Find Academic Supervisors

Find and connect with academic supervisors, professors, and scholars for your research journey.

Showing 121-135 of 138 supervisors

Profile data may be stale. It is sourced from public faculty pages.

Franz WotawaView profile

Associate Professor

Vienna University of TechnologyAustria

Franz Wotawa is an Associate Professor at the Institute of Information Systems Engineering, Faculty of Informatics, TU Wien. His primary research areas include model-based and qualitative reasoning, software engineering, configuration, verification and validation, intelligent agents, and theorem proving. He is affiliated with the Databases and Artificial Intelligence research group (E192-02) and can be contacted at franz.wotawa@tuwien.ac.at. Wotawa's research spans model-based reasoning for diagnosis and testing in service-oriented architectures, software verification techniques, and intelligent agent applications. His work bridges theoretical theorem proving with practical SOA validation challenges, emphasizing configuration management and qualitative analysis methods within distributed systems. His 2013 publications reveal a strong focus on risk-aware SOA testing methodologies, integrating criticality metrics with business impact analysis to optimize testing frameworks. These works demonstrate consistent exploration of grey-box testing approaches and reliability assessment in complex service compositions. Wotawa has supervised the following Master's theses: Hybrid approach for model-based random testing (J. P. Wallner, 2010) Model transformation from UML state machines to input/output symbolic transition systems (C. Thurnher, 2008) Entwurf und Implementierung eines wertebasierten Diagnose-Modells für VHDL-Programme (F. Bruckner, 2003) Constraint satisfaction problems: hybrid decomposition and evaluation (M. Hutle, 2002) Framework für generische Suche in einem komplexen Objektmodell am Beispiel von See Your Client (B. Schmidt, 2002) System analysis and monitoring (H.-P. Petek, 2001) He has led significant research projects: D-Flat (2013-2017): Dynamic programming via tree decompositions START (2014-2022): Argumentation semantics analysis Audit 4 SOAs (2011-2014): Criticality-based SOA testing INDENICA (2010-2013): SOA testing frameworks

Official University Profile

Marek M. KarpinskiView profile

Professor

Graz University of TechnologyAustria

Marek M. Karpinski is a Chair Professor of Computer Science at the University of Bonn and a founding member of the Hausdorff Center for Mathematics . He has held visiting or professorial positions at institutions such as Princeton University, Carnegie-Mellon University, and the University of Edinburgh. His affiliations also include the B-IT Research School on Applied Informatics and the Lab for Foundations of Computing . His research spans efficient algorithms , combinatorial optimization , computational complexity , randomized approximation techniques , and applications in network design , quantum computation , and molecular biology . Recent work focuses on approximation hardness for NP-hard problems, graph algorithms , and algebraic computational complexity . His scientific contributions include polynomial time approximation schemes for dense NP-hard problems and key publications in randomized algorithms , VC dimension , and network optimization . He has advised numerous researchers and received honors such as the Humboldt Research Award and the Max Planck Research Prize .

Official University Profile

Seema JehanView profile

Lecturer

University of YorkUnited Kingdom

Dr. Seema Jehan is a Lecturer in the Department of Computer Science at the University of York, UK (2023–present). She holds a PhD in Computer Science from Graz University of Technology, Austria. Previously, she served as Assistant Professor at SEECS-NUST, Islamabad (2018–2022) and Software Team Lead at Zaheen Systems (2022–2023). Her research focuses on Mutation Testing, Constraint Satisfaction Problems, and Deep Learning applications in education and software systems. Education: PhD in Computer Science from Graz University of Technology; prior roles include academic and industry positions in Pakistan. Research interests emphasize improving software testing methodologies and applying machine learning to education. Her publications span topics like BPEL integration testing, SOA validation, and educational technology innovations in Pakistan. She contributes to both theoretical advancements (e.g., mutation coverage analysis) and practical applications (e.g., test suite optimization). No awards or grants are explicitly listed. She currently advises no formally listed students but may engage in teaching-related mentorship.

Official University Profile

Yong GaoView profile

Professor

University of British ColumbiaCanada

Yong Gao is a Professor of Computer Science, Data Science, and Mathematics at the University of British Columbia (UBC) Okanagan, affiliated with the Irving K. Barber Faculty of Science. He holds a PhD from the University of Alberta and leads research in algorithmic and computational problems in artificial intelligence, network science, and computational biology. His work emphasizes graph theory, probabilistic methods, and applications in social media and biological systems. Educational Background : PhD in Computer Science, University of Alberta Research Interests : Algorithmic foundations of AI and network science Graph-based methods for computational biology and social media analysis Probabilistic modeling of complex systems Awards & Grants : Recipient of multiple NSERC Discovery Grants (2006–2019) UBC Okanagan Startup Grant (2005–2008) Senior Member, Association for the Advancement of AI (AAAI) Professional Roles : Member, Centre for Optimization, Convex Analysis and Nonsmooth Analysis Graduate student supervisor Teaching : Courses in algorithm design, artificial intelligence, discrete mathematics, and network science.

Official University Profile

Aleksa StankovićView profile

Associate Professor

University of ZenicaBosnia & Herzegovina

V. Prof. Dr. sc. Aleksa Stanković is an Associate Professor at the Faculty of Sports and Physical Education, University of Zenica. His academic journey includes a Master of Science in Physical Education from the Faculty of Physical Education, Sarajevo, and a Doctorate in Sports and Physical Education. He specializes in teaching Physical Education I and maintains an active research profile. Research interests span both sports science and theoretical computer science. In sports science, he focuses on motor abilities, morphological characteristics, and athletic performance in youth sports (e.g., basketball and football). His computer science work addresses algorithmic challenges in constraint satisfaction problems, approximation algorithms, and combinatorial optimization. Recent publications (2023–2025) highlight advancements in algorithm design and sports biomechanics. His work often bridges theoretical and applied domains, with studies analyzing training effects on motor skills and exploring computational complexity in discrete optimization problems. Consultations are managed via email or electronic communication, adhering to scheduled teaching hours. No scientific awards are explicitly mentioned in the provided texts. His professional role emphasizes teaching and research, with no noted affiliations to specific labs or teams beyond departmental responsibilities.

Official University Profile

Tom KellyView profile

Assistant Professor

Georgia Institute of TechnologyUnited States

Tom Kelly is an Assistant Professor at the School of Mathematics, Georgia Institute of Technology, specializing in Combinatorics and Graph Theory. His research intersects with Theoretical Computer Science, particularly in algorithms and randomness. He co-organizes the Atlanta Combinatorics Colloquium and the Georgia Tech Combinatorics Seminar . His current PhD students include Sarah Frederickson , Xuanang Li , and Tantan Dai , and he is funded by NSF Grant DMS-2247078. Dr. Kelly's research focuses on graph decompositions, hypergraph coloring, and probabilistic combinatorics. He has made significant contributions to problems like the Erdős-Faber-Lovász conjecture and threshold phenomena in Latin squares. His work often employs advanced techniques such as absorption methods and nibble algorithms. His recent publications explore entropy bounds, Steiner systems, and Hamilton transversals, reflecting his interest in extremal combinatorics and random structures. He teaches graduate and undergraduate courses in combinatorics and graph theory, including Math 3012 (Applied Combinatorics) and Math 7016 (Combinatorics) . He also led research initiatives like the Georgia Tech Summer 2023 REU project on Latin squares.

Official University Profile

Tselil SchrammView profile

Assistant Professor

University of California, San DiegoUnited States

Tselil Schramm is an Assistant Professor in the Department of Statistics at Stanford University, with courtesy appointments in Computer Science and Mathematics. She is actively engaged in research and teaching in theoretical computer science and statistics. Department: Department of Statistics School: School of Humanities and Sciences University: Stanford University Office: CoDa E254 Email: tselil@stanford.edu She earned her PhD from UC Berkeley under Prasad Raghavendra and Satish Rao, followed by postdoctoral work at Harvard and MIT with Boaz Barak, Jon Kelner, Ankur Moitra, and Pablo Parrilo. Her research lies at the intersection of theoretical computer science and statistics, focusing on high-dimensional estimation, information-computation tradeoffs, sum-of-squares algorithms, and random graph theory. She develops algorithms for statistical problems and investigates the boundaries between what is statistically possible and what is computationally feasible. Her recent publications span topics including the overlap-gap property, discrepancy algorithms, robust message passing, semidefinite programming, spectral clustering, and random geometric graphs, appearing in top venues such as STOC, FOCS, COLT, NeurIPS, and The Annals of Statistics. She teaches a range of courses, including Introduction to Statistics (STATS 60), Theory of Statistics II (STATS 300B), and Machine Learning Theory (STATS 214 / CS 228M), reflecting her expertise in both foundational and advanced statistical theory. Runner-up for Best Paper at COLT 2021 Invited to STOC 2022 special issue of SICOMP Invited to SODA 2016 special issue of ACM Transactions on Algorithms Invited to CCC 2019 special issue of Theory of Computing Tselil Schramm advises and collaborates with numerous students and researchers, including Shuangping Li, Misha Ivkov, and Siqi Liu. She has been involved in multiple research grants and projects, particularly in the areas of high-dimensional inference and algorithmic robustness. Her work often bridges theoretical guarantees with practical algorithmic design. She is affiliated with Stanford’s theoretical computer science and statistics research groups, contributing to a vibrant academic environment. Her future work is expected to further explore the limits of efficient computation in statistical settings, with potential applications in machine learning, signal processing, and network analysis.

Official University Profile

Anuj DawarView profile

Professor

University of CambridgeUnited Kingdom

Professor Anuj Dawar is a leading academic in Theoretical Computer Science at the University of Cambridge's Department of Computer Science and Technology. He holds a PhD from the University of Pennsylvania (1993) and has been a faculty member since 1999. His research focuses on computational complexity via logic, descriptive complexity, and finite model theory, with applications to databases, verification, and games. Education: PhD in Computer Science, University of Pennsylvania (1993) Masters, University of Delaware Bachelor's, Indian Institute of Technology (Delhi) Research Interests: His work bridges logic and computation, investigating limits of symmetric algorithms and complexity through formal languages. Notable themes include: Descriptive complexity and homomorphism preservation Finite model theory and its applications Algorithmic model theory and constraint satisfaction Professional Activities: Editor-in-Chief, ACM Transactions on Computational Logic Former president of European Association for Computer Science Logic Committee roles for Gödel Prize, Church Award, and Nerode Award Advising & Teaching: Supervised over 15 PhD students and taught advanced courses like Quantum Computing, Complexity Theory, and Foundations of Functional Programming. Currently on sabbatical (2024–25).

Official University Profile

Pravesh KothariView profile

Adjunct Professor

Carnegie Mellon UniversityQatar

Pravesh Kothari serves as an Adjunct Professor in the Computer Science Department at Carnegie Mellon University, focusing on theoretical computer science and algorithmic foundations of average-case computational problems. His research centers on designing efficient algorithms and establishing rigorous evidence for algorithmic thresholds in problems spanning theoretical computer science, statistics, and allied fields. Key contributions include the development of the sum-of-squares method which bridges proof complexity and semidefinite programming relaxations for optimization challenges, detailed in his monograph Semialgebraic Proofs and Efficient Algorithm Design with Pitassi and Fleming. Recent publications reveal consistent focus on constraint satisfaction problems, small-set expansion, and sparse statistical estimation, demonstrating strong integration of theoretical computer science with statistical learning theory through semidefinite programming frameworks. Major recognitions include: NSF CAREER Award (2021-2026) for The Nature of Average-Case Computation Sloan Fellowship (2022) Current research is primarily supported by the NSF CAREER Award, enabling investigation into computational thresholds and efficient algorithm design for average-case problems through theoretical frameworks. His Fall 2021 CMU lecture notes document practical applications of these methodologies.

Official University Profile

Conrado Martinez ParraView profile

Professor

Polytechnic University of CataloniaSpain

Conrado Martinez Parra is a Professor in the Department of Computer Science at the Faculty of Computer Science, Universitat Politècnica de Catalunya (UPC). He is a core member of the ALBCOM research group, which focuses on Algorithmics, Bioinformatics, Complexity, and Formal Methods. Affiliation : Department of Computer Science, Faculty of Computer Science (FIB), UPC Research Group : ALBCOM - Algorísmia, Bioinformàtica, Complexitat i Mètodes Formals Email : conrado@cs.upc.edu ORCID : 0000-0003-1302-9067 Researcher ID : G-4629-2015 His research spans theoretical computer science with a strong emphasis on the design and analysis of algorithms and data structures. His work includes average-case analysis of algorithms, combinatorial generation, probabilistic methods in algorithmics, and applications in information retrieval and data stream processing. He has extensively studied multidimensional data structures such as quadtrees, K-d trees, and skip lists, analyzing their performance under various query models including partial match and orthogonal range searches. His recent publications reveal a sustained focus on algorithmic efficiency, sampling techniques, and probabilistic modeling in data structures. Trends indicate a deep engagement with randomized algorithms, unbiased estimation, and cache-efficient selection methods, reflecting both theoretical rigor and practical applicability in modern computing environments. Scientific Contributions Extensive publication record spanning over three decades, from 1989 to 2024. Active in major algorithmic conferences such as ANALCO, AofA, and AAAI. Contributions to foundational algorithm analysis including Hoare’s FIND, Quickselect variants, and deletion in binary search trees. Collaborative research with prominent figures in theoretical computer science across Europe. Professor Martinez Parra has advised or collaborated with several doctoral students, including Gustavo Lau, whose thesis on partial match queries he supervised. He has participated in numerous competitive R&D projects funded by national and regional programs, focusing on large-scale information processing and graph-based computing models. His work is supported by long-standing grants from Spanish and Catalan research councils. He is affiliated with the ALBCOM research group, a leading team in algorithmic research at UPC, contributing to both theoretical advances and practical implementations in combinatorics and data structure optimization.

Official University Profile

Michel GoemansView profile

Professor

University of California, BerkeleyUnited States

Michel Goemans is the RSA Professor and Head of the Department of Mathematics at the Massachusetts Institute of Technology (MIT), with additional affiliations at MIT CSAIL and MIT ORC. Previously, he held the Leighton Family Professorship (2007-2017) and adjunct/visiting positions at the University of Waterloo, University of Louvain, and RIMS Kyoto. His research focuses on combinatorial optimization , discrete algorithms , and approximation methods , with applications spanning network design, stochastic optimization, and algorithmic game theory. His publications consistently explore fundamental problems in mathematical programming and theoretical computer science. Notable awards include: Leroy P. Steele Prize (2022) George B. Dantzig Prize (2021) Farkas Prize (2012) Fellowships: AMS, ACM, SIAM, Guggenheim, Sloan Foundation Doctor Honoris Causa (Université catholique de Louvain) He advises doctoral candidates and postdocs, with prominent former students including David Williamson (Cornell), Jon Kleinberg (Cornell), and Aleksander Madry (MIT). Research is primarily funded by NSF and ONR grants.

Official University Profile

François PirotView profile

Associate Professor

University of Novi SadSerbia

François Pirot is an Associate Professor (Maître de Conférences) at Université Paris-Saclay since September 1, 2021. He conducts research at the LISN laboratory within the GALaC team and teaches at the Faculty of Science of Orsay. PhD in Mathematics (Radboud University) and Computer Sciences (Université de Lorraine), 2019 Postdoctoral experience: ULB (2019), G-SCOP (2019-2020), Inria Sophia Antipolis (2020-2021) His research focuses on graph coloring problems in diverse contexts such as graph powers, locally sparse graphs, and distributed algorithms, utilizing probabilistic methods and connections to bio-informatics through circular codes. He has advanced bounds for h -conflict-free coloring, acyclic coloring, and dichromatic numbers in oriented graphs, with applications to minor-closed families and geometric group theory. Scientific contributions include: Asymptotically tight bounds for chromatic numbers in sparse graphs Efficient fractional coloring algorithms for K_t-minor-free graphs Structural analysis of comma-free and mixed circular codes in genetic alphabets Charles Delorme Prize for outstanding thesis in Graph Theory (2019) Collaborations span institutions like ULB, G-SCOP, Inria, and cross-disciplinary fields from computer science to mathematical biology.

Official University Profile

Nutan LimayeView profile

Professor

IT University of CopenhagenDenmark

Nutan Limaye is a Professor at the Department of Theoretical Computer Science , IT University of Copenhagen , specializing in Algorithms , Computational Complexity , and Algebraic Circuits . She actively contributes to research on polynomial complexity, quantum computation, and lower bound techniques. Key Research Areas : Algebraic Circuit Complexity, Polynomial Computation, Graph Isomorphism, Boolean Satisfiability Current Projects : FLows : Formula complexity and lower bounds (2024-2026) DIREC: OnlineAlgo : Digital research initiatives (2022-2025) BARC2 : Basic Algorithms Research Copenhagen (2024-2029) Scientific Recognition includes the FOCS Best Paper Award (2022) . Her work frequently appears in top conferences like CCC , FSTTCS , and SIGACT News , with recent collaborations in Denmark and international institutions. She contributes to public understanding through media appearances on topics like basic computer science research and BARC's initiatives .

Official University Profile

Binyamin ApplebaumView profile

Professor

Leipzig UniversityGermany

Prof. Binyamin Applebaum is a Professor in the School of Electrical Engineering at Tel Aviv University, within the Iby and Aladar Fleischman Faculty of Engineering. He is a core member of the COmputer and Network SEcurity Lab and the Check Point Institute of Information Security, and actively co-organizes the Greater Tel-Aviv Cryptography seminar (GTACS) and Tel Aviv University's Crypto Seminar. His research centers on cryptographic foundations and practical computer security systems, with significant contributions to computational complexity theory, coding theory applications, and random constraint satisfaction problem analysis. He has advanced the field through his monograph "Cryptography in Constant Parallel Time" and extensive service on program committees for premier conferences including CRYPTO, STOC, and TCC. Prof. Applebaum serves on the editorial board of SIAM Journal on Computing (SICOMP) and chairs the steering committee for the Conference on Information-Theoretic Cryptography (ITC). He currently seeks postdoctoral researchers with strong publication records in cryptography, theoretical computer science, or coding theory, reflecting active research funding and mentorship commitments.

Official University Profile

Horia PopaView profile

Lecturer

West University of TimisoaraRomania

Horia Popa is a Lecturer at the Faculty of Computer Science , West University of Timișoara. He has taught courses such as Artificial Intelligence , Network Administration , and Functional and Logic Programming since the 2022-2023 academic year, with additional historical courses dating back to 2011-2012. His teaching emphasizes hands-on lab work, software tools (Jess, CLIPS, WEKA), and project-based learning. Education: Not explicitly mentioned in the text. Research: Focuses on multi-agent systems, distributed constraints, asynchronous search algorithms, and system administration. Research Interests: Horia Popa specializes in Artificial Intelligence and Multi-agent Systems , particularly in asynchronous search techniques and constraint satisfaction problems. His work explores scale-free networks, nogood processors, and distributed execution environments. He also investigates Network Administration (DHCP, firewall configuration, kernel recompilation) and Knowledge Discovery through agent-based modeling. Article Trends: His publications (2001-2015) span Computer Science , Artificial Intelligence , and Multi-agent Systems . Key subfields include Asynchronous Algorithms , Constraint Networks , Protein Folding Simulation , and Kernel-Level System Management . He frequently uses NetLogo for large-scale simulations and integrates Samba/ldap for networked environments. Teaching and Projects: Students in his courses work on projects involving Jess , Prolog , and JADE . Assignments include implementing search algorithms (A*, Hill Climbing, RBFS), configuring NIS and Samba servers, and analyzing system monitoring tools like sar and top . He emphasizes practical implementation and cross-language diversity (e.g., Racket, Prolog).

Official University Profile