Find Academic Supervisors

Clark AndrewView profile

Research Professor

• Labour economics
• Subjective well-being
• Health
• +4 more

Clark Andrew is a CNRS Research Professor at the Paris School of Economics (PSE), with a career spanning institutions like the University of Sheffield, DELTA, and LEO. His work bridges economics, psychology, and sociology, focusing on subjective well-being, labor market dynamics, and health economics. Current affiliation: Paris School of Economics (PSE), France Academic rank: CNRS Research Professor (Classe Exceptionnelle) Research areas: Labour economics, Subjective well-being, Health, Social interactions Research Focus: Specializes in analyzing job and life satisfaction as proxies for utility, exploring income comparisons, habituation to life events, and social learning in economic contexts. Collaborates with psychologists and public health experts to study adaptation patterns using panel data. Scientific Awards: Web of Science Highly-Cited Researcher Elsevier China Economic Review Best Paper Award 2023 Alexandre Pedrós Prize 2023 Academy of Europe Membership Publications: Over 500 presentations in 30+ countries, with key works on unemployment's psychological impact, income comparisons, and pandemic well-being. Notable grants include ERC Advanced Grant and NERC Large Grant. Collaborations: Works with institutions across Europe, Japan, and the US, including collaborations with psychologists and public health researchers.

Andrew David CliffView profile

Professor

• Geographical processes and disease emergence
• World Geography of poliomyelitis
• Theory of spatial processes
• +1 more

Andrew David Cliff is a Professor at the Department of Geography, University of Cambridge, with a career spanning over five decades. He has held significant administrative roles including Head of Department (1999-2001), Chair of the School of Physical Science (2001-03), and Pro-vice-counsellor since 2004. Education: PhD and DSc from the University of Bristol Research Focus: Geography of epidemics, spatial processes, historical disease mapping, and conflict-related health crises Cliff's research explores the intersection of geography and public health, emphasizing the spatial dynamics of infectious diseases across historical contexts. His work includes groundbreaking studies on avian influenza, poliomyelitis, cholera, and smallpox, often analyzing their diffusion in war zones and isolated regions. His publications from 2000-2008 highlight interdisciplinary approaches combining geography, epidemiology, and historical analysis, with a focus on computational frameworks, island epidemiology, and the role of conflict in disease spread. Key journals include Annals of the Association of American Geographers and Medical History. Member, Academia Europaea (2002) Member, Historical and Cultural Geography research cluster Editorial Board, Statistical Methods in Medical Research Fellow of the Society of Study (FSS 1968) Fellow of the British Academy (FBA 1996) Chartered Geographer (CGeog 2002) Cliff has been affiliated with Christ's College, Cambridge, as Director of Studies (1973-) and Fellow (1974-). He has also collaborated with global institutions like the WHO and CDC through visiting scholar roles.

Enrique Herrera ViedmaView profile

Professor

• Digital libraries
• Intelligent decision making systems
• Computational intelligence
• +8 more

Enrique Herrera-Viedma is a Full Professor in Computer Science and AI at the University of Granada (UGR) since 2007. He currently serves as Vice-President for Research and Knowledge Transfer at UGR (2015-present) and held leadership roles in IEEE System, Man & Cybernetics Society, including Vice-President for Publications (2019-2020) and Vice-President for Cybernetics (2021-2023). His research spans computational intelligence, fuzzy decision-making systems, and consensus models. IEEE Fellow (2021) IFSA Fellow (2021) Highly Cited Researcher (Computer Science, Engineering) by Clarivate Analytics (2014-2020) Andrew P. Sage Best Transactions Paper Award (2016) 2011 IEEE Transactions on Fuzzy Systems Outstanding Paper Award His publications focus on consensus reaching processes , computing with words , linguistic modeling , and social network analysis . His work integrates fuzzy systems , optimization models , and trust mechanisms in group decision-making contexts. Articles highlight distributed linguistic trust , non-cooperative behavior management , and feedback mechanisms to enhance decision-making efficiency. He contributes to prestigious institutions like the Royal Institute Elcano (Spain) and Ulster University's Artificial Intelligence Research Center. His h-index (85 in WoS, 101 in Google Scholar) reflects his significant impact, with over 560 peer-reviewed papers and 50 highly cited works.

Hervé MoulinView profile

Professor

• Cooperative Game Theory
• Social Choice
• Incentive Compatibility
• +5 more

Hervé Moulin is the D.J. Robertson Chair in Economics at the University of Glasgow, where he has been since 2013. Prior to this, he held professorial positions at Rice University, Duke University, and Virginia Polytechnic Institute. His academic journey began with a PhD in Mathematics from the Université de Paris in 1975, following his graduation from the École Normale Supérieure in 1971. His research focuses on cooperative game theory, social choice, incentive compatibility, and fair division mechanisms. Moulin has significantly contributed to redefining normative economics, particularly in designing fair resource allocation systems for scenarios like voting, asset division, and rationing. His work bridges theoretical foundations with practical applications in areas such as traffic pricing, communication networks, and commons exploitation. Moulin has been honored as a Fellow of the Econometric Society (1983), the Royal Society of Edinburgh (2015), and the British Academy (2018). He served as President of the Society for Social Choice and Welfare (1998–1999) and the Game Theory Society (2018–2020). His contributions include over 140 peer-reviewed articles and five books, emphasizing the intersection of mathematics, economics, and social choice theory.

• Distributed Computing
• Graph Algorithms
• Theoretical Computer Science
• +3 more

Yannic Maus is a Professor at Graz University of Technology, affiliated with the Institute of Algorithms and Theory and the Institute of Software Engineering and Artificial Intelligence. His research focuses on distributed computing, graph algorithms, and theoretical computer science. He holds a PhD and multiple bachelor’s and master’s degrees in Computer Science. His work emphasizes distributed graph coloring, locality in algorithms, and massively parallel computing. He has contributed to foundational results in distributed algorithms, including optimal edge coloring and coloring hyperbolic random graphs. His research bridges theoretical insights with practical distributed systems challenges. Education: PhD in Natural Sciences (Dr.rer.nat.), B.Sc. and M.Sc. in Computer Science Key research interests include distributed algorithms for graphs, Lovász Local Lemma applications, and algorithmic efficiency in dynamic networks. His publications explore topics like ruling sets in trees, exponential speedups in MPC models, and adaptive coloring techniques for sparse graphs. He has also investigated the algorithmic small-world phenomenon and connectivity in forests using deterministic approaches. Yannic Maus’s work often addresses theoretical lower bounds and upper limits in distributed computing, with applications to real-world networked systems. His contributions span conferences like DISC and SoCG, focusing on both foundational problems and their algorithmic solutions.

• Randomized Algorithms
• Networking
• Social Networks
• +7 more

Aravind Srinivasan is a Professor of Computer Science at the University of Maryland, College Park, USA. He holds tenure and has held academic positions at the National University of Singapore and Bell Labs. He completed his B.Tech at IIT Madras and his Ph.D. at Cornell University, with postdoctoral research at the Institute for Advanced Study and DIMACS. His research focuses on randomized algorithms, networking, social networks, combinatorial optimization, and their applications to public health, machine learning, and energy systems. He has published over 115 papers in top journals like Nature and the Journal of the ACM, and his work has received significant recognition, including 1,551 citations for his 2004 Nature paper on disease modeling. Education: B.Tech, Indian Institute of Technology Madras Ph.D., Cornell University Awarded Fellowships from ACM, AAAS, IEEE, and EATCS, he also serves as Editor-in-Chief of the ACM Transactions on Algorithms. His students have secured roles in academia, industry, and government, reflecting his impactful mentorship. His contributions span theoretical computer science and applied domains, with notable work in probabilistic methods, network science, and interdisciplinary applications.

Zomaya AlbertView profile

Academic

• Complex systems
• Parallel and distributed computing
• Sustainable computing
• +7 more

Dr. Zomaya is the Chair Professor of High Performance Computing & Networking and Founding Director of the Centre for Distributed & High Performance Computing at the University of Sydney, Australia. He has held leadership roles including Deputy Head of School and Head of School at The University of Western Australia and the University of Sydney. A Fellow of AAAS, IEEE, and IET, he leads research in distributed computing systems, sustainable computing, and edge intelligence. His research spans parallel/distributed computing, energy-efficient systems, and cloud/edge technologies. He has published over 600 papers, authored/edited 20+ books, and secured $22M+ in funding from ARC, Cisco, IBM, and others. He currently supervises 12 PhD students and has mentored 35 PhD completions. Key awards include the ACM MSWIM 2017 Fessenden Award and IEEE Technical Achievement Award (2014). He serves as Editor-in-Chief of IEEE Transactions on Sustainable Computing and has chaired over 700 conferences. His current projects focus on data analytics over cloud/edge platforms and holistic energy-aware scheduling for distributed systems.

Pietro Lio'View profile

Professor

• Computational Biology
• Bioinformatics
• Machine Learning
• +2 more

Pietro Lio' is a Professor of Computational Biology at the University of Cambridge's Department of Computer Science and Technology, where he has held academic positions since 2003. He progressed from Lecturer to Senior Lecturer, Reader, and ultimately Professor (2018-present). His career includes prior roles as Associate Professor of Genetics at the University of Teramo and research positions at the European Bioinformatics Institute, University of Cambridge (Genetics/Zoology), and University of Southampton. Education: 1989: BSc in Electronic Engineering and Biology, University of Firenze 1995: PhD in Theoretical Genetics, University of Pavia 2007: PhD in Engineering (Non-Linear Dynamics & Complex Systems), University of Firenze Research Focus: Professor Lio' specializes in interdisciplinary approaches bridging computer science and biology. His primary research domains include computational biology, bioinformatics algorithms, machine learning (particularly graph neural networks), deep learning architectures, and complex network analysis. His work spans molecular to ecological scales, with applications in genomics, systems biology, and environmental modeling. Publication Trends: Recent work (2018-2020) demonstrates strong emphasis on graph neural networks (Graph Attention Networks, Deep Graph Infomax) and blockchain applications. Earlier publications (2015-2017) focus on ecological modeling, multi-omics integration, molecular communications, and single-cell genomics, reflecting consistent cross-disciplinary innovation. Awards and Honors: 2018: BITS Award (Bioinformatics Italian Society) 2017: Visiting Professorship at University of Padova 2016: BYRA First Prize (ISEM) & MCE Award Second Prize 2013-2015: Lagrange Fellowship 2011: European Commission Award for methodological innovation No information is available regarding student advising, grants, labs, or research teams in the provided materials.

Matiyasevich YuriView profile

Professor

• Diophantine equations
• Computability theory
• Algorithms
• +1 more

Yuri Matiyasevich is a Russian mathematician and computer scientist affiliated with the Steklov Institute of Mathematics (Leningrad/St.Petersburg Branch) since 1980, where he serves as head of the Laboratory of Mathematical Logic. He also holds part-time professorships at Leningrad/St.Petersburg State University (since 2003) and previously at Polytechnical Institute (1980-1981). His research focuses on Diophantine equations, Computability theory, Algorithms, and Decidability problems. Full member, Russian Academy of Sciences (2008) Corresponding member, Bavarian Academy of Sciences (2007) Docteur Honoris Causa, Université Pierre et Marie Curie (2003) Humboldt Research Award (1997) Markov Prize, Academy of Sciences of the USSR (1980) His recent work involves computational approaches to Riemann's zeta function, probabilistic reformulations of graph theory problems, and algorithmic analysis of Diophantine representations. He has published extensively on connections between number theory and computational models, including studies on exponential Diophantine equations and their applications. Notable contributions include definitive solutions to Hilbert's Tenth Problem through Diophantine representations of recursively enumerable sets, and computational experiments supporting the Riemann Hypothesis. His publications span multiple languages and cover intersections between mathematical logic, number theory, and theoretical computer science.

Paul M.B. VitanyiView profile

Professor

• Kolmogorov complexity
• Computational machine learning
• Computational complexity
• +4 more

Paul M.B. Vitanyi is a CWI Fellow at the Centrum Wiskunde & Informatica (CWI) in the Netherlands and Professor of Computer Science at the University of Amsterdam's Faculty of Science. He has held the position of Professor since 1988, was appointed Hoogleraar 1 (highest professor rank) in 2005, and served as Adjunct Professor at the University of Waterloo from 2005. His academic career spans over four decades with continuous contributions to theoretical computer science. Education: Master of Science, Technical University of Delft, 1971 Ph.D. in Computer Science, Free University of Amsterdam, 1978 Vitanyi's research centers on Kolmogorov complexity , which he pioneered through applications and co-authored the seminal textbook 'An Introduction to Kolmogorov Complexity and its Applications' (Springer, 1993; 3rd ed. 2008) with Ming Li. His work extends across computational learning theory, distributed systems, information theory, and quantum computing, establishing foundational connections between computation and physics. His interdisciplinary approach has influenced multiple fields through approximately 200 publications. Major Honors: IFIP Silver Core Award (2007) Knighthood in the Order of the Netherlands Lion (2007) Kolmogorov Medal (2003) University of Helsinki Medal (2003) China's National 1st Prize for Excellent Books (1999) He has supervised 11 PhD students and maintains active editorial roles for journals including Information Processing Letters and Theory of Computing Systems. His academic service includes the Goedel Prize Committee (2005-2007) and initial membership on the ERC Information and Communication Panel. Vitanyi regularly delivers plenary lectures at major international conferences across Europe, Asia, and North America. As a core member of CWI's Algorithms and Complexity research group, he contributes to one of Europe's leading theoretical computer science teams, advancing fundamental research while mentoring the next generation of scholars through his teaching and supervision.

Anton ZeilingerView profile

Professor

• Quantum Information Science
• Quantum Computation
• Quantum Communication
• +7 more

Anton Zeilinger is a Full Professor of Experimental Physics at the University of Vienna and Scientific Director of the Institute for Quantum Optics and Quantum Information (IQOQI) at the Austrian Academy of Sciences. He served as President of the Austrian Academy of Sciences from 2013 to 2022. His work focuses on quantum foundations and applications, including quantum teleportation, entanglement, and quantum cryptography. Zeilinger holds honorary doctorates from Gdańsk and Humboldt Universities, and has received the Nobel Prize in Physics (2022), Wolf Prize (2010), and numerous other accolades. His research spans quantum optics, atom interferometry, and the philosophical implications of quantum mechanics. Education: PhD in Physics, University of Vienna (1971) Habilitation, Technical University of Vienna (1979) Research interests include testing quantum mechanics fundamentals, quantum nonlocality, and developing quantum technologies. His experiments on entangled photons and Bell inequality violations pioneered quantum information science. He has advised numerous researchers and holds leadership roles in global scientific institutions. Zeilinger’s labs are at the forefront of quantum communication and computing, with contributions to quantum teleportation and decoherence studies.

Sergiu HartView profile

Professor

• Game Theory
• Economic Theory
• Mathematical Economics
• +3 more

Sergiu Hart is the Alice Kusiel and Kurt Vorreuter University Professor of Economics and Mathematics at The Hebrew University of Jerusalem. He holds dual professorships and has held academic positions at Stanford University, Tel Aviv University, and Harvard University as a visiting scholar. Since 1991, he has been pivotal in establishing and leading the Center for the Study of Rationality, a multidisciplinary research center at Hebrew University. His academic career spans over four decades, with roles including Founding Director (1991–1998), Chair of the Academic Committee (since 2008), and President of the Game Theory Society (2008–2010). Education: Ph.D. in Mathematics from Tel Aviv University (1976). Research focuses on game theory, economic theory, and their intersections with computer science, probability, and statistics. Key contributions include strategic foundations of cooperation, repeated games, adaptive dynamics, and risk measurement frameworks. His work bridges theoretical insights with applications in fair distribution, economic competition, and bounded rationality. Notable awards include the Rothschild Prize (1998), election to the American Academy of Arts and Sciences (2016), and fellowships from the Econometric Society (1985) and Israel Academy of Sciences (2006). He has delivered prestigious lectures worldwide, such as the Walras-Bowley Lecture (2003) and the Harris Lecture (2009). His edited works include the three-volume Handbook of Game Theory with Robert J. Aumann. Leadership and grants: Secured an ERC Advanced Investigator Grant (2010–2015), chaired academic committees, and held executive roles in professional societies. His research lab, the Center for the Study of Rationality, fosters interdisciplinary collaboration across economics, mathematics, and computer science.

• Causal Inference
• Machine Learning
• Statistical Modeling
• +4 more

Dr. Lucas Kook is a Researcher at the Department of Statistics and Mathematics, WU Vienna University of Economics and Business. His research focuses on causal inference, machine learning, and statistical modeling, with applications in sports analytics, medical data analysis, and healthcare outcomes. He actively develops R packages such as deeptrafo for neural network-based statistical inference. His work bridges theoretical advancements in distributional regression and practical implementations in healthcare and sports domains. Key research areas include algorithm development for significance testing in supervised learning, causal feature selection, and nonparametric methods for conditional independence. Recent studies explore the efficacy of thrombolytic therapies in retinal artery occlusion and the predictive power of deep learning models in stroke patient outcomes. Collaborations span interdisciplinary fields, emphasizing reproducibility and methodological rigor in simulation studies.

Monika DörflerView profile

Professor

• Applied Harmonic Analysis
• Audio Signal Processing
• Machine Learning
• +3 more

Monika Dörfler is a Professor in the Department of Mathematics at the University of Vienna. Her research focuses on applied harmonic analysis, audio signal processing, and the mathematics of machine learning. She specializes in time-frequency analysis, nonstationary Gabor frames, and deep learning applications in audio processing. Dörfler has contributed significantly to methods like the invertible constant-Q transform and has explored the intersection of convolutional neural networks with signal representation theory. Affiliations: Department of Mathematics, University of Vienna Roles: Professor, Privatdozent, Principal Investigator (PI) in grants including WWTF Hertha Firnberg and SALSA projects Teaching: Courses such as Applied Analysis and Bachelor seminar Her research interests emphasize both theoretical foundations and practical applications of signal processing techniques. Notable contributions include work on Gabor frames in deep scattering networks and orthogonal projections for dimension reduction in learning problems. Dörfler has received awards for her papers, including Best Paper Awards at ISMIR19 and DAFx-11, and has organized international conferences like SAMPTA19 and DAFx2020. Awards: Best Paper Gold (DAFx-11), ISMIR19 Award, WWTF Grant Leadership Grants: Co-PI in aMOBY (Acoustic Monitoring of Biodiversity), PI in Audio-Miner and Hertha Firnberg grant Her work addresses challenges in audio denoising, music information retrieval, and algorithmic biases in recommendation systems. Ongoing projects include "Filter them all! Gabor theory for image quality assessment" submitted to FWF in 2023.

Hendrik TheineView profile

Researcher

• Media Economics
• Media Ownership
• Platform Economy
• +3 more

Hendrik Theine is a Researcher at the Department of Economics, Vienna University of Economics and Business (WU Wien), holding a Ph.D. and serving as Principal Investigator for multiple projects including WU IRF initiatives and the ACRP-funded Media Matters project. His research examines critical intersections of media structures, economic power, and societal challenges, with emphasis on media ownership dynamics and platform labor systems. His primary research domains include media economics (particularly Austrian media crises and ownership effects), platform economy (domestic work platforms and algorithmic labor), and climate-social policy. He investigates how media ownership shapes journalistic content, the political economy of wealth taxation narratives, and Big Tech's influence on news environments, employing empirical analysis and theoretical frameworks to address systemic inequities. Recent publications (2024-2025) reveal concentrated focus on Big Tech's media disruption, media ownership consequences, and platform labor exploitation. His work demonstrates methodological diversity through systematic reviews, theoretical contributions, and critical analyses of platform design, highlighting trends toward eroded journalistic independence and intensified platformization in labor markets. Scientific awards recognizing his contributions include: Auszeichung der WU Wien für besondere Forschungsleistungen (2018) Forschungsstipendium der WU Wien (2018) Kurt-Rothschild-Preis (2018) Leistungsstipendium WU Wien (2017) Theine leads significant internally funded projects like DNIE: Disturbing Narratives in Economics (2023-2024) exploring wealth distribution media narratives, and Media Matters analyzing ownership impacts. He collaborates with interdisciplinary teams including Gruszka, Pillinger, Gerold, and Friedrich across 12 projects, securing research grants focused on media economics and platform labor. His public engagement includes media contributions on climate policy and wealth inequality, bridging academic research with societal discourse.