Find Academic Supervisors

Nate FosterView profile

Professor

• Programming Languages
• Networking
• Databases
• +5 more

Nate Foster is a Professor of Computer Science at Cornell University and currently serves as the Associate Dean for Research in the Ann S. Bowers College of Computing and Information Science. He is also a Visiting Researcher at Jane Street and served as a Visiting Professor at École Polytechnique Fédérale de Lausanne during the 2023-24 academic year. His research uses ideas from programming languages to solve problems in networking, databases, and security. BA in Computer Science, Williams College (2001) MPhil in History and Philosophy of Science, University of Cambridge (2008, all work completed in 2003) PhD in Computer and Information Science, University of Pennsylvania (2009) Foster's research focuses on developing languages and tools that make it easy for programmers to build secure and reliable systems. His current work centers on the design and implementation of languages and tools for programmable networks, particularly using the P4 language. His past work includes bidirectional languages (also known as 'lenses'), database query languages, data provenance, type systems, mechanized proof, and formal semantics. His research group at Cornell has made significant contributions to network verification, software-defined networking, and formal foundations for programmable data planes. Analysis of Foster's recent publications reveals a strong focus on network verification and programming language foundations for networking. His work consistently applies formal methods to practical networking problems, with a particular emphasis on the NetKAT and P4 languages. Over the past five years, his research has evolved toward more complex network verification techniques, including infinite state verification, active learning of network models, and dependently-typed approaches to network programming. His work bridges theoretical computer science with practical networking systems, making formal methods accessible to network engineers. ACM Fellow (2025) ACM SIGPLAN Robin Milner Award (2023) ACM SIGCOMM Rising Star Award (2018) NSF CAREER Award (2013) Alfred P. Sloan Fellowship (2012) Multiple distinguished paper awards across top conferences including POPL, PLDI, and SIGCOMM Foster has advised numerous PhD and Master's students who have gone on to prominent positions in both industry and academia, with many continuing work in programming languages and networking. He has led multiple significant research grants including an NSF CAREER Award and has been involved in the P4 Language Consortium, serving as Chair of the P4 Language Governing Board. His work has been supported by various organizations including NSF, DARPA, and industry partners like Intel and Jane Street. Foster is also active in the programming languages research community, serving on numerous program committees and as Vice Chair of DARPA's Information Science and Technology (ISAT) study group. Foster leads a vibrant research group at Cornell focused on programming languages for networks, with collaborators from academia and industry. His group has developed several influential tools and frameworks including NetKAT, Petr4, and KATch. They maintain strong connections with the P4 community and work closely with industry partners to ensure their research has practical impact on real-world networking systems.

Yao QinView profile

Assistant Professor

• Machine Learning
• Adversarial Robustness
• Out-of-Distribution Generalization
• +5 more

Yao Qin is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of California, Santa Barbara (UCSB), with dual affiliation in the Department of Computer Science. She concurrently serves as Co-Director of the REAL AI Initiative at UCSB and holds a Senior Research Scientist position at Google DeepMind, where she contributes to the Gemini Multimodal project. Her academic credentials include a PhD in Computer Science and Engineering from the University of California, San Diego (advised by Prof. Garrison W. Cottrell) and a BS in Electrical Engineering from Dalian University of Technology. During her doctoral studies, she completed internships with pioneering researchers Geoffrey Hinton and Ian Goodfellow. Dr. Qin's research program centers on machine learning robustness, with emphasis on adversarial robustness, out-of-distribution generalization, and fairness. She develops reliable AI systems specifically for healthcare applications, with diabetes management as a primary focus. Her lab explores critical themes including AI safety in multimodal models and diabetes-specific AI solutions, particularly exercise metabolism modeling and glycemic effect prediction. Recent publications reveal a strong trajectory in robust machine learning with cross-domain applications. Her work consistently bridges theoretical robustness concepts with practical healthcare implementations, particularly in diabetes care. Key publication venues include CVPR, ICML, NeurIPS, and ICLR, with notable contributions to out-of-distribution detection, adversarial transfer learning, and multimodal AI safety. Her distinguished recognition includes: EECS Rising Star at MIT (2021) UCSB Regents' Junior Faculty Fellowship Award Helmsley Charitable Trust award for Type 1 diabetes research UCSB Faculty Research Grant American Diabetes Association Abstract Award (ADA-2025) Dr. Qin actively mentors four PhD students—Mehak Dhaliwal, Andong Hua, Kenan Tang, and Youngseok Yoon—on projects spanning LLMs for diabetes, multimodal robustness, and generative time-series modeling. Her research is funded by the Helmsley Charitable Trust and UCSB, with recent grants supporting exercise-specific AID algorithms for diabetes management. As Co-Director of the REAL AI Initiative, she leads a research ecosystem focused on developing reliable artificial intelligence. Current lab activities include organizing workshops at NeurIPS-2024 (AdvML-Frontiers and AIM-FM) and developing next-generation diabetes management tools through collaborations with medical institutions.

Wojciech RytterView profile

Professor

• Design and analysis of computer algorithms
• Automata and formal languages
• Parallel algorithms
• +5 more

Wojciech Rytter is a full professor at the Institute of Informatics, Department of Mathematics and Informatics at the University of Warsaw, Poland, holding this position continuously since October 1971. His academic career includes significant international appointments as full professor at New Jersey Institute of Technology (2002-2004), Liverpool University (1997-2002), and Bonn University (1994-1995), and as visiting professor at University of California, Riverside (1992-1993) and University of Warwick (1985-1986). He earned his MSc in 1971, PhD in 1975, habilitation in 1985, and was awarded the scientific degree of professor in 1997, all from Warsaw University. Professor Rytter's research focuses on the design and analysis of computer algorithms, with particular expertise in automata and formal languages, parallel algorithms, and text algorithms. His work spans efficient sequential and parallel algorithms, automata theory, complexity of recognition and parsing of context-free languages, pattern matching, algorithmics of WWW, parallel combinatorial computing, graph-theoretic algorithms, and algorithmics of highly compressible objects. His theoretical contributions have practical applications in computational biology, bioinformatics, and text processing systems. His recent publications (2022-2025) demonstrate continued activity in string algorithms, particularly in pattern matching, string covers, and combinatorics on words, with a strong focus on theoretical computer science with applications in bioinformatics. 200 problems on automata, languages, computations (Cambridge University Press 2023) 125 Problems in Text Algorithms (Cambridge University Press, 2021) Jewels of Stringology (World Scientific, 2002) Fast parallel algorithms for matching problems in graphs (Oxford University Press 1998) Text algorithms (Oxford University Press 1994) Professor Rytter has collaborated extensively with researchers including Jakub Radoszewski, Tomasz Walen, Tomasz Kociumaka, and Maxime Crochemore. He is a member of the Academy of Europe (elected 2011, Informatics section) and has authored or co-authored more than 130 publications. He maintains an active research laboratory focused on string algorithms and combinatorics on words at the University of Warsaw.

Kyle Bellucci JohansonView profile

Visiting Assistant Professor

• Collaborative practice
• Digital media
• Drawing
• +14 more

Kyle Bellucci Johanson serves as a Visiting Critic in Cornell University's College of Architecture, Art, and Planning, Department of Art. Holding an MFA from California Institute of the Arts and a BA in Art and Reconciliation Studies from Bethel University, he merges artistic practice with critical theory through performance architecture and collaborative media. Whitney Independent Study Program (2022–23) Founding fellow at land's edge free school (Los Angeles) Teaching experience at SAIC, UIC, CUNY, and Cooper Union His research investigates: Power structures through spatial interventions Critical theory applications in art practice Post-capitalist imaginaries Hauntology and historical materialism Transdisciplinary approaches to social critique Project trends reveal: Reinterpretation of Soviet design principles Investigation of worker identity in post-industrial contexts Temporal and spatial dislocation in artistic practice Monument critique through performative methods Quantum theory-inspired architectural concepts Reimagining of common spaces as political sites Scientific awards include: Creative Research Grant (2025) Whitney ISP participation (2022–23) Automata Studio Residency (2022) Artists Run Chicago Grant (2021) BOLT Residency (2020–21) Through projects like KLUB WRKR —a nomadic workers' club reimagined for the gig economy—and table (2018–2022), a Chicago-based experimental space for artistic practice, he interrogates institutional frameworks while fostering community through discursive meals and collaborative exhibitions.

Sanjit A. SeshiaView profile

Professor

• Formal Methods
• Cyber-Physical Systems
• Computer Security
• +10 more

Sanjit A. Seshia is the Cadence Founders Chair Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley . He is affiliated with the Group in Logic and the Methodology of Science and participates in centers like the Industrial Cyber-Physical Systems Center , Berkeley AI Research , and the Simons Institute for the Theory of Computing . Research interests include formal methods for automated verification and synthesis of dependable systems, with applications to cyber-physical systems , AI-based autonomy , and computer security . His work spans SMT solving, model counting, syntax-guided synthesis, and algorithmic improvisation, with tools like UCLID5 , VerifAI , and Scenic for verifying autonomous systems and educational platforms like CPSGrader . Students and collaborators include notable researchers such as Dorsa Sadigh (Stanford), Daniel Fremont (UC Santa Cruz), and Hazem Torfah (Chalmers). He has co-founded startups like Decyphir and 20ⁿ Labs based on his research.

Risto MiikkulainenView profile

Professor

• Neuroevolution
• Evolutionary Computation
• Deep Learning
• +7 more

Risto Miikkulainen is a Professor of Computer Science and Neuroscience at the University of Texas at Austin and VP of AI Research at Cognizant AI Lab. He directs the UTCS Neural Networks Research Group and is currently on leave from UT, working on Evolutionary Computation and Deep Learning at Sentient Technologies, Inc. Education: Ph.D. in Computer Science, UCLA, 1990 M.S. in Applied Mathematics, Helsinki University of Technology (now Aalto University), 1986 Risto Miikkulainen's research focuses on biologically-inspired computation such as neural networks and evolutionary computation. His work spans three main areas: (1) Neuroevolution, evolving complex deep learning architectures and recurrent neural networks for sequential decision tasks in robotics, games, and artificial life; (2) Cognitive Science, developing models of natural language processing, memory, and learning that shed light on disorders such as schizophrenia and aphasia; and (3) Computational Neuroscience, studying the development, structure, and function of the visual cortex, episodic memory, and language processing. His research combines theoretical understanding of biological information processing with practical applications for developing intelligent artificial systems. His recent publications (2025) show a strong focus on evolutionary approaches to AI development, particularly in neural architecture search, loss function optimization, and explainable AI. Many papers explore the intersection of evolutionary computation with deep learning, creating more efficient and transparent AI systems. His work spans theoretical foundations and practical applications in areas ranging from environmental control systems to cognitive modeling. Scientific Awards: College of Fellows, International Neural Network Society, 2024 Best Pathway to Impact Award, NeurIPS Climate Change workshop, 2024 AAAI Fellow, 2023 IEEE CIS Evolutionary Computation Pioneer Award, 2020 Gabor Award, International Neural Network Society, 2017 Outstanding Paper of the Decade Award, International Society for Artificial Life, 2017 IEEE Fellow, 2016 Multiple Best Paper Awards at GECCO, CIG, and CEC conferences Deployed Application Award, AAAI/IAAI-2013, AAAI/IAAI-2018 Miikkulainen has extensive experience mentoring students through undergraduate research courses like CS378 Computational Intelligence in Game Design I and II, where students develop independent research projects on the OpenNERO research platform. He has received multiple awards for deployed applications, demonstrating the practical impact of his research. His work has led to the development of the NERO game platform, which serves as both an educational tool and research platform for AI. He directs the UTCS Neural Networks Research Group, which focuses on neuroevolution, cognitive science models, and computational neuroscience. The group has developed the NERO (Neuro-Evolving Robotic Operatives) platform, a machine learning game that allows users to train intelligent agents through evolutionary computation. The group's work spans theoretical research and practical applications in AI, with connections to both academic and industry partners.

Jiaoyang LiView profile

Assistant Professor

• Multi-Robot Coordination
• Artificial Intelligence
• Planning and Scheduling
• +5 more

Jiaoyang Li is an Assistant Professor at the Robotics Institute, Carnegie Mellon University , where she leads research in large-scale multi-robot coordination. She earned her Ph.D. in Computer Science from the University of Southern California (2022) under Professor Sven Koenig and holds a B.Eng. in Automation from Tsinghua University (2017) . Ph.D. (2022): University of Southern California B.Eng. (2017): Tsinghua University Research Focus : Jiaoyang Li's work centers on algorithms for multi-robot coordination in dynamic environments. Key areas include: Multi-Agent Path Finding (MAPF) Lifelong Planning for Autonomous Systems Kinodynamic Motion Planning Warehouse and Transportation Automation Human-Robot Collaboration Integration of Planning and Machine Learning Swarm Robotics Publication Trends : Recent work spans 2023-2025 , showing emphasis on: Scalable coordination for 10,000+ robots Bézier curve optimization for dual-arm assembly Diffusion models in multi-robot motion planning Guidance graph optimization for airport/railway traffic Multi-objective search in warehouse automation Temporal plan graphs for switchable passing orders Scientific Honors : ICAPS-24 Best Student Paper Award Three top dissertation awards (ICAPS-23, IFAAAMAS, USC) 2023 League of Robot Runners champion Outstanding student paper award at ICAPS-20 Technology Commercialization Award from USC Student Leadership : Advises 5 Ph.D. students and 1 Master's student at CMU, with alumni now at MIT (Ying Feng) and USC (Yimin Tang). Collaborates with visiting students from National University of Singapore and Tsinghua University. Lab Affiliation : Directs the Artificial Intelligence for Robot Coordination at Scale (ARCS) Lab , focusing on: Warehouse automation with thousands of robots Multi-arm LEGO assembly systems Railway coordination algorithms Cooperative assembly with multiple manipulators

Sanjay JainView profile

Professor

• Inductive Inference
• Recursion Theory
• Complexity Theory
• +3 more

Sanjay Jain is a Provost's Chair Professor in the Department of Computer Science at the School of Computing, National University of Singapore (NUS). His research focuses on theoretical computer science with particular emphasis on inductive inference, recursion theory, complexity theory, and computational learning theory. Education: B.Tech. in Computer Science from Indian Institute of Technology Kharagpur, India (1986) M.S. in Computer Science from University of Rochester, USA (1988) Ph.D. in Computer Science from University of Rochester, USA (1990) Professor Jain's research spans multiple areas of theoretical computer science. His primary contributions are in computational learning theory, where he has made significant advances in understanding the intrinsic complexity of language identification and the limits of inductive inference. His work on recursion theory explores fundamental questions about computability and complexity, while his research in complexity theory addresses structural aspects of computational problems. A notable achievement was his work on "Deciding Parity Games in Quasipolynomial Time," which won the prestigious STOC 2017 best paper award and later the EATCS-IPEC Nerode Prize. Professor Jain's publication record shows a consistent focus on theoretical foundations of computer science, particularly in learning theory and computational complexity. His recent work has expanded into automatic structures, semiautomatic models, and connections between computational learning and algebraic structures. There is a clear progression from foundational work on language identification to more complex models involving automatic functions, transducers, and connections to mathematical logic. Scientific Awards: STOC 2017 Best Paper Award for "Deciding Parity Games in Quasipolynomial Time" EATCS-IPEC Nerode Prize (2021) Professor Jain has served on the editorial board of Information and Computation and has been actively involved in the academic community through program committee memberships for major conferences including COLT, ALT, LATA, TAMC, and PRICAI. He has held leadership roles as program co-chair for ALT 2000 and ALT 2013, and conference chair for ALT 2005. His work has been supported by various research grants, though specific details are not provided in the available materials. Professor Jain leads research in theoretical computer science at NUS, where he has built a strong research group focused on computational learning theory and related areas. His work often involves collaborations with researchers from around the world, particularly with Frank Stephan, with whom he has co-authored numerous papers. His research group has made significant contributions to understanding the fundamental limits and possibilities of computational learning models.

Marina BlantonView profile

Associate Professor

• Applied Cryptography
• Information Security
• Privacy-Preserving Computation
• +3 more

Marina Blanton is an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo, and Faculty Director of Women in Science and Engineering within the School of Engineering and Applied Sciences. She holds a PhD in Computer Science from Purdue University (2007), along with multiple advanced degrees in Computer Science and Electrical Engineering from prestigious institutions in the US and Russia. Her research focuses on applied cryptography, information security, and privacy-preserving computation and outsourcing. She has pioneered work on secure multi-party computation protocols, privacy-preserving biometric authentication, and secure data analytics across distributed systems. Her contributions include foundational frameworks like PICCO, a compiler for private distributed computation, and advancements in protocols for genomic data analysis and floating-point secure computation. Blanton has been recognized with numerous awards, including IEEE and ACM Senior Membership (2016/2015), the ACM CCS Test of Time Award (2015), and the AFOSR Young Investigator Award (2013). Her research has been supported by grants such as NSF SaTC awards and AFOSR funding. Her work emphasizes practical implementations of secure computation, with applications in healthcare, biometrics, and distributed data systems. She has advised numerous students and contributed to educational initiatives promoting women in STEM through her leadership roles.

• Self-organized criticality
• Neuronal network dynamics
• Excitation/Inhibition balance
• +5 more

Anna Levina is an Assistant Professor for Computational Neuroscience at the University of Tübingen , affiliated with the Department of Computer Science under the Faculty of Science. Her research focuses on the self-organization of neuronal activity, critical dynamics in neural networks, and the excitation/inhibition balance in cortical circuits. Current positions: Assistant Professor (since 2018), Group Leader (2017-2018), Equality Officer (Computer Science) Previous roles: IST Fellow (2015-2017), Associated Researcher (2011-2015), Postdoc/PI (2011-2015), Postdoc (2008-2011) Her research integrates mathematical modeling , statistical physics , and computational neuroscience to study criticality phenomena, neural avalanches, and adaptive network dynamics. Key interests include: Self-organized criticality in neural systems Excitation/Inhibition balance mechanisms Network topology and dynamics Timescale analysis in neural processing Stochastic modeling of neural activity Recent publications reveal trends in understanding critical dynamics across biological and artificial networks, with applications to memory systems, sensorimotor integration, and disease modeling. She has received recognition as an IST Fellow .

Mehmet Esat BelviranliView profile

Assistant Professor

• Heterogeneous Architectures
• Runtime Systems
• Performance Modeling
• +5 more

Mehmet Esat Belviranli is an Assistant Professor in the Computer Science Department at the Colorado School of Mines, where he directs the High Performance Systems and Software Lab (HyperSys). His research focuses on increasing resource utilization in heterogeneous architectures through runtime systems, scheduling algorithms, and performance modeling, with publications in top venues including MICRO, PPoPP, and SC. Education: Ph.D. in Computer Science, University of California, Riverside (2016) M.S. in Computer Science, Bilkent University (2009) B.S. in Computer Science, Bilkent University (2006) Belviranli's research spans heterogeneous architectures, runtime systems, performance modeling, parallel programming, autonomous computing, deep learning acceleration, cyber-physical systems, and edge-cloud platforms. His work develops analytical models and programming abstractions to address resource management, scheduling, and security challenges in diversely heterogeneous systems, with applications in edge computing, autonomous systems, and machine learning acceleration. Recent projects emphasize real-world constraints and security implications. His publication trends reveal increasing focus on edge-cloud resource management (e.g., HARNESS), security vulnerabilities in heterogeneous systems (e.g., MC3), and deep learning acceleration under resource constraints. Key themes include memory contention modeling, scheduling for cyber-physical systems, and concurrent DNN execution, reflecting a shift toward practical deployment in security-sensitive edge environments. Scientific Awards: U.S. Air Force Research Lab Summer Faculty Fellowship Award (2022) U.S. Air Force Research Lab Summer Faculty Fellowship Award (2021) Oak Ridge National Laboratory Significant Event Award (2019) Best Paper Finalist, IEEE HPEC 2018 Outstanding Paper Award, DATE 2024 Belviranli mentors Ph.D. students Ismet Dagli (MLCommons Rising Star 2024, CGO'24 SRC finalist) and Justin Davis (DATE'24 Outstanding Paper Award winner). He has secured $2M+ in funding from NSF, DoE, and SRC, including an NSF-SaTC grant on mobile security (2024), a DoE grant on superconductive systems (2023), and an NSF FuSe grant on graphene nanoribbons (2023), often leading multi-institutional teams from Rochester, Virginia, Arizona, and Minnesota. The HyperSys Lab develops ecosystems for high-performance heterogeneous systems, with recent projects including HARNESS for edge-cloud resource management and MC3 for mobile SoC security. The lab has received equipment donations from Google Coral.ai and Xilinx, and collaborates with national labs on security challenges and next-generation semiconductor technologies.

Mingsheng YingView profile

Professor

• Quantum Computation
• Quantum Programming
• Model-checking Quantum Systems
• +5 more

Mingsheng Ying is a Distinguished Professor and Research Director of the Centre for Quantum Computation and Intelligent Systems (QCIS) at the Faculty of Engineering and Information Technology, University of Technology Sydney, Australia. He also holds the position of Cheung Kong Professor at the State Key Laboratory of Intelligent Technology and Systems, Department of Computer Science and Technology, Tsinghua University, Beijing, China. Professor Ying graduated from the Department of Mathematics, Fuzhou Teachers College, Jiangxi, China, in 1981. His primary research interests span quantum computation (particularly quantum programming and model-checking quantum systems), programming theory and formal methods, and the foundations of artificial intelligence (focusing on logic and uncertainty). As an author of the books "Foundations of Quantum Programming" (Elsevier - Morgan Kaufmann 2016) and "Topology in Process Calculus: Approximate Correctness and Infinite Evolution of Concurrent Programs" (Springer-Verlag, 2001), he has published over 100 papers in top international journals and conferences. His recent research publications demonstrate a strong focus on quantum programming languages, verification techniques for quantum systems, and the theoretical foundations of quantum computation. The trend in his work shows increasing emphasis on formal verification methods for quantum systems, particularly model-checking techniques for quantum Markov chains and quantum processes. His research bridges theoretical computer science with quantum information theory, creating frameworks for reliable quantum software development. Editorial Board, Artificial Intelligence, Elsevier, Amsterdam Editorial Board, Fuzzy Sets and Systems, Elsevier, Amsterdam Vice President, International Fuzzy Systems Association (elected in 2005) Program Chair, IFSA 2005, World Congress of International Fuzzy Systems Association Chairman, Chinese Association of Fuzzy Systems and Mathematics Professor Ying has secured significant research funding including multiple Australian Research Council Discovery Projects such as "Model-checking quantum Markov chains: towards verification techniques for quantum cryptographic systems" (2013-2015) and "Process algebra approach to distributed quantum computation and secure quantum communication" (2011-2013). His work has also received funding from the National Natural Science Foundation of China and Tsinghua University. At QCIS, he leads research in quantum software theory and methodology, with applications in quantum cryptography and secure communication.

Shiva NejatiView profile

Professor

• Software Engineering
• Cyber-Physical Systems
• Autonomous Vehicles
• +7 more

Shiva Nejati is a Professor at the University of Ottawa 's School of Electrical Engineering and Computer Science . He holds a PhD in Computer Science from the University of Toronto and previously worked as a Senior Scientist (2012-2019) and Scientist (2009-2012) at the SnT Centre (University of Luxembourg) and Simula Research Laboratory. Research focus: Software engineering for cyber-physical systems (autonomous vehicles, IoT), blending formal verification, machine learning, and search-based testing Key tools developed: ARIsTEO, SOCRaTEs, SimCoTest, EPIcuRus Editorial roles: Associate Editor for EMSE Journal (2025–), ASE Journal (2025–), IEEE Transactions on Software Engineering (2020–2024) His work combines formal methods , empirical software engineering , and AI/ML to address verification challenges in complex systems, particularly through evolutionary algorithms and surrogate modeling . Notable collaborations include industry partners in telecommunications, automotive, and aerospace sectors. Recent publications emphasize large language models for requirements analysis, adversarial testing of vision systems, and multi-objective optimization for test generation. His Sedna Research Lab actively trains graduate students in these cutting-edge methodologies.

David DotyView profile

Professor

• Molecular computing
• Algorithmic self-assembly
• Chemical reaction networks
• +8 more

David Doty is a Professor in the Department of Computer Science at the University of California, Davis . His research focuses on the intersection of molecular systems and computation , exploring how natural processes like chemical reactions , DNA nanotechnology , and self-assembly can perform computation. He also investigates connections to theoretical computer science, including distributed computing and algorithmic information theory . Doty's work bridges physics , chemistry , and biology through rigorous computational models like the Tile Assembly Model and Population Protocols . His research program includes software development ( scadnano , ppsim ), theoretical analysis, and collaborations with experimentalists. He teaches courses on theory of computation and molecular computing , and has advised numerous students in his research group. His publications cover topics such as algorithmic self-assembly , chemical reaction networks , and thermodynamic binding networks , with a focus on understanding fundamental computational and physical limits. Key software tools developed by his group include scadnano for DNA design and ppsim for population protocol simulations. Doty's recent research trends explore rate-independent chemical computing , error correction , and stochastic modeling in molecular systems. Current academic activity includes teaching ECS 120 (Undergraduate Theory of Computation), ECS 220 (Graduate Theory of Computation), and ECS 232 (Theory of Molecular Computation). He maintains a research lab in 2306 Academic Surge and continues to publish in leading conferences like DNA Computing and CMSB .

• Algorithms
• Game Theory
• Automata Theory
• +7 more

Marcin Jurdzinski is an Associate Professor (Reader) in the Department of Computer Science at the University of Warwick , UK. He has been a faculty member since 2004 and is a core member of the Foundations of Computer Science and Discrete Mathematics and its Applications research groups. University: University of Warwick School: Faculty of Science Department: Department of Computer Science Position: Associate Professor (Reader) Email: Marcin.Jurdzinski@warwick.ac.uk Office: CS2.19 His research lies at the intersection of algorithms, game theory, automata, and logic , with a strong emphasis on formal verification , model checking , and theoretical computer science . He is best known for his foundational work on parity games , including the development of small progress measures and discrete strategy improvement algorithms. The recent publications reveal a consistent focus on computational complexity in games and verification. Key themes include stochastic games, timed automata, bisimilarity, and quantitative analysis . His work often bridges theoretical insights with practical verification challenges, especially in real-time and probabilistic systems. He has supervised several PhD students and hosted postdoctoral researchers such as Laure Daviaud and Alexander Kozachinskiy. He has led EPSRC-funded projects including Solving Parity Games in Theory and Practice and Counter Automata: Verification and Synthesis . PhD Students: Aditya Prakash, Thejaswini K. S., Michail Fasoulakis, John Fearnley, Michal Rutkowski, Ashutosh Trivedi Postdocs: Laure Daviaud, Alexander Kozachinskiy He is actively involved in the academic community, serving on the steering committee of the Highlights of Logic, Games and Automata conference and on program committees for major venues such as CONCUR, ICALP, and LICS. He has also organized workshops including FORMATS and ICALP co-located events.