},"Uganda"]
[{"$nulls":3},"Ukraine"]
[{"$nulls":3},"United Arab Emirates "]
[{"$nulls":3},"United Kingdom "]
[{"$nulls":3},"United States of America "]
[{"$nulls":3},"Uruguay"]
[{"$nulls":3},"Uzbekistan"]
[{"$nulls":3},"Vanuatu"]
[{"$nulls":3},"Vatican City State"]
[{"$nulls":3},"Venezuela"]
[{"$nulls":3},"Viet Nam"]
[{"$nulls":3},"Virgin"]
[{"$nulls":3},"Wake Island"]
[{"$nulls":3},"Wallis and Futuna Islands"]
[{"$nulls":3},"Western Sahara"]
[{"$nulls":3},"Yemen"]
[{"$nulls":3},"Zambia"]
[{"$nulls":3},"Zimbabwe"]

{"sheet":"Topic","index":5,"n_rows":95,"n_cols":10,"rows_kept":95,"hidden":true}
[]
["No.","Research area","Title of the research","Website","Name of supervisor","Title of the supervisor","Requirements for applicants: Master's / Ph.D. Student","Total number of acceptance per supervisor","Duration : 2-6months (less than 180days)","Comments"]
["P01101","Machine learning","Geometric analysis of machine learning models","https://mahito.nii.ac.jp","Mahito Sugiyama","Associate Professor","Ph.D.",2,"3 - 6 months","Legendre decomposition (information geometric tensor decomposition; NeurIPS2018): https://arxiv.org/abs/1802.04502\r\nMany-body approximation for tensors (NeurIPS2023): https://openreview.net/forum?id=5yedZXV7wt"]
["P01102","Machine learning","Geometric analysis of T-PRISM, a logic programming language based on tensor embedding for statistical modeling","https://mahito.nii.ac.jp","Mahito Sugiyama","Associate Professor","Ph.D.",2,"3 - 6 months","Legendre decomposition (information geometric tensor decomposition; NeurIPS2018): https://arxiv.org/abs/1802.04502\r\nT-PRISM: https://github.com/prismplp/prism"]
["P01103","Machine learning/Data mining","Machine learning for graphs","https://mahito.nii.ac.jp","Mahito Sugiyama","Associate Professor","Ph.D.",2,"3 - 6 months","Molecular Graph Generation by Decomposition and Reassembling: https://doi.org/10.1021/acsomega.3c01078"]
["P01201","Artificial Intelligence","Knowledge Graph Applications","http://www-kasm.nii.ac.jp/~takeda","Hideaki Takeda","Professor","Either",3,"3 - 6 months"]
["P01202","Artificial Intelligence","Building and Applications for Academic Knowledge Graph",null,"Hideaki Takeda","Professor","Either",3,"3 - 6 months"]
["P01203","Legal Informatics","Applying AI in the legal information processing","https://ds.rois.ac.jp/en_center7/","Hideaki Takeda","Professor","Either",3,"2 - 6 months"]
["P02001","Theoretical Computer Science","Sensitivity Analysis/Lipschitz Continuous Algorithms","https://arxiv.org/abs/2211.04674https://arxiv.org/abs/2111.02657https://arxiv.org/abs/2411.02744","Yuichi Yoshida","Professor","Ph.D.",3,"2 - 6 months"]
["P02002","Data Mining","Sensitivity Analysis/Lipschitz Continuous Algorithms","https://openreview.net/forum?id=VM7u8ecLrZVhttps://openreview.net/forum?id=boik01yhssB","Yuichi Yoshida","Professor","Ph.D.",3,"2 - 6 months"]
["P02003","Theoretical Computer Science","Spectral Graph Theory for Directed Graphs and Hypergraphs","https://arxiv.org/abs/2106.02353https://arxiv.org/abs/2201.07289","Yuichi Yoshida","Professor","Ph.D.",3,"2 - 6 months"]
["P02004","Theoretical Computer Science","Sublinear-time Algorithms","https://arxiv.org/abs/2204.08404https://arxiv.org/abs/2210.12601","Yuichi Yoshida","Professor","Ph.D.",3,"2 - 6 months"]
["P02101","Computational Complexity Theory","Meta-complexity, average-case complexity, pseudorandomness, and the Minimum Circuit Size Problem","https://eccc.weizmann.ac.il/report/2022/119/https://eccc.weizmann.ac.il/report/2021/058/","Shuichi Hirahara","Associate Professor","Either",2,"2 - 6 months","It is desirable that applicants have a conference publication in complexity theory."]
["P02701","Algorithmic game theory / Combinatorial optimization","Algorithmic studies on information design, correlated equilibria, and online learning","https://fujiik.github.io/","Kaito Fujii","Assistant Professor","Either",2,"2 - 6 months"]
["P03401","Robotics","Real-world robot learning",null,"Taisuke Kobayashi","Assistant Professor","Ph.D.",2,"4 - 6 months","Knowledge and experience of reinforcement learning and/or imitation learning are required. The details of the research contents will be decided by prior discussion."]
["P03501","Quantum information","Theoretical and/or numerical research on quantum information processing",null,"Akihito Soeda","Associate Professor","Either",1,"2 - 6 months"]
["P03601","Robotics olfaction, Mechatronics, System control engineering, Computational Neuroscience, Ethology","Modeling and Robot Implementation of Insect Locomotion Control Using Computational Neuroscience","https://sshigaki.jimdofree.com/research/","Shunsuke Shigaki","Assistant Professor","Ph.D.",1,"2 - 6 months"]
["P03701","Theoretical Computer Science","Parameterized Algorithms/Complexity","See e.g. https://arxiv.org/abs/2211.04278.","Philip Wellnitz","Assistant Professor","Ph.D.",2,"4 - 6 months"]
["P03702","Theoretical Computer Science","Fine-Grained Complexity Theory/Algorithm Design","See e.g. https://arxiv.org/abs/2305.06659 or https://arxiv.org/abs/2010.09096","Philip Wellnitz","Assistant Professor","Either",2,"4 - 6 months"]
["P03703","Theoretical Computer Science/Algorithm Engineering","Fast Approximate String Matching in Practice","Preference is given to longer stays.","Philip Wellnitz","Assistant Professor","Either",2,"4 - 6 months","The ultimate goal would be to implement (parts of) https://arxiv.org/abs/2004.08350, especially in the fully-compressed setting for Hamming distance. Efficient implementations might require theoretical results as well. Profound knowledge in C++ or Rust is preferred."]
["P03704","Theoretical Computer Science","Theoretical Foundations of Graphical Neural Networks and related topics","See e.g. https://arxiv.org/abs/2004.06595 or https://arxiv.org/abs/2311.08988","Philip Wellnitz","Assistant Professor","Ph.D.",2,"5 - 6 months"]
["P03901","Combinatorial Optimization","Parallel Combinatorial Optimization Solvers",null,"Ryo Kuroiwa","Assistant Professor","Ph.D.",2,"2 - 6 months"]
["P04001","Theoretical Computer Science","Categorical Software Verification","https://group-mmm.org/~kazuki/","Kazuki Watanabe","Assistant Professor","Either",2,"3 - 6 months","Our goal is to uncover and analyze underlying mathematical structures that govern software verification in an abstract setting. \r\nTo this end, we employ category theory as a primary theoretical framework, aiming to develop novel and efficient algorithms that build upon this categorical foundation.\r\nSome related references are: \r\nMayuko Kori, Kazuki Watanabe, and Jurriaan Rot. \"Initial Algebra Correspondence under Reachability Conditions.\" To Appear in LICS2025.\r\nKazuki Watanabe, Sebastian Junges, Jurriaan Rot, and Ichiro Hasuo. “A Unifying Approach to Product Constructions for Quantitative Temporal Inference.” OOPSLA2025.\r\nMayuko Kori, Kazuki Watanabe, Jurriaan Rot, and Shin-ya Katsumata, “Composing Codensity Bisimulations.” LICS2024.\r\nKazuki Watanabe, Clovis Eberhart, Kazuyuki Asada and Ichiro Hasuo. \"Compositional Probabilistic Model Checking with String Diagrams of MDPs\" CAV2023."]
["P04002","Software Verification","Optimisation and Heuristics for Efficient Verification Algorithms","https://group-mmm.org/~kazuki/","Kazuki Watanabe","Assistant Professor","Either",2,"3 - 6 months","We aim to develop efficient verification algorithms, particularly for probabilistic systems such as Markov decision processes, primarily leveraging convex and multi-objective optimization techniques.\r\nSome related references are: \r\nKazuki Watanabe, Marck van der Vegt, Sebastian Junges, and Ichiro Hasuo, “Compositional Value Iteration with Pareto Caching.” CAV2024.\r\nKazuki Watanabe, Marck van der Vegt, Ichiro Hasuo, Jurriaan Rot, and Sebastian Junges, “Pareto Curves for Compositionally Model Checking String Diagrams of MDPs.” TACAS2024."]
["P04003","Theory of Programming Language","Denotational Semantics for Software Verification","https://group-mmm.org/~kazuki/","Kazuki Watanabe","Assistant Professor","Either",2,"3 - 6 months","We investigate denotational semantics of higher-order languages with the aim of enabling efficient software verification for functional programs. \r\nOur current focus lies on computational effects and weakest preconditions; however, our research interests are not limited to these topics."]
["A00301","Software Engineering, Formal Methods, Generative AI, AI4SE","Generative AI for Trustworthy Software Engineering","https://research.nii.ac.jp/~f-ishikawa/en/call.html#internships","Fuyuki Ishikawa","Associate Professor","Either",5,"2 - 6 months"]
["A00302","Software Engineering, Testing, Deep Learning, Generative AI, SE4AI","Testing and Trust Exploration for AI Systems","https://research.nii.ac.jp/~f-ishikawa/en/call.html#internships","Fuyuki Ishikawa","Associate Professor","Either",5,"2 - 6 months"]
["A00601","Wireless and Mobile  Networks, Sensing, Signal Processing, AI/ML for wireless communications","Energy-efficient edge AI-based wireless networks design for Beyond 5G","https://research.nii.ac.jp/~megkaneko/","Megumi Kaneko","Professor","Either",3,"4 - 6 months","Required programming skills: Matlab, Python.\r\nBasic knowledge in wireless/digital communications and signal processing is required."]
["A00602","Wireless and Mobile  Networks, Sensing, Signal Processing, AI/ML for wireless communications","Joint wireless communications and sensing for IoT massive connectivity","https://research.nii.ac.jp/~megkaneko/","Megumi Kaneko","Professor","Either",3,"4 - 6 months","Required programming skills: Matlab, Python.\r\nBasic knowledge in wireless/digital communications and signal processing is required."]
["A00603","Wireless and Mobile  Networks, Sensing, Signal Processing, AI/ML for wireless communications","Integrated terrestrial and spatial wireless communications for 6G","https://research.nii.ac.jp/~megkaneko/","Megumi Kaneko","Professor","Either",3,"4 - 6 months","Required programming skills: Matlab, Python.\r\nBasic knowledge in wireless/digital communications and signal processing is required."]
["A01201","Programming Language Theory, Program Verification","Type-Based Temporal Verification and Its Automation","https://skymountain.github.io/","Taro Sekiyama","Associate Professor","Either",3,"4 - 6 months","This topic aims to develop an advanced type-based approach to verification of temporal properties, a class of properties about sequences of events, called traces. Real-world programs involve not only pure computation but also side effects, and many side effects have certain disciplines to be met. For example, file resources need to be opened first, and reading from and writing to them should be done before closing them, and opened files should be closed eventually. In this example, \"open\", \"read\", \"write\", and \"close\" are regarded as events on files, and the discipline of files to be met can be described as temporal properties about traces of such events. In this topic, we study 1) theory of temporal verification for higher-order programs and 2) implementation of verifiers to automate the temporal verification.\r\n\r\nReference\r\n- T. Sekiyama et al. Temporal Verification with Answer-Effect Modification. POPL'23.\r\n- T. Sekiyama et al. Algebraic Temporal Effects. POPL'25"]
["A01202","Programming Language Theory, Program Verification","Advanced Type Systems for Computational Effects","https://skymountain.github.io/","Taro Sekiyama","Associate Professor","Either",3,"4 - 6 months","Real-world programs involve side effects, such as memory, file, nondeterminism, and probability. This topic aims to study advanced type systems for uniformly verifying programs with such effects. As a means to express side effects in a uniform manner, we plan to focus on algebraic effect handlers, a programming construct able to model a variety of side effects. The expressivity of algebraic effect handlers comes from the ability to manipulate the notion of (delimited) continuations. Therefore, type systems to be studied need to effectively verify the use of continuations in programs. There are many directions and potentials to advance such type systems for algebraic effect handlers (the details will be discussed with applicants).\r\n\r\nReference\r\n-F. Kawamata et al. Answer Refinement Modification. POPL'24.\r\n-T. Sekiyama et al. Signature restriction for polymorphic algebraic effects. ICFP'20, JFP'24.\r\n- T. Yoshioka et al. Abstracting Effect Systems for Algebraic Effect Handlers. ICFP'24."]
["A01203","Programming Language Theory, Program Verification","Program Verification for Concurrency, Parallelism, and Distributed Computing","https://skymountain.github.io/","Taro Sekiyama","Associate Professor","Either",3,"4 - 6 months","Concurrency, parallelism, and distributed computing are techniques to distribute the computation over multiple processes or agents that interact with each other. They are fundamental to process big data or a large number of queries, but, on the other hand, they also make the systems complex, which hinders understanding and reasoning about the systems. The aim of this topic is to study a fundamental computational model of concurrent, parallel, or distributed systems and to develop verification techniques based on it. This is at an early stage of research, but there are a number of open questions worth exploring."]
["A01204","Security Verification, Refinement-based Verification","Modular Security Verification of Software Stacks","https://skymountain.github.io/","Taro Sekiyama","Associate Professor","Either",3,"4 - 6 months","Security verification guarantees the absence of vulnerability in software systems or protocols.  Computer systems consist of stack layers of software, such as firmware, hypervisor, OS, library, and user applications, from the bottom to top of the layers. The verification of each layer relies on some assumptions  on lower layers and guarantees some properties required by higher layers, where the assumptions and guarantees specify lower- and higher-level behavior respectively, so they may be described in different specification languages. The aim of this topic is at building a theoretical or practical framework for modular (layer-by-layer) security verification of  such software stack layers.\r\n\r\nReference\r\n- Deep Specifications and Certified Abstraction Layers. Ronghui Gu, et al. POPL'15."]
["A01701","Theoretical Computer Science","Categorical Foundation of Model Checking","https://group-mmm.org/~ichiro/","Ichiro Hasuo","Professor","Either",2,"3 - 6 months","Fixed-point specifications (such as in LTL and modal \\mu-calculus) have been conventionally studied in terms of finitary and combinatory structures (automata, games, etc.). These observations are recently being transferred to more abstract settings, opening up algorithms and proof methods for new application domains (esp. probabilistic, metric, etc.). There are a number of research questions waiting to be answered, both theoretical and algorithmic. \r\n\r\nReferences (you'll work on one line): \r\n- Fibrational line: [Komorida, Katsumata, Hu, Klin, Hasuo, LICS’19], [Komorida, Katsumata, Kupke, Rot, Hasuo, LICS'21], [Kori, Hasuo, Katsumata, CONCUR'21]\r\n- PDR line: [Kori+, CAV’22], [Kori+, CAV'23]\r\n- compositionality line: [Watanabe+, CAV'23] \r\n\r\n##  Desired: familiarity with mathematical and abstract reasoning used in logic, lattice theory and (possibly) category theory\r\n\r\n##  Interested? Please first consult https://group-mmm.org/eratommsd/internship-students/ (don't write an email to me)"]
["A01702","Theoretical Computer Science","Logical guidance in optimization metaheuristics","https://group-mmm.org/~ichiro/","Ichiro Hasuo","Professor","Either",2,"3 - 6 months","Many real-world optimization problems have inherent logical and discrete structures, but many optimization metaheuristics (stochastic optimization, hill-climbing, evolutionary computation, etc.) do not make explicit use of such structures. We have used hierarchical optimization frameworks where the upper logical layer guides the lower metaheuristics layer for efficiency and explainability. The goal is to push the idea further in other applications and theoretical foundations.\r\n\r\nReferences: [Zhang, Hasuo, Arcaini, CAV'19], [Zhang, Ernst, Sedwards, Arcaini, Hasuo, EMSOFT'18]\r\n\r\nDesired: familiarity with, or eagerness to learn, 1) formal logic, 2) optimization metaheuristics, 3) statistical machine learning\r\n\r\nInterested? Please first consult https://group-mmm.org/eratommsd/internship-students/ (don't write an email to me)"]
["A01703","Theoretical Computer Science","Logical safety for automated driving","https://group-mmm.org/~ichiro/","Ichiro Hasuo","Professor","Either",2,"3 - 6 months","Responsibility-sensitive safety (RSS) is a recently proposed methodology for devising mathematically-guaranteed safety rules for automated driving. The candidate will work on its logical foundations and its application to various driving scenarios. The work is much like interactive theorem proving, but with unique theoretical challenges (e.g. continuous dynamics) and a hot application (automated driving).\r\n\r\nReferences: [Hasuo, Eberhart, Haydon, et al., IEEE Trans. Intelligent Vehicles, ‘23 (available at arXiv)] [Shalev-Shwartz, Shammah, Shashua, arXiv'17]  \r\n\r\nDesired: familiarity with formal logic and interactive theorem proving, passion for bringing theory to practice\r\n\r\nInterested? Please first consult https://group-mmm.org/eratommsd/internship-students/ (don't write an email to me)"]
["A01704","Theoretical Computer Science","Logic and semantics for safe AI","https://group-mmm.org/~ichiro/","Ichiro Hasuo","Professor","Either",2,"3 - 6 months","We are interested in logical, semantical, and programming language techniques for safe AI. Most importantly, we will be combining discrete/symbolic/algebraic/logical structures with smooth/numeric/differentiable/fuzzy machine learning algorithms.\r\n\r\nReferences: [Zhang, Hasuo, Arcaini, CAV'19], [Hasuo, Eberhart, Haydon, et al., IEEE Trans. Intelligent Vehicles, ‘23 (available at arXiv)]\r\n\r\nDesired: familiarity with, or eagerness to learn, 1) formal logic, 2) statistical machine learning\r\n\r\nInterested? Please first consult https://group-mmm.org/eratommsd/internship-students/ (don't write an email to me)"]
["A01801","Computer network","Network security measurement and analysis","http://www.flab.nii.ac.jp/internship","Kensuke Fukuda","Professor","Either",3,"5 - 6 months","Solid programming and machine learning skills"]
["A01802","Computer network","LLMs and network configuration","http://www.flab.nii.ac.jp/internship","Kensuke Fukuda","Professor","Either",3,"5 - 6 months","Solid network operation and programming skills"]
["A01803","Computer network","IoT traffic anomaly detection","http://www.flab.nii.ac.jp/internship","Kensuke Fukuda","Professor","Either",3,"5 - 6 months","Solid programming and machine learning skills"]
["K00101","Natural language processing","Natural language understanding","http://www-al.nii.ac.jp","Akiko Aizawa","Professor","Either",4,"3 - 6 months"]
["K00102","Natural language processing","Deep analysis of scientific papers","http://www-al.nii.ac.jp","Akiko Aizawa","Professor","Either",4,"3 - 6 months"]
["K00401","Molecular biology","GEOScore3D: Quantitative Enhancement of Molecule-Based Discovery through Optimized QED and logP Prediction","http://research.nii.ac.jp/~andres/official/intern2025_ON_SITE_topic_1.htm","Frederic ANDRES","Associate Professor","Either",5,"6 months","cooperation with the  Japanese National Institute of Health Sciences (NIHS), The University of Nebraska at Omaha and The British University in Egypt,"]
["K00402","Biomathematics","AI-based mapping/activation state prediction of viral molecular pathways","http://research.nii.ac.jp/~andres/official/intern2025_ON_SITE_topic_2.htm","Frederic ANDRES","Associate Professor","Either",5,"6 months","Collaboration with Biomathematics experts and National Institute of Health Sciences"]
["K00403","High Performacne Computing","Securing High-Performance Computing: Addressing ABAC Challenges in Next-Generation HPC Service (Geom-SAC/Ontolearn)","http://research.nii.ac.jp/~andres/official/intern2025_ON_SITE_topic_3.htm","Frederic ANDRES","Associate Professor","Either",5,"6 months","cooperation with the  CNRS French Laboratory"]
["K00404","Molecular biology","GeoPharma3D: Customizable Geometric Deep Reinforcement Learning for Precision Pharmacotherapy","http://research.nii.ac.jp/~andres/official/intern2025_ON_SITE_topic_4.htm","Frederic ANDRES","Associate Professor","Either",5,"6 months","cooperation with the  Japanese National Institute of Health Sciences (NIHS) ,  The British University in Egypt, and the University of Nebraska at Omaha"]
["K00405","Data Science","OntoAI learning annotation service","http://research.nii.ac.jp/~andres/official/intern2025_ON_SITE_topic_5.htm","Frederic ANDRES","Associate Professor","Either",5,"6 months","Cooperation with IRISA Lab (France)"]
["K00406","Data Science","CiboLingua Revolution: The FusionFormer Challenge for Next-Generation Cooking Language Creation\"","http://research.nii.ac.jp/~andres/official/intern2025_ON_SITE_topic_6.htm","Frederic ANDRES","Associate Professor","Either",5,"6 months","Cooperation with CRWB project and IEEE ICDE"]
["K00407","Automation Control","Carbon-Conscious Production PLANning  (C2PLAN)","http://research.nii.ac.jp/~andres/official/intern2025_ON_SITE_topic_7.htm","Frederic ANDRES","Associate Professor","Either",5,"6 months","Cooperation with IRISA and Osaka University"]
["K00501","3D Computer Vision","- 3D Computer Vision- 3D reconstruction and visualization (single-view, multiview)- 3D human modeling and understanding- 3D scene reconstruction and analysis- 3D Generation (text-to-3D, image-to-3D, video-to-3D)","https://satoshi-ikehata.github.io/","Satoshi Ikehata","Associate Professor","Ph.D.",2,"3 - 6 months","Required:\r\n- Research experience in Computer Vision or Deep Learning\r\n- Strong coding skills in Deep Learning frameworks\r\n- Experience in writing scientific papers (including theses)\r\nDesired:\r\n- Knowledge of 3D Computer Vision\r\n- Publication record in international conferences/journals\r\n- Experience in submitting research proposals\r\nIf you are interested in this topic, please send:\r\n- Your CV\r\n- A document explaining your research experience and the topic you are interested in\r\n- Bachelor’s or Master’s thesis\r\n- Conference or journal papers (optional)\r\n- Research proposals (optional)\r\n*I plan to accept two students from all the topics"]
["K00502","3D Sensing and Computational Photography","- 3D sensing and Computational Photography- Multispectral Analysis Photometric Stereo- Shape-from-X (e.g., shape from polarization)- Physics-based Vision","https://satoshi-ikehata.github.io/","Satoshi Ikehata","Associate Professor","Ph.D.",2,"3 - 6 months","Required:\r\n- Research experience in Computer Vision or Deep Learning\r\n- Strong coding skills in Deep Learning frameworks\r\n- Experience in writing scientific papers (including theses)\r\nDesired:\r\n- Knowledge of 3D Computer Vision\r\n- Publication record in international conferences/journals\r\n- Experience in submitting research proposals\r\nIf you are interested in this topic, please send:\r\n- Your CV\r\n- A document explaining your research experience and the topic\r\nyou are interested in\r\n- Bachelor’s or Master’s thesis\r\n- Conference or journal papers (optional)\r\n- Research proposals (optional)\r\n*I plan to accept two students from all the topics"]
["K01001","Digital Humanities","Machine learning for image processing (esp. character recognition), geographic information, linked data, metadata management, and data infrastructure for cultural big data","https://agora.ex.nii.ac.jp/~kitamoto/education/internship/index.html.en","Asanobu Kitamoto","Professor","Either",4,"3 - 6 months","Programming skills are required, and collaboration with domain experts is requested for an interdisciplinary theme."]
["K01002","Earth Environmental Informatics","Big data analytics (esp. image processing, remote sensing, and machine learning) for solving environmental and societal problems","https://agora.ex.nii.ac.jp/~kitamoto/education/internship/index.html.en","Asanobu Kitamoto","Professor","Either",4,"3 - 6 months","Programming skills are required, and collaboration with domain experts is requested for an interdisciplinary theme."]
["K01003","Crisis Informatics","Big data analytics (esp. image processing, natural language processing, and machine learning) for natural disasters and crisis","https://agora.ex.nii.ac.jp/~kitamoto/education/internship/index.html.en","Asanobu Kitamoto","Professor","Either",4,"3 - 6 months","Programming skills are required, and collaboration with domain experts is requested for an interdisciplinary theme."]
["K01004","Open Science","Research on a new trend in science, such as open data, data citation, citizen science, and open innovation","https://agora.ex.nii.ac.jp/~kitamoto/education/internship/index.html.en","Asanobu Kitamoto","Professor","Either",4,"3 - 6 months","Programming skills are required, and collaboration with domain experts is requested for an interdisciplinary theme."]
["K01301","Computer Vision and Computer Graphics","Computational Photography: Deep learning, Image-based rendering, Image processing, Color analysis, Spectral imaging","http://research.nii.ac.jp/~imarik/http://research.nii.ac.jp/pbv/","Imari Sato","Professor","Either",3,"5 - 6 months","A basic knowledge of Image Analysis and/or Machine learning, and  good programming skills are required"]
["K01302","Computer Vision and Application","3D medical image analysis, Deep learning,  Image processing, Color analysis, Spectral imaging","http://research.nii.ac.jp/~imarik/http://research.nii.ac.jp/pbv/","Imari Sato","Professor","Either",3,"5 - 6 months","A basic knowledge of Image Analysis and/or Machine learning, and  good programming skills are required"]
["K01401","Content-Based Image and Video Analysis","General image analysis topics, e.g., image semantic analysis, semantic segmentation, classification, image captioning, image retrieval, and so on.  Landmark image retrieval can be considered, e.g., Google Landmark Image Retrieval https://www.kaggle.com/competitions/landmark-retrieval-2021","http://www.satoh-lab.nii.ac.jp/","Shin'ichi Satoh","Professor","Either",3,"2 - 6 months"]
["K01402","Content-Based Image and Video Analysis","General video analysis topics, e.g., video semantic analysis, video segmentation, classification, video captioning, video retrieval, and so on.  TRECVID ad-hoc video retrieval (AVS), or Video Question Answering (VQA), can be considered. https://trecvid.nist.gov/","http://www.satoh-lab.nii.ac.jp/","Shin'ichi Satoh","Professor","Either",3,"2 - 6 months"]
["K01601","computer vision","One of the following topics (but not limited to):(1) 3D vision, (2) Human activity recognition,  (3) Vision and language, (4) Object detection and segmentation from video using deep learning, (5) Image/video generation using deep learning.","http://www.dgcv.nii.ac.jp","Akihiro Sugimoto","Professor","Either",5,"4 - 6 months","Longer duration is better.\r\nRigorous background on mathematics is required.  Strong programming skills on image processing and computer vision are also required.  In the case of Master course students, highly motivated students who can stay for 6 months are preferable.  Students who are willing to pursuit ph.D at NII are preferable as well.  Potential applicants should send your CV and research interests/proposals directly to Prof. Sugimoto before your application."]
["K01602","digital geometry","(1) Discretization model of geometric shape,  (2) Discrete shape fitting to noisy integer points,(3) Any proposed topic related with digital geometry.","http://www.dgcv.nii.ac.jp","Akihiro Sugimoto","Professor","Either",5,"3 - 6 months","Rigorous background on mathematics as well as computer vision is required.  In particular, strong knowledge on linear algebra, graph theory, and number theory is important requirements.  Programming skills on image processing or computer vision are also required.  Potential applicants should send your CV and research interests/proposals directly to Prof. Sugimoto before your application."]
["K01701","Data Mining","Recommender System","https://www.tlab.nii.ac.jp/","Atsuhiro Takasu","Professor","Either",3,"4 - 6 months"]
["K01702","Data Mining","Tabular Data Recognition and Analysis","https://www.tlab.nii.ac.jp/","Atsuhiro Takasu","Professor","Either",3,"4 - 6 months"]
["K01703","Data Mining","Sequence Data Mining","https://www.tlab.nii.ac.jp/","Atsuhiro Takasu","Professor","Either",3,"4 - 6 months"]
["K02001","Financial Time Series Forecasting","Deep Learning and Foundation Models for Stock/Crypto Market Prediction","https://research.nii.ac.jp/~prendinger/papers/FY2025(2)_Topics.html","Helmut PRENDINGER","Professor","Either",3,"4 - 6 months","We investigate the potential of Deep Learning and time series foundation models for predicting the price action of stocks and crypto assets as a basic component for swing trading strategies. Deep Learning methods for time series forecasting include Convolutional Neural Networks (CNNs) and Transformers. Time series foundation models are either trained on massive text corpora, i.e., Large Language Models (LLMs), or massive time series data. Our approach builds on the concept of a “Corrective AI” system, in which a primary model forecasts market movements and a secondary, corrective model estimates the reliability of these predictions. In this way, accuracy and precision can be improved significantly. (Please check the link for Github repositories and references.)"]
["K02002","Financial Time Series Forecasting","Development of Adaptive Time Series Models for Stock/Crypto Market Prediction","https://research.nii.ac.jp/~prendinger/papers/FY2025(2)_Topics.html","Helmut PRENDINGER","Professor","Either",3,"4 - 6 months","We investigate the potential of deep learning and time series foundation models to predict the price action of stocks and crypto assets as a core component of swing trading strategies. Financial time series exhibit challenging characteristics for learning algorithms. In particular, distributional shifts occur when statistical properties such as the mean and variance change over time; volatility may vary dynamically (heteroskedasticity); and, in some cases, the entire distribution can shift abruptly (regime change). Because a “one-model-fits-all-markets” approach is unlikely to be robust, we aim to develop an adaptive time series model capable of adjusting to these evolving market conditions. . (Please check the link for Github repositories and references.)"]
["K02003","Token Economy, Crypto Token, Smart Contract","A Crypto Token for Advanced Air Mobility","https://research.nii.ac.jp/~prendinger/papers/FY2025(2)_Topics.html","Helmut PRENDINGER","Professor","Either",3,"4 - 6 months","We develop a crypto token for AAM, based on ideas from token economy (Web3). Our studies include: (i) Development of a AAM related crypto token, (ii) Use of blockchain in an AAM simulator, (iii) Development of Smart Contracts with Solidity.  (Please check the link for Github repositories and references.)"]
["K02101","Image Processing","sign language recognition (SLR), sign language translation (SLT)",null,"Mayumi Bono","Associate Professor","Ph.D.",2,"2 - 6 months"]
["K02102","Natural Language Processing","sign language recognition (SLR), sign language translation (SLT)",null,"Mayumi Bono","Associate Professor","Ph.D.",2,"2 - 6 months"]
["K02301","Speech processing","Beyond robustness: investigating DNN-based speech audio watermark against security attacks","Relevant but not limited to [1] For background on audio watermark robustness, https://openreview.net/pdf?id=44TCZ5XTuR, https://arxiv.org/abs/2406.06979, https://arxiv.org/abs/2505.19663[2] For example of security issue of ownership, https://doi.org/10.1109/49.668979[3] For example of security issue of key management, https://10.1109/TSP.2005.855418[4] Collision attack in LLM watermark: https://arxiv.org/pdf/2403.10020","Junichi Yamagishi","Professor","Ph.D.",4,"5 - 6 months","This topic is not on how watermark is robust to degradation or manipulation but on how watermark can be secure if the attacker, for example, conducts collision attack. The successful candidate should be a PhD student in speech processing, computer science, or a related discipline. Familiarity with DNN tools (e.g., Pytorch) and speech tools are preferable. Supervision teams include Dr. Xin Wang, Dr. Wanying Ge"]
["K02302","Speech processing","Voice Collision on voice privacy protection","Relevant but not limited to [1] For background, please check https://www.voiceprivacychallenge.org/[2] For analysis approach that may be tried, please check Introduction of A Graduate Course in Applied Cryptography https://toc.cryptobook.us/","Junichi Yamagishi","Professor","Ph.D.",4,"5 - 6 months","Will an anonymized voice collides with unseen real speaker's voice? How to quantize it in a large population? The successful candidate should be a PhD student in speech processing, computer science, or a related discipline. Familiarity with DNN tools (e.g., Pytorch) and speech tools are preferable. Supervision teams include Dr. Xin Wang"]
["K02303","Speech processing","Limitations of Post-Trained Deepfake Speech Detectors","[1] Post-trained model: https://arxiv.org/pdf/2506.21090[2] Audio deepfake datasets: https://arxiv.org/pdf/2410.09732[3] Audio deepfake datasets: https://arxiv.org/pdf/2503.02857","Junichi Yamagishi","Professor","Ph.D.",4,"5 - 6 months","This topic focuses on analyzing the failure cases of large-scale deepfake speech detectors trained on large amounts of data. We aim to examine factors such as emotion, background noise, and self-collected speeches, and explore ways to improve performance without compromising the detector’s original capabilities. The successful candidate should be a PhD student in speech processing, computer science, or a related discipline. Familiarity with DNN tools (e.g., PyTorch) and speech processing tools is preferable. The supervision team includes Dr. Wanying Ge and Dr. Xin Wang."]
["K02304","Speech processing","Tracing Deepfake Speeches Generated by Variants of the Same Model","[1] Impact of training on artifacts: https://arxiv.org/abs/2406.18278[2] Network architecture attribution: https://arxiv.org/abs/2202.13843[3] Source tracing: https://arxiv.org/pdf/2507.06470","Junichi Yamagishi","Professor","Ph.D.",4,"5 - 6 months","This topic investigates whether a source tracing model can correctly classify deepfakes generated by variants of a known model, and whether such variants should be classified as a new class or handled by improving the model’s generalization ability. The successful candidate should be a PhD student in speech processing, computer science, or a related discipline. Familiarity with DNN tools (e.g., PyTorch) and speech processing tools is preferable. The supervision team includes Dr. Wanying Ge."]
["K02305","Speech processing","Effectively leveraging speaker and attribute information for realistic audio deepfake detection","For prior study on speaker-aware anti-spoofing and interpretability, please check [1] https://arxiv.org/abs/2303.01126[2] https://arxiv.org/abs/2412.18191For speaker and speech profile attribute recognition, please check[3] https://arxiv.org/abs/2505.14648","Junichi Yamagishi","Professor","Ph.D.",4,"5 - 6 months","This research aims at investigating what kind of speaker and their related information is useful and what is not for effective audio deepfake detection. The successful candidate should be a PhD student familiar with audio deepfake detection and have minor prior knowledge on speaker recognition. Supervision team includes Dr. Xuechen Liu."]
["K02306","Natutal language processing, Computer vision","Visual Commonsense Reasoning for Scientific Claims","For scientific claims and high-density figures (e.g. charts, diagrams), please check[1] https://www.arxiv.org/pdf/2506.04585[2] https://aclanthology.org/2025.acl-long.420.pdf For background, please check[1] https://aclanthology.org/2023.findings-emnlp.361.pdf[2] https://aclanthology.org/2024.acl-long.775.pdf","Junichi Yamagishi","Professor","Ph.D.",4,"5 - 6 months","Fact-check scientific claims by grounding them in figures, charts, and images from scientific papers—requiring models to interpret scientific visuals (e.g., graphs, microscopy images) alongside textual claims. The successful candidate should be a PhD student in NLP, computer vision, computer science, or a related discipline. He or she should have strong programming skills. Familiarity with DNN tools (e.g., Pytorch) and CV tools are preferable. Supervision teams include Dr. Iffat Maab."]
["K02307","Music & speech processing","Audio Effect Parameter Estimation with Invertible Neural Networks (INN)","[1] https://arxiv.org/abs/2308.16177[2] https://arxiv.org/abs/2502.14405[3] https://arxiv.org/abs/2310.11781[4] https://arxiv.org/pdf/2404.06928","Junichi Yamagishi","Professor","Ph.D.",4,"5 - 6 months","This project aims at applying Invertible Neural Networks (INNs) to model and reverse audio effect chains, enabling accurate parameter recovery and edit detection. INNs handle nonlinear transformations and quantify uncertainty, supporting robust analysis of music and speech. Supervision teams include Dr. Yigitcan Özer and Dr. Zhe Zhang."]
["K02308","Music & audio processing","Guitar Effect Identification and Timbre Reconstruction","[1] https://arxiv.org/abs/2012.03216[2] https://doi.org/10.1186/s13636-022-00257-4[3] https://dl.acm.org/doi/abs/10.1186/s13636-024-00330-0","Junichi Yamagishi","Professor","Ph.D.",4,"5 - 6 months","This project explores applying deep neural networks to recognize active guitar effects in recorded audio and accurately estimate their parameter settings, including in chained multi-effect configurations. It builds upon state‑of‑the‑art research in audio parameter estimation and classification, aiming to create an end‑to‑end pipeline for detecting vaious effects and reconstructing the timbre with predicted parameters. Supervision teams include Dr. Yigitcan Özer and Dr. Zhe Zhang."]
["K02309","Image Processing","Deepfake detection and source attribution for general images at scale with many generative models","For a foundational overview, please refer to:[1] https://arxiv.org/abs/2307.01426For scalable deepfake detection of general images and potential attribution to generative models, please see:[2] https://arxiv.org/abs/2411.04125v2","Junichi Yamagishi","Professor","Ph.D.",4,"5 - 6 months","The successful candidate should be a PhD student in speech processing, computer science, or a related discipline. He or she should have strong programming skills. Familiarity with DNN tools (e.g., Pytorch) and speech tools are preferable. Supervision teams include Dr. Yusuke Yasuda."]
["K02310","Speech Processing","Automatic quality prediction of synthetic speech beyond mean opinion scores","Relevant but not limited to [1] For background, please check https://sites.google.com/view/voicemos-challenge[2] For related methods, please check https://arxiv.org/abs/2308.15203https://arxiv.org/abs/2204.02152","Junichi Yamagishi","Professor","Ph.D.",4,"5 - 6 months","The successful candidate should be a PhD student in speech processing, computer science, or a related discipline. He or she should have strong programming skills. Familiarity with DNN tools (e.g., Pytorch) and speech tools are preferable. Supervision teams include Dr. Yusuke Yasuda."]
["K02311","Computer Vision","From shallow deepfake detection to deep deepfake understanding","[1] https://arxiv.org/html/2506.00868v1[2] https://arxiv.org/pdf/2406.08772[3] https://arxiv.org/pdf/2505.16512","Junichi Yamagishi","Professor","Ph.D.",4,"5 - 6 months","This project aims to develop a novel deepfake detection model capable of understanding and identifying forgeries that manipulate an image's context or narrative, moving beyond the limitations of methods focused solely on facial swaps. The research will concentrate on training a model to reason about conceptual and semantic inconsistencies within person-centric scenes. The successful candidate should be a PhD student in a Computer Vision or Deep Learning related discipline, with strong programming skills. Familiarity with DNN tools like PyTorch and Large Language Models (LLMs) is preferred. The supervision team includes Dr. Surbhi Madan."]
["K02901","Natural Language Processing","Better evaluation of large language models: evaluation methods and task design","https://penzant.net","Saku Sugawara","Assistant Professor","Either",2,"4 - 6 months","https://aclanthology.org/2024.emnlp-main.905/\r\nhttps://aclanthology.org/2023.emnlp-main.9/\r\nhttps://aclanthology.org/2023.acl-short.53/\r\nhttps://aclanthology.org/2023.findings-acl.861/\r\n\r\nWhen you reach out to me, please mention what kind of tasks or linguistic phenomena you are interested in for evaluation (e.g., by referring to recent papers)."]
["K02902","Natural Language Processing","Understanding language models through the lens of human language acquisition","https://penzant.net","Saku Sugawara","Assistant Professor","Either",2,"4 - 6 months","https://aclanthology.org/2024.emnlp-main.1146/\r\nhttps://aclanthology.org/2024.findings-acl.865/\r\nhttps://aclanthology.org/2024.findings-acl.913/\r\n\r\nWhen you reach out to me, please mention what aspect of language modeling or human language acquisition you are interested in (e.g., by referring to recent papers)."]
["K03501","Audio Processing","Physics-informed machine learning for spatial audio processing","https://www.ap.nii.ac.jp/","Shoichi Koyama","Associate Professor","Either",3,"3 - 6 months","Knowledge of deep learning,  signal processing, and acoustics is required. Programming skills in Python or Julia are also required. \r\nReference: Koyama, et al., IEEE SPM 2025, Ribeiro, et al. IEEE/ACM TASLP 2024."]
["K03502","Audio Processing","Spatial active noise cancelling","https://www.ap.nii.ac.jp/","Shoichi Koyama","Associate Professor","Either",3,"3 - 6 months","Knowledge of adaptive signal processing and acoustics is required. Programming skills in Python are also required. \r\nReference: Koyama, et al. IEEE TASLP 2021."]
["K03503","Audio Processing","Head-related transfer function personalization for VR audio","https://www.ap.nii.ac.jp/","Shoichi Koyama","Associate Professor","Either",3,"3 - 6 months","Knowledge of deep learning,  signal processing, and acoustics is required. Programming skills in Python are also required. \r\nReference: Ito, et al. IWAENC 2022, Niu, et al. WASPAA 2025."]
["K03701","Generative AI, Computer Vision, Large Language Models","One of the following topics for Computer Vision and Language Modeling: 1) Efficient architectures (e.g., auto-regressive models and diffusion models), 2) Efficient training and/or inference of the foundation models.","https://layneh.github.io/","Lang HUANG","Assistant Professor","Either",3,"3 - 6 months","Please send me 1) your CV, 2) a short description of your background, and 3) the topics you would like to explore with me.\r\n\r\nReference:\r\nhttps://arxiv.org/abs/2205.13515\r\nhttps://arxiv.org/abs/1907.12273\r\nhttps://arxiv.org/abs/2207.05557"]
["K03702","Generative AI, Computer Vision, Large Language Models","Data Efficient Learning for Computer Vision and Language Modeling, with its applications to visual and multi-modal understanding and generation","https://layneh.github.io/","Lang HUANG","Assistant Professor","Either",3,"3 - 6 months","Please send me 1) your CV, 2) a short description of your background, and 3) the topics you would like to explore with me.\r\n\r\nReference:\r\nhttps://arxiv.org/abs/2002.10319\r\nhttps://arxiv.org/abs/2203.14898\r\nhttps://arxiv.org/abs/2502.20008"]
["K03703","Deep Learning, Weight Space Learning","Analysis, Composition, and Generation in the Weight Space","https://layneh.github.io/","Lang HUANG","Assistant Professor","Either",3,"3 - 6 months","This is an emergent (and exciting) topics in the Deep Learning and Machine Learning community. \r\nThe candidates can refer to the Weight Space Learning workshop at ICLR for a general sense of the research: https://openreview.net/pdf?id=Bz6wEdobY7\r\nFor example, we are interested in the specific applications like model merging and model generation:\r\nhttps://arxiv.org/pdf/2203.05482\r\nhttps://arxiv.org/abs/2402.13144\r\n\r\nPlease send me 1) your CV, 2) a short description of your background, and 3) the topics you would like to explore with me."]
["J00301","AI Security","Fake Information Generation Technology and Attack Technology Using Fake Information (e.g., Fraudulent human perception and cognition, Attacks on biometric and large-scale AI models)","https://research.nii.ac.jp/~iechizen/synthetiq-x/en/research.htmlhttps://research.nii.ac.jp/~iechizen/official/research/research5-e.html","Isao Echizen","Professor","Either",8,"3 - 6 months"]
["J00302","AI Security","Technology to Protect Spread of Fake Information (e.g., Authenticity judgment, Estimation of tampering area, Provenance management, Cross-modal judgment)","https://research.nii.ac.jp/~iechizen/synthetiq-x/en/research.htmlhttps://research.nii.ac.jp/~iechizen/official/research/research5-e.html","Isao Echizen","Professor","Either",8,"3 - 6 months"]
["J00303","AI Security","Technology to Prevent Spread of Fake Information (e.g., Makes collection of training data difficult, Disables generation of fake information, Purification of training data)","https://research.nii.ac.jp/~iechizen/synthetiq-x/en/research.htmlhttps://research.nii.ac.jp/~iechizen/official/research/research5-e.html","Isao Echizen","Professor","Either",8,"3 - 6 months"]
["J00304","AI Security and Social Sciences/Cognitive Sciences","Innovative Methodologies to Prevent Deception in Human Perception and Cognition (Joint research with Media Bias Group)","https://research.nii.ac.jp/~iechizen/synthetiq-x/en/research.htmlhttps://media-bias-research.org/","Isao Echizen","Professor","Either",8,"3 - 6 months"]
["J02401","Information Retrieval, Natural Language Processing","On-Device Information Retrieval","https://www.mpkato.net/","Makoto Kato","Associate Professor","Either",2,"2 - 6 months","This research aims to design a novel information retrieval system that operates entirely on laptops, leveraging on-screen information to enable highly personalized retrieval. The system will integrate capabilities from both LLMs and VLMs. Applicants are expected to have a basic understanding of LLMs and VLMs."]
["J02402","Information Retrieval, Natural Language Processing","Multilingual Information Retrieval for Scientific Documents","https://www.mpkato.net/","Makoto Kato","Associate Professor","Either",2,"2 - 6 months","This research aims to develop multilingual retrieval models tailored for scientific documents. LLM-based neural retrieval systems will serve as the foundation, which will be fine-tuned on domain-specific corpora such as scientific papers. Applicants are expected to have prior experience in fine-tuning language models (e.g., BERT and LLaMA) and familiarity with information retrieval tasks."]