Find Academic Supervisors

• Computer Science
• Combinatorial Optimization
• Operations Research
• +3 more

Mohammad Polash is a Lecturer at the School of Computer Science, The University of Sydney, since 2019. Previously, he served as an Associate Professor in the Department of Computer Science and Engineering at Jagannath University, Bangladesh. He holds a PhD from Griffith University, Australia, and degrees in Computer Science and Engineering from the University of Dhaka, Bangladesh. His academic roles include Executive Member of SIGCSE Australia Chapter, Fellow of the UK Higher Education Academy (FHEA), and Member of the Internet Society Bangladesh Chapter. He advises Jagannath University IT Society. Education: PhD in Computer Science, Griffith University (Australia), 2017 MSc in Computer Science and Engineering, University of Dhaka (Bangladesh) BSc in Computer Science and Engineering, University of Dhaka (Bangladesh) Research interests focus on Combinatorial Optimization, Operations Research, Evolutionary Computation, Data Mining, and Machine Learning. He develops algorithms for constraint-based problem-solving and explores applications in logistics, scheduling, and educational technology. His recent work emphasizes AI's impact on IT professions and computing education. Earlier research includes optimization in SAT solvers, aircraft sequencing, and Golomb rulers, reflecting a blend of theoretical and applied computer science. Scientific Awards: University of Sydney Faculty of Engineering Dean’s Commendation for Teaching (2024) University of Sydney Vice Chancellor's Award for Excellence in Teaching & Learning (2023) Dean’s Award for Excellence in Innovative Education (2022) Research Impact Award-2016 (Griffith University) Best Paper Runner-up at PRICAI 2018 IEEE Best Paper Award (2009) Advising and Grants: Supervises Zifan ZHENG on Sign Language Production via Deep Learning Recipient of IPRS and Publication Assistance Scholarships during PhD Mentored competition teams at Dhaka IT Fest-2018 and Sydney Coding Fest 2023

• Boolean Satisfiability (SAT) Solvers
• Formal Verification
• Distributed Protocols
• +7 more

Karem Sakallah is a Professor in the Department of Electrical Engineering and Computer Science at the University of Michigan, College of Engineering. His research focuses on formal verification, SAT solvers, and distributed protocols, with a strong emphasis on symmetry breaking and scalable verification techniques. He mentors Ph.D. students by fostering curiosity, collaborative problem-solving, and clear technical communication. Research highlights: Quantified symmetric minimization, SAT-based verification of distributed systems, symmetry detection in graphs, and automated inductive invariant inference. Teaching philosophy: Encourages students to view research as an adventure, prioritizes teaching them to identify gaps in literature, write effectively, and present solutions elegantly. Conference attendance: Supports participation in top-tier venues like FMCAD, SAT, CAV, and VMCAI, covering associated costs through research funding.

Moses CharikarView profile

Professor

• Algorithms
• Machine Learning
• Approximation Algorithms
• +4 more

Moses Charikar is the Donald E. Knuth Professor of Computer Science at Stanford University, with a courtesy appointment in Mathematics. He earned his B.Tech. from the Indian Institute of Technology Bombay (1995) and a Ph.D. from Stanford University (2000). His research focuses on high-dimensional data processing, machine learning optimization, approximation algorithms, and metric embeddings. Charikar has held faculty positions at Princeton University (2001–2015) and spent time at Google Research. Research interests include algorithmic techniques for massive data sets, convex optimization for non-convex problems, and low-distortion metric embeddings. His work has led to influential contributions like locality-sensitive hashing (LSH), earning the Paris Kanellakis Award (2012) and ACM Fellowship (2021). He has also received the Simons Investigator award (2014) and multiple best-paper accolades at top conferences. Awards: Donald E. Knuth Professorship (Stanford) 2012 Paris Kanellakis Theory and Practice Award ACM Fellow (2021) Simons Investigator in Theoretical Computer Science (2014) Charikar’s research bridges theoretical computer science and practical applications, with notable contributions to clustering, approximation algorithms, and data analysis. His publications span algorithm design, computational geometry, and machine learning theory.

Andreas VenerisView profile

Assistant Professor

• Digital Systems Verification
• Circuit Synthesis
• Boolean Satisfiability
• +3 more

Andreas Veneris serves as an Assistant Professor in the Department of Informatics at the School of Information Sciences and Technology, Athens University of Economics and Business (AUEB). His academic career is rooted in computer engineering and theoretical computer science, with a focus on digital systems and computational methods. Education: Diploma in Computer Engineering and Informatics (1991), University of Patras M.Sc. (1992), University of Southern California Ph.D. (1998), University of Illinois at Urbana-Champaign Research Focus: Dr. Veneris specializes in the verification and synthesis of digital systems and circuits, with particular expertise in Boolean satisfiability solvers. His work bridges theoretical computer science with practical engineering applications, focusing on developing efficient algorithms and data structures for complex computational problems in hardware design and verification. His research intersects with formal methods, computational logic, and electronic design automation, contributing to advancements in reliable hardware systems development. Professional Activities: Based in the Antoniadou Wing, 3rd floor at AUEB, Dr. Veneris contributes to both undergraduate and postgraduate education in computer science. His work connects with various research groups and laboratories within AUEB's Department of Informatics, which participates in numerous national and European research projects. The department maintains strong industry connections and has produced notable alumni working at leading technology companies worldwide.

Szemerédi EndreView profile

Professor

• Discrete mathematics
• Combinatorics
• Theoretical computer science
• +1 more

Endre Szemerédi is a Hungarian mathematician and computer scientist, currently serving as a Permanent Research Fellow at the Alfréd Rényi Institute of Mathematics (Hungarian Academy of Sciences) and holding the New Jersey Professor of Computer Science position at Rutgers University since 1986. His career spans prestigious institutions including Stanford, Caltech, and the Institute for Advanced Study. Expertise: Discrete mathematics, combinatorics, theoretical computer science, and number theory. Education: M.Sc. (1965, Eötvös Loránd University), Ph.D. (1970, Moscow State University under Israel Gelfand). Research legacy encompasses foundational contributions to combinatorics, graph theory, and computational complexity. His work on Hamiltonian cycles in random graphs , parallel sorting networks , and the Blow-up Lemma revolutionized extremal combinatorics and algorithm design. Scientific honors include: 2012 Abel Prize and Széchenyi Prize 2008 Rolf Schock Prize and Steele Prize 1982 Member of Hungarian Academy of Sciences , 2010 Member of US National Academy of Sciences 1975 Pólya Prize , 1973 Rényi Prize , multiple Grünwald Prizes .

Khushraj MadnaniView profile

Researcher

• Formal Logics and Models of Computation
• Specification and Verification of Timed Systems
• Scheduler Synthesis for Networked Control Cyber-Physical Systems
• +3 more

Khushraj Madnani is a postdoctoral researcher at the Max Planck Institute for Software Systems (MPI-SWS), Kaiserslautern, Germany, under Prof. Rupak Majumdar and Prof. Georg Zetzsche. His research focuses on formal logics, infinite-state models, and their applications in formal methods and verification. Previously, he was a postdoctoral researcher at Delft University of Technology (2020–2021) and a visiting fellow at the Tata Institute of Fundamental Research (2019–2020). He holds a PhD in Computer Science from the Indian Institute of Technology Bombay (2013–2019). Research Interests : Specification and Verification of Timed Systems Scheduler Synthesis for Networked Control Cyber-Physical Systems Formal Logics and Models of Computation Recent Contributions : His work spans decidability of timed logics, formal verification of real-time systems, and control theory. Key themes include metric temporal logic extensions, decidability boundaries, and applications in cyber-physical systems. Recent articles explore quantifier elimination in Presburger arithmetic and decidability of timed temporal logics with advanced quantifiers. Professional Roles : He collaborates with leading research institutes and has contributed to international conferences such as CONCUR, MFCS, and CDC. His work bridges theoretical foundations with practical verification challenges in real-time systems and networked control.

• Programming Languages
• Software Engineering
• Compiler Optimization
• +5 more

Qirun Zhang is an Assistant Professor in the School of Computer Science at the Georgia Institute of Technology . He holds the Catherine M. and James E. Allchin Early Career academic title. His research focuses on programming languages , software engineering , and compiler optimization , with an emphasis on program analysis , static analysis , and formal methods . He received his Ph.D. in Computer Science and Engineering from The Chinese University of Hong Kong (2013) and a Bachelor's from Zhejiang University (2009). Research Interests include techniques for improving software reliability/security via program analysis and compiler optimization. His work leverages computational complexity, analytic combinatorics, graph theory, and formal languages. Notable contributions involve debug information validation , context-free language reachability , and compiler testing frameworks like Skeletal Program Enumeration (SPE) . Recent Work spans scalable cryptographic accelerator design, LLVM-based debug validation, and SMT solving optimizations. His papers often address algorithmic improvements for reachability problems and compiler correctness. Awards include the PLDI Distinguished Paper Award (2020) and Facebook Fellowship (2021). He serves on program committees for top venues like POPL, SAS, and PLDI, and chairs artifact evaluation committees (PLDI'25). Teaching includes courses on compilers (CS 4240), software analysis (CS 6340), and advanced program analysis (CS 8803). He mentors a research group with current Ph.D. students and MS/undergraduate researchers. Lab/Team focuses on rigorous compiler validation and program analysis tools. Open positions are available for Fall 2025.

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +4 more

Yin Chen is a Professor in the Department of Computer Science at South China Normal University, Guangdong, China. With an extensive publication record spanning over 25 years from 2000 to 2025, Professor Chen has established themselves as a leading researcher in multiple domains of computer science and artificial intelligence. Professor Chen's research spans artificial intelligence, machine learning, computer vision, natural language processing, and deep learning. Their work demonstrates exceptional breadth across theoretical and applied domains, with significant contributions to facial expression recognition, transformer-based language models, 3D human modeling, and optimization algorithms. Recent research shows particular strength in multimodal learning, with numerous publications integrating visual, textual, and audio information for advanced AI applications. The publication trends reveal a consistent output of high-impact research, with a notable acceleration in recent years. Professor Chen's work appears in top-tier venues including IEEE Transactions, ACM Multimedia, and various specialized journals. Their research demonstrates strong interdisciplinary connections, bridging computer science with applications in engineering, bioinformatics, and mathematics. Professor Chen collaborates extensively with researchers across institutions, particularly with Jia Li, Meng Wang, Richang Hong, and Xianghua Fu. These collaborations span multiple projects in affective computing, multimodal translation, and algorithm development. The research group appears to be active in both theoretical advancements and practical implementations of AI systems.

Christoph BerkholzView profile

Professor

• Theoretical Computer Science
• Algorithm Design
• Computational Complexity
• +3 more

Prof. Christoph Berkholz is a University Professor and head of the Algorithms Group at the Institute for Theoretical Computer Science within the Department of Computer Science and Automation at Humboldt-Universität zu Berlin since August 2022. He holds a PhD from RWTH Aachen University (2014) and completed postdoctoral research in Stockholm, Berlin, and Berkeley. Prior to his current role, he served as a Junior Professor of Logic and Complexity at Humboldt-Universität, leading the DFG-funded Emmy Noether Junior Research Group on Representation Complexity of Enumeration and Counting Algorithms. His research focuses on theoretical computer science, particularly algorithmic methods and their fundamental limits. Core questions driving his work include conditions for efficient algorithms, structural differences between 'light' and 'heavy' input instances, and the capabilities/limitations of algorithmic strategies. Research applications span query optimization in databases, SAT solving, and constraint solving. He has published ~30 papers and actively participates in program committees for AI, theoretical computer science, and database systems conferences. Prof. Berkholz's group investigates methods ranging from classical decision problems (e.g., propositional logic satisfiability) to dynamic algorithms supporting efficient updates. Key application areas include probabilistic databases and SAT/constraint-solving data structures. No specific awards are listed, though his Emmy Noether Research Group indicates significant grant recognition.

• Operations Research
• Decision Support Systems
• Optimization Algorithms
• +5 more

Daniele Pretolani is an Associate Professor at the Department of Engineering Sciences and Methods, University of Modena and Reggio Emilia. He specializes in Operations Research (MATH-06/A) with a focus on decision support systems, multi-objective optimization, and directed hypergraph algorithms. Teaches Methods and Algorithms for Optimization in Digital and Creative Industry (Management Engineering) Teaches Models and Methods for Decision Support (Management Engineering) His research explores: Stochastic time-dependent network routing Multi-criteria decision analysis for supplier selection Hypergraph reductions for satisfiability problems Visual decision support tools for composite indexes Recent work includes developing a decision support system for global service providers (2024) that improved supplier selection by 25% over company practices, and foundational contributions to the SDEWES sustainability index (2018-2020). No specific awards or student advising details were mentioned in the provided texts.

Antonin KuceraView profile

Professor

• Stochastic Processes
• Probabilistic Systems
• Markov Decision Processes
• +8 more

Antonin Kucera is a Professor at the Faculty of Informatics , Masaryk University, Czech Republic. His work focuses on stochastic processes, probabilistic systems, Markov decision processes, stochastic games, infinite-state systems, and applications of game theory in security and operational research. He has led multiple research projects funded by institutions like the US Army Research Office and the Czech Science Foundation. Research Interests : Stochastic processes, probabilistic verification, infinite-state systems, multi-objective optimization, game theory, and security applications. Projects : Leading studies on adversarial security patrolling, probabilistic systems analysis, and game-theoretic verification. Past projects include European Network for Game Theory (COST) and Institute for Theoretical Computer Science. Advising : Mentored 13 PhD/Master's students, including Tomáš Brázdil, Petr Novotný, and Jan Křetínský. Teaching : Courses on Petri Nets, Semantics of Programming Languages, and Mathematical Logic.

• Automated Reasoning
• Knowledge Representation and Reasoning
• Computational Logic
• +5 more

Uwe Egly is an Associate Professor at the Department of Knowledge-Based Systems, Faculty of Informatics, Technische Universität Wien (TU Wien). His research focuses on automated reasoning, proof theory, knowledge representation, and computational logic, with a strong emphasis on quantified Boolean formulas (QBFs), argumentation frameworks, and applications of AI in engineering. He leads projects funded by the Austrian Science Fund (FWF) and the Vienna Science and Technology Fund (WWTF), including the Boolean project (2011–2019) and FAME (2011–2014). Egly is known for developing QBF solvers like DepQBF and contributing to SAT-solving techniques. He teaches courses such as Abstract Argumentation , Formal Methods in Computer Science , and Quantum Computing . His research interests span proof complexity, satisfiability checking, and AI-driven algorithms for path planning. He has advised numerous students on theses involving quantum algorithms, QBF solver optimizations, and argumentation frameworks. Egly’s work bridges theoretical computer science with practical applications, including contributions to deformation monitoring systems and circuit synthesis using SAT-based methods. He is involved in international workshops and conferences, such as SAT, FMCAD, and Dagstuhl Seminars, and has edited proceedings for events like SAT 2014 . His collaborations include projects on scenario-based testing of UML diagrams and semantics-aware model versioning. Egly’s interdisciplinary approach integrates logic, artificial intelligence, and computational methods to solve complex theoretical and applied problems.

Stefan SzeiderView profile

Professor

• Algorithms
• Computational Complexity
• Theoretical Computer Science
• +4 more

Stefan Szeider is a full professor and chair of the Algorithms and Complexity Group at the Faculty of Informatics, Technische Universität Wien (TU Wien). He also serves as a visiting scientist at UC Berkeley's Simons Institute for the Theory of Computing. His academic journey includes positions at the University of Durham (UK) and the University of Toronto (Canada), and he earned his Mathematics PhD from the University of Vienna in 2001. Dr. Szeider's research focuses on designing efficient algorithms for problems in Artificial Intelligence, automated reasoning, and combinatorial optimization. He leads several initiatives, including the Vienna Center for Logic and Algorithms (VCLA), and has secured funding from the ERC, EPSRC, FWF, and others. His Erdős number is 2, reflecting his collaborative network in mathematics and computer science. Key achievements include the first ERC Starting Grant awarded to an Austrian computer scientist (2009), and awards such as the Highlighted Paper Award at SAT 2023 and Best Paper at CP 2020. He advises numerous PhD students and postdocs, fostering the next generation of researchers in algorithms and complexity. Notable contributions extend beyond academia to public outreach, including initiatives like the 'Algorithms Think Differently' educational program and the 'Algorithms in 60 Seconds' video competition. His work bridges theoretical foundations and practical applications, influencing both academic and real-world computational challenges.

• Satisfiability (SAT)
• Graph Theory
• Combinatorial Optimization
• +3 more

Markus Kirchweger is a PreDoc Researcher at the Department of Algorithms and Complexity, Faculty of Informatics, Technische Universität Wien. His work spans Satisfiability (SAT) solving, graph theory, and combinatorial optimization, with a focus on symmetry breaking and SAT modulo theories. Research Interests: Developing SAT-based frameworks for graph generation and enumeration Dynamic symmetry breaking in combinatorial problem encodings Integrating user propagators into CDCL solvers Applying SAT techniques to conjectures like Erdős-Faber-Lovász and Rota’s Basis Co-certificate learning and shortest common supersequence optimization Projects: INCR (2021–2024), REVEAL-AI (2020–2024), SLIM (2019–2024), ASK-SAT (2024–2027).

Ciaran McCreeshView profile

Research Fellow

• Graph Theory
• Combinatorial Optimization
• Constraint Programming
• +5 more

Ciaran McCreesh is a Research Fellow in the School of Computing Science at the University of Glasgow. His research focuses on solving hard combinatorial problems in practice, particularly in graph theory and subgraph finding, leveraging symbolic AI techniques like constraint programming and Boolean satisfiability. He explores closing the gap between theoretical worst-case complexity and practical performance through empirical algorithmics and computational experiments. His work also addresses algorithm reliability via proof logging, parallel hardware exploitation (bit-parallelism, multi-core computing), and algorithm engineering to improve solver accessibility. Research interests: Combinatorial optimization, constraint programming, proof logging, parallel computing, algorithm reliability. Developed the Glasgow Subgraph Solver, a constraint programming-based tool for hard subgraph isomorphism problems. Publications span graph computation models, certified solvers, and algorithmic advancements. His work emphasizes practical algorithmic improvements with rigorous validation methods. Supervised students include Matthew McIlree and José Antonio Rodríguez Bacallado.