جست‌وجوی استاد و پژوهشگر

Rohit Chadhaمشاهده پروفایل

دانشیار

• Computer Security
• Formal Methods
• Program Analysis
• +۵ مورد دیگر

Rohit Chadha is an Associate Professor in the Department of Electrical Engineering and Computer Science at the University of Missouri and serves as the Director of the Mizzou Cybersecurity Center . His research focuses on formal methods and their application to cybersecurity , particularly in verifying differential privacy mechanisms and randomized security protocols . Education : PhD from the University of Pennsylvania, BTech from the Indian Institute of Technology, Delhi Previous Positions : INRIA Saclay (France), University of Illinois at Urbana-Champaign, Instituto Superior Tecnico (Portugal), University of Sussex (UK) Research Interests include automated verification of security hyperproperties , probabilistic automata , and quantitative information flow . His work addresses privacy risks in aggregate data and AI-driven battlefield communication systems. Publication Trends show a focus on differential privacy verification , zero-trust architectures , and model checking of probabilistic systems. He has contributed to security frameworks for military applications and educational initiatives using collegiate competitions. Scientific Awards : NSF CAREER Award (2016) NSF SHF: Medium Grant (2019) NSF TWC: Medium Grant (2013) Rohit leads the Mizzou Cybersecurity Center , collaborating with industry partners through its Industrial Advisory Board . His research integrates formal verification with practical cyber defense applications.

• Modeling and Verification of Reactive Systems
• Quantitative Analysis of Stochastic Systems
• Probabilistic Model Checking
• +۸ مورد دیگر

Christel Baier is a full Professor and head of the Chair for Algebraic and Logic Foundations of Computer Science at the Faculty of Computer Science, Technische Universität Dresden, a position she has held since 2006. She previously served as an associate professor for Theoretical Computer Science at the University of Bonn from 1999 to 2006. She is currently the dean of the Faculty of Computer Science at TU Dresden (2025–2027), having been vice-dean from 2019 to 2024. She holds a Diploma in Mathematics (1990), a Ph.D. in Computer Science (1994), and a Habilitation (1999), all from the University of Mannheim. In 2022, she was awarded an honorary doctorate from RWTH Aachen. Her research centers on formal methods in computer science, with a strong emphasis on modeling, specification, and verification of reactive and stochastic systems. She is a leading expert in probabilistic model checking, temporal and modal logics, automata over infinite structures, game theory, and the verification of infinite-state systems. Her work bridges theoretical foundations with practical applications in system reliability and correctness. The recent publications and edited volumes reflect a consistent focus on formal verification, logic in computer science, and tools for system analysis. Her editorial leadership in major venues such as LICS, TACAS, and FoSSaCS underscores her influence in shaping the research agenda in theoretical computer science and formal methods. Jean-Claude Laprie Award in Dependable Computing (2023) Honorary doctorate from RWTH Aachen (2022) Member of Academia Europaea (since 2011) Editor-in-Chief of Acta Informatica (2015–2022) Steering Committee Member of LICS, FoSSaCS, FORTE, and FSEN Extensive service on program committees of top-tier conferences including CAV, CONCUR, and ICALP Christel Baier has advised numerous PhD and master’s students (though not explicitly listed), and has led major research projects funded by DFG, EU, and DAAD. She has organized pivotal events such as CONCUR'06, TACAS'15, and LICS'22. She is actively involved in academic governance, serving on the senate of TU Dresden (2015–2020), as ombudsperson for the Department of Computer Science, and on the Scientific Advisory Board of Schloss Dagstuhl. Her leadership in the German Excellence Initiative and DFG Research Training Groups highlights her role in shaping national research agendas.

• Logic in computer science
• linear dynamical systems
• automated verification
• +۳ مورد دیگر

James Worrell is a Professor of Computer Science at the University of Oxford , with a focus on logic in computer science , linear dynamical systems , and automated verification . He is also a Fellow of Green Templeton College. His research spans theoretical computer science and formal methods , including work on metric temporal logic , probabilistic semantics , and category theory . His publications address decision problems , verification of linear dynamical systems , and automata theory . James has received the EPSRC Established-Career Fellowship for his work in linear dynamical systems verification . His recent papers include polynomial invariants , polyhedral escape problems , and skolem problem solutions . He has advised students such as Mehran Hosseini , Pascale Gourdeau , and Ventsislav Chonev , and teaches courses like Computational Learning Theory and Logic and Proof . His work appears in venues like ICALP , LICS , and SODA .

• Approximation Algorithms
• Probabilistically Checkable Proofs
• Hardness of Approximation
• +۳ مورد دیگر

Amey Bhangale is an Assistant Professor in the Department of Computer Science and Engineering at the University of California, Riverside. Prior to this, he held positions as a post-doctoral fellow at the Weizmann Institute of Science under Irit Dinur and a research fellowship at the Simons Institute. His research focuses on Approximation Algorithms , Probabilistically Checkable Proofs , Hardness of Approximation , and Analysis of Boolean Functions . Research Trends His recent work explores inapproximability bounds for constraint satisfaction problems, parallel repetition theorems, and additive combinatorics in finite fields. Notable collaborations include Subhash Khot, Dor Minzer, and Yang P. Liu. Teaching CS219: Advanced Algorithms (2025) CS141: Intermediate Data Structures and Algorithms (2024) CS218: Design and Analysis of Algorithms (2023) CS215: Theory of Computations (2021-2023)

Stefan Borgwardtمشاهده پروفایل

پژوهشگر

• Knowledge Representation
• Description Logics
• Automated Reasoning
• +۸ مورد دیگر

Stefan Borgwardt is a Researcher and Teaching Associate at the Chair of Automata Theory, Faculty of Computer Science, Technische Universität Dresden, working under Prof. Franz Baader. He leads key research projects such as Practical Planning with Ontologies (PPO) and contributes to the Center for Perspicuous Computing (CPEC), funded by DFG and SNF. His work bridges theoretical logic and practical AI systems. Research Interests: Knowledge Representation and Reasoning Description Logics and Ontology-Mediated Query Answering Explainable AI and Proof Visualization (Evee/ Evonne systems) Temporal, Fuzzy, and Probabilistic Logics Automated Planning with Ontologies Logic-Guided Natural Language Generation His recent publications (2021–2025) show a strong trend toward explainability in logical reasoning, with a focus on modular, interactive, and user-friendly proof systems. He investigates reasoning complexity in expressive description logics and develops practical tools for ontology explanation and planning. His work often combines symbolic AI with real-world applications such as sensor data interpretation and autonomous systems. Scientific Awards: Harold Boley Distinguished Paper Award (RuleML+RR'23) Best Paper Award (RuleML+RR'22, JELIA'19, AI'15) Quality Champion for ECAI'23 reviewing Commerzbank Award for PhD thesis (2014) Distinguished Student Paper Awards (DL'14, DL'13) N. J. Lehmann Award (2011) Stefan Borgwardt actively advises and collaborates with students and early-career researchers on projects involving explanation, planning, and reasoning. He has secured competitive funding through DFG and SNF grants and plays a leadership role in the KR community as PC co-chair, senior PC member, and steering committee member for major conferences like DL, KR, and JELIA. He is also a reviewer for top-tier journals including Artificial Intelligence and Journal of the ACM . Labs and Teams: He is a core member of the Chair of Automata Theory at TU Dresden and contributes to the Center for Perspicuous Computing (CPEC), where he works on projects A3 (Description Logic Explications) and E2 (Safe Handover in Mixed-Initiative Control) in collaboration with Vera Demberg and Antonio Krüger.

Neng-Fa Zhouمشاهده پروفایل

استاد

• Programming Languages
• Constraint Programming
• Logic Programming
• +۶ مورد دیگر

Neng-Fa Zhou is a Professor of Computer and Information Science at Brooklyn College and the Graduate Center of the City University of New York (CUNY). He holds a BS from Nanjing University (1984), and MS and PhD from Kyushu University (1988, 1991). Before joining CUNY, he served as an Associate Professor at Kyushu Institute of Technology (1991-1999) and held visiting positions at Yale, Alberta, Tokyo Tech, and Melbourne. Specializes in programming languages, constraint logic programming, and compiler design Developed Picat and B-Prolog languages with constraint-based graphics libraries Contributed to SAT encodings, multi-agent pathfinding, and declarative programming Scientific Awards: Most Practical Paper Award at PADL 2017 Award in ASP Solver Competition for BPSolver (2011)

Ramyaaمشاهده پروفایل

استادیار

• Theory of Computation
• Computational Complexity
• Logic
• +۷ مورد دیگر

Ramyaa is an Assistant Professor in the Department of Computer Science & Engineering at New Mexico Tech. Her research focuses on the intersection of computation, logic, and emerging models of computation, including implicit complexity theory and biologically inspired neural networks. She also explores machine learning applications in real-world problems and interpretable AI. Education: Ph.D. in Computer Science, with a focus on theoretical foundations. Research Interests: Implicit complexity (relating logical complexity to computational resource constraints), formalization of computational models (e.g., biological neural networks), machine learning (including neural network training, adversarial robustness, and program synthesis), and applications in healthcare, security, and education. Her work emphasizes adaptable complexity measures for novel computational frameworks. Recent Trends in Publications: Recent work includes reinforcement learning for astrophysical data workflows, biologically inspired sleep algorithms for neural networks, and machine learning applications in nutritional epidemiology. She also explores educational technology, such as games for teaching logic and interactive programming tutorials. Grants & Advising: Advises research in machine learning, theoretical computer science, and interdisciplinary applications. Active in grant-seeking for projects at the intersection of theory and applications. No listed students, but collaborates widely with researchers globally. Affiliations: Fellow at the Simons Institute for the Theory of Computing (Berkeley), organizer of conferences like ICALT and CSR, and contributor to initiatives like WiCS at NMT. Teaches courses in formal languages, automata theory, and reinforcement learning.

Giorgio Bacciمشاهده پروفایل

دانشیار

• Behavioural Metrics
• Model Synthesis and Automata Learning
• Analysis and Verification of Cyber-Physical Systems
• +۳ مورد دیگر

Giorgio Bacci is an Associate Professor at the Department of Computer Science , Aalborg University , Denmark. He is a member of the Distributed, Embedded, and Intelligent Systems (DEIS) research group led by Prof. Kim G. Larsen. He earned his Ph.D. in Computer Science from the University of Udine (2013) under Prof. Marino Miculan, following M.Sc. and B.Sc. degrees in Computer Science from the same university (2008 and 2005, both 110/110 cum laude ). Research Interests include: Behavioural Metrics : Quantitative methods for system equivalence and approximation. Model Synthesis and Automata Learning : Automated construction of models for probabilistic/stochastic systems. Analysis of Cyber-Physical Systems : Formal verification techniques for real-time and hybrid systems. Process Algebras : Nondeterministic, probabilistic, and stochastic process calculi. Semantics of Programming Languages : Formal models for probabilistic and concurrent computation. Scientific Service includes roles as PC member for LICS 2025 , ICALP 2025 , and co-chair for EXPRESS/SOS 2025 and GandALF 2025 . He has contributed to 35 publications in areas like probabilistic automata , Markov processes , and bigraphical models , with a focus on computational complexity and behavioral distances . Awards include: Teacher of the Year 2022/2023 (Department of Computer Science, Aalborg University) Best Paper Award at CALCO 2021 .

• Computer Vision
• Sensor Fusion for Mobile Robotics
• Low Power Computing
• +۴ مورد دیگر

Jorge Lobo is an Assistant Professor at the Department of Electrical and Computer Engineering, Faculty of Science and Technology, University of Coimbra. His research focuses on computer vision, sensor fusion for mobile robotics, and low power computing, with recent emphasis on quantum computing and bio-inspired computational approaches. B.Sc/M.Sc in Electrical Engineering (University of Coimbra) Ph.D. in Electrical and Computer Engineering (2007, thesis: 'Integration of Vision and Inertial Sensing') Research Interests: Specializes in artificial perception systems combining computer vision and inertial sensing for robotics. Develops probabilistic models for sensor fusion and explores unconventional computing architectures like stochastic circuits and quantum computing for efficient Bayesian inference. Key applications include autonomous robotic grasping and disaster response systems. Scientific Leadership: Principal Investigator for Q-Bet: Bridging classical/quantum computing via HPC and bio-inspired methods Founding member of Quantum@UC interest group Coordinator of quantum computing specialization courses (collaboration with Physics & Computer Science departments) Key Projects: Contributed to European initiatives BACS (Bayesian Cognitive Systems), HANDLE (robotic dexterity), BAMBI (Bayesian inference hardware), and ECOBOTICS.SEA (marine ecosystem robotics). Academic Recognition: IEEE Senior Member and former president of the Portuguese IEEE RAS chapter. Developed innovative remote labs for stochastic computing education.

• Theoretical Computer Science
• Statistics
• High-Dimensional Estimation
• +۷ مورد دیگر

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.

José Nuno Oliveiraمشاهده پروفایل

استاد

• Formal Methods
• Algebra of Programming
• Functional Programming
• +۳ مورد دیگر

Roles and Affiliations: José Nuno Oliveira is a Full Professor at the University of Minho's School of Engineering, Department of Computer Science. He is a member of the HASLab (High-Assurance Software Laboratory) and the Formal Methods Europe (FME) Association. He has held roles such as General Chair of the 3rd World Congress on Formal Methods (FM'19) and served on numerous international conference committees. Education: Habilitation in Computing Foundations (2010), University of Minho Ph.D. in Computer Science (1984), University of Manchester, UK M.Sc. in Computer Science (1981), University of Manchester, UK Lic. Eng. Elect. (Digital Systems & Computers) (1978), University of Porto, Portugal Research Interests: Oliveira focuses on formal methods, program calculation, and algebraic programming. His work emphasizes improving software design through mathematical rigor, including applications of relational algebra, functional programming, and program transformation. He has contributed to frameworks like Alloy and QAlloy for software verification. Publications: His recent work spans topics like quantum programming (e.g., quantamorphisms), typed linear algebra for data analysis, and formal methods in education. Over 80 publications include influential papers on Galois connections, metaphorisms, and coalgebraic systems. Awards and Grants: Not explicitly listed, but his leadership roles and extensive conference involvement highlight his recognition in formal methods. Active in projects like IBEX (cyber-physical systems) and TRUST (Alloy-based design). Teaching and Service: Teaches courses on program calculation and formal methods. Serves on editorial boards (e.g., Formal Aspects of Computing ) and chairs international conferences. Active in promoting formal methods education through workshops and training initiatives. Labs and Teams: Co-leads the HASLab (INESC TEC & University of Minho), focusing on high-assurance software systems. Collaborates on projects like EVEREST (railway network verification) and LeanBigData (big data analytics).

• Computer Science
• Probabilistic Programming
• Semantics
• +۶ مورد دیگر

Fredrik Dahlqvist is a faculty member at the University College London , Department of Computer Science , focusing on theoretical and applied aspects of probabilistic programming , semantics , and formal verification . His work bridges computer science with mathematical logic , machine learning , and programming language theory . Education: PhD in Coalgebraic Logics from Imperial College London (2014) His recent publications (2016–2025) explore model pruning , reparameterisation invariance , probabilistic numerical analysis , and categorical approaches to machine learning . Key themes include optimisation , cosine similarity , and omega-complete cone duality in probabilistic systems. Contact: f.dahlqvist@ucl.ac.uk (institutional) or f.p.h.dahlqvist@gmail.com (private), located at Gower Street, London WC1E 6BT, United Kingdom .

Hwa Changمشاهده پروفایل

دانشیار

• Wireless Communications
• e-care
• Computer Networking
• +۵ مورد دیگر

Hwa Chang is a tenured Associate Professor in the Department of Electrical & Computer Engineering at Tufts University , where he has been a faculty member since 1987. He directs the Tufts Wireless Lab and oversees the Computer Engineering Program . His research focuses on wireless communications, sensor networks, distributed computing, and engineering education. Education: Ph.D. in Electrical and Computer Engineering (Drexel University, 1987), M.S. in Computer Science (Montana State University, 1983), B.S. in Engineering Science (National Cheng Kung University, 1977). Research Interests: Wireless Sensor Networks (WSNs), energy-efficient routing, mobile ad hoc networks, grid computing, and network security. Notable projects include the Wireless Grid initiative and WISeNET , exploring resource-sharing in dynamic environments. Awards: Outstanding Alumni Award (National Cheng-Kung University, 2005) Excellent Leadership and Service Award (New England Association of Chinese Professionals, 2005) $600K NSF grant for Virtual Markets research (2002-2004) Advising & Grants: Advised ~150 master students and 160 senior design projects Ph.D. graduates include Amlir Davis (2013), Na Wang (2009) Recipient of grants from BBN, NSF, and industry partnerships like A$W Technology Corp. Professional Activities: Leadership roles in New England Association of Chinese Professionals, IEEE, and global science organizations. Editor-in-chief for multiple conference proceedings.

• Machine Learning
• Natural Language Processing
• Language Modelling
• +۷ مورد دیگر

Wilker Ferreira Aziz is an Assistant Professor at the Institute for Logic, Language and Computation (ILLC) within the Faculty of Science at the University of Amsterdam, where he leads the Probabilistic Language Learning group. His primary affiliation is with the Natural Language Processing & Digital Humanities research unit. His research focuses on the intersection of machine learning, natural language processing, and probabilistic modeling. Key areas of interest include language modeling, machine translation, syntactic parsing, text classification, and question answering. He develops techniques for probabilistic inference, gradient estimation, and uncertainty quantification in neural language models. Dr. Aziz's recent publications demonstrate a strong focus on uncertainty in natural language generation, with multiple papers at top-tier conferences like EACL, EMNLP, and ICLR. His work examines how language models represent uncertainty compared to humans, calibration issues when humans disagree on labels, and methods for more robust decision-making in text generation. Best Paper Award at Coling 2020 He actively supervises both PhD and MSc students, with several ongoing PhD projects focusing on uncertainty in language models and neural text generation. Dr. Aziz serves on program committees for major ML and NLP conferences including ACL, EMNLP, NeurIPS, and ICLR, and has acted as area chair for several of these venues. His research has been supported through positions at the Mercury Machine Learning Lab, a collaboration between Booking.com, TU Delft, and the University of Amsterdam.

Raquel Garrido Alhamaمشاهده پروفایل

استادیار

• Computational modelling of language learning
• Language acquisition
• Language evolution
• +۷ مورد دیگر

Dr Raquel Garrido Alhama is an Assistant Professor of Artificial Intelligence for text and human interaction at the Institute for Logic, Language and Computation (ILLC) , University of Amsterdam. She also co-directs the /k/omputation and Language Lab and previously served as Assistant Professor at the Cognitive Science and Artificial Intelligence department of Tilburg University. She earned her PhD from the ILLC under the supervision of Jelle Zuidema, Remko Scha and Carel Ten Cate, with a dissertation entitled Computational Modelling of Artificial Language Learning . Prior post-doctoral positions include the Max Planck Institute for Psycholinguistics and the Basque Center on Cognition, Brain and Language. Research Interests: Computational modelling of language learning and evolution Language acquisition, word learning and sentence processing Neural-symbolic integration and connectionist architectures Visual and auditory word recognition, syntactic parsing and part-of-speech tagging In recent years her work has converged on validating developmental milestones—such as the onset of productive determiner–noun combinations—using large-scale child corpora and neural models. She also investigates how multi-agent referential games can lead to emergent compositional languages, moving from image to richer graph representations. Scientific Awards: Best Article Award (2019) from Psychonomic Bulletin & Review for the review on computational models of rule learning Best Poster Award (2015) at the International Conference on Cognitive Modeling Teaching & Supervision: Dr Alhama has designed and lectured courses on advanced programming for cognitive science, computational linguistics, linear algebra and language acquisition at Tilburg University, University of Amsterdam, Radboud University and the University of the Basque Country. She currently supervises eleven MSc and BSc students in AI, Logic and Cognitive Science. Labs & Teams: She is the founding co-director of the /k/omputation and Language Lab together with Phong Le, where they use Language Emergence frameworks to explore the cognitive prerequisites for displacement and compositionality in human language.