جست‌وجوی استاد و پژوهشگر

Amar Hadzihasanovicمشاهده پروفایل

استادیار

• Category Theory
• Higher-Dimensional Algebra
• Quantum Computing
• +۳ مورد دیگر

Amar Hadzihasanovic is an Assistant Professor at Tallinn University of Technology, affiliated with the Compositional Systems and Methods group, and a Scientific Advisor at Quantinuum. He specializes in category theory, higher-dimensional algebra, and their applications in quantum computing and formal systems. His recent work includes organizing the 110th Peripatetic Seminar on Sheaves and Logic (PSSL) and completing a book on higher-categorical diagrams with Cambridge University Press. Hadzihasanovic has been awarded grants from ARIA (Safeguarded AI programme) and the Estonian Research Council, supporting his research on diagrammatic rewriting and homotopy theory. His research interests span categorical foundations, diagrammatic sets, and computational aspects of higher-dimensional structures. Key contributions include model structures for (∞, n)-categories, acyclicity conditions in pasting diagrams, and formal axiomatizations of quantum systems. He has advised PhD students Alkis Ioannidis and Clémence Chanavat, and collaborates widely with institutions like the University of Cambridge and Quantinuum. Hadzihasanovic has delivered invited talks at conferences such as Category Theory 2024, the Nordic Congress of Mathematicians, and the Geometric and Topological Methods in Computer Science (GETCO). His teaching includes a course on category theory and diagrammatic reasoning at Kyoto University. His software, including the rewalt library, supports topologically sound higher-dimensional diagram rewriting.

• Applied Category Theory
• Game Theory
• Theoretical Computer Science
• +۳ مورد دیگر

Matteo Capucci is a researcher at the University of Strathclyde , affiliated with the Department of Computer and Information Sciences . His work centers on applied category theory , game theory , and mathematical cybernetics , with a focus on compositional structures and coalgebraic modeling. PhD in Computer and Information Sciences Research interests include: Extensive form games and equilibrium models Categorical optics and fibrational structures Compositionality failures in cohomology and sheaf theory Quantitative reasoning and parametric categories Open energy-driven systems in physics His publications from 2020–2025 span theoretical advancements in category theory, applications to game theory, and connections to cybernetics, with recurring themes of feedback, gradient descent, and compositional modeling. A notable prize is the Distinguished Presentation Award (2021) . Capucci contributed to the EPSRC-funded project "Maths DTP 2020" , collaborating with Fredrik Nordvall Forsberg, Julian Hedges, and others. He has co-authored 4 research outputs, including conference papers and book chapters.

Larry P. Heckمشاهده پروفایل

استاد

• Artificial Intelligence
• Conversational Systems
• Machine Learning
• +۵ مورد دیگر

Larry P. Heck is a Professor at the Georgia Institute of Technology with joint appointments in the Schools of Electrical and Computer Engineering and Interactive Computing. He holds the Rhesa S. Farmer Distinguished Chair of Advanced Computing Concepts and is a Georgia Research Alliance Eminent Scholar. His career spans academia, industry, and research leadership, with notable roles at Microsoft, Google, Samsung, and SRI International. BSEE, Texas Tech University (1986) MSEE, Georgia Institute of Technology (1989) PhD in Electrical Engineering, Georgia Institute of Technology (1991) His research focuses on Artificial Intelligence , particularly in Conversational Systems , Machine Learning , and Natural Language Processing . Key subfields include dialogue systems, speech/speaker recognition, multimodal interaction, and large language model (LLM) governance. Recent publications emphasize dataset creation, intent modeling, reinforcement learning, and ethical AI practices. Scientific awards include IEEE Fellow , National Academy of Inventors Fellow (2025) , and multiple accolades from Texas Tech and Georgia Tech. He has led groundbreaking work in deep learning for speech processing and holds over 50 U.S. patents.

Manling Liمشاهده پروفایل

استادیار

• Computer Science
• Artificial Intelligence
• Machine Learning
• +۷ مورد دیگر

Manling Li is an Assistant Professor at the Department of Computer Science, Northwestern University. She previously served as a postdoc at Stanford University's Vision and Learning Lab under Prof. Jiajun Wu and received her Ph.D. from the University of Illinois at Urbana-Champaign (advisor: Prof. Heng Ji). Her research spans Language + Vision + Robotics with applications in Embodied AI and AI for Science . Key Research Areas : Knowledgeable Foundation Models, Reasoning & Planning, Compositionality, Multimodal Knowledge Extraction, Factuality & Trustworthiness in AI Leadership Roles : Organizing Committee for ACL 2025, NAACL 2025, EMNLP 2024 Research Trends in her 15 most recent publications show: Advancing Embodied AI through structured reasoning and planning frameworks Developing Vision-Language Models for 3D layout optimization and video understanding Addressing LLM Hallucinations via knowledge shadowing and mechanistic interpretability Creating collaborative agent systems with out-of-sync recovery mechanisms Scientific Recognition : ACL 2024 Outstanding Paper SoCal NLP 2024 Best Paper Microsoft Research Fellowships (PhD & Postdoc) DARPA Riser & EE CS Rising Star Advising Impact : Mentored 19 students in developing the UIUC information extraction system. Currently advising 12 students across PhD, Master's, and undergraduate levels, with particular emphasis on supporting underrepresented groups. Led teams to rank 1st in DARPA AIDA evaluations.

Jingwei Jiمشاهده پروفایل

عضو هیئت علمی

• Human Activity Understanding
• Video Analysis
• 3D Vision
• +۲ مورد دیگر

Jingwei Ji is a Research Scientist at Waymo LLC, specializing in computer vision and machine learning. He holds a Ph.D. in Electrical Engineering from Stanford University, where he was co-advised by Prof. Juan Carlos Niebles and Prof. Silvio Savarese, and a B.Sc. in Physics from Peking University. Education Ph.D. in Electrical Engineering, Stanford University B.Sc. in Physics, Peking University His research focuses on human activity understanding , video analysis , 3D vision , and scene graph modeling . He pioneered the Action Genome dataset, which bridges human actions and human-object relationships through spatio-temporal scene graphs. Jingwei's recent publications emphasize temporal alignment in few-shot learning, semantic segmentation of actors/actions, and 3D shape reconstruction. His work spans both theoretical advancements and practical applications in autonomous systems. Academic services include serving as a reviewer for top-tier conferences like CVPR, ICCV, AAAI, and journals including The Visual Computer. He organized workshops at CVPR 2020 and ECCV 2020 on compositional perception. Previously, he worked as an Applied Scientist Intern at Amazon Go (2018) and contributed to open-source projects like ActionGenome, a Python-based video dataset framework under MIT license.

Lei Buمشاهده پروفایل

استاد

• Software Verification
• Software Testing
• Software Analysis
• +۸ مورد دیگر

Lei Bu is a Professor and Vice Dean of the Software Institute at Nanjing University, China. He has been with Nanjing University since 2010, progressing from Assistant Professor to his current position. His academic career includes a visiting position at Microsoft Research Asia through their StarTrack Program from 2014-2015. Professor Bu received his B.Sc. and Ph.D. degrees in Computer Science from Nanjing University, with additional research experience at Carnegie Mellon University and University of Texas at Dallas during his doctoral studies. His academic journey shows steady progression through the ranks at his alma mater. Lei Bu's research primarily focuses on software verification, testing, and analysis, with particular expertise in model checking, bounded model checking, formal methods, and cyber-physical systems. His work spans theoretical foundations to practical applications in safety-critical systems. Recent publications demonstrate growing interest in integrating machine learning techniques with traditional formal methods, as seen in works like SpecGen that leverage large language models for program specification generation. His research outputs show a consistent focus on verification techniques for complex systems, particularly addressing challenges in hybrid systems, cyber-physical systems, and IoT applications. Professor Bu has developed several verification tools including BACH (Bounded Reachability Checker for Linear Hybrid Automata) and BRICK (Bounded Reachability Checker of Numerically-Intensive C Code), which have been used in international verification competitions. 2023: Zhongchuang Software Talent Award 2022: CCF-IEEE CS Young Computer Scientist Award 2020: The Outstanding Teachers of Computing in Higher Education Award Program 2019: NASAC Young Software Innovation Award 2016: Young Talent Development Program 2014: StarTrack Program Visiting Young Faculty 2007: Full Scholarship under the State Scholarship Fund Professor Bu serves as a Principal Investigator on multiple significant research projects funded by the Natural Science Foundation of China, including a Key Program grant (2023-2027) on dynamic adjustment-control-fault tolerance theory. He has also advised numerous students and taught courses including Formal Languages and Automata, Theoretical Foundation of Software Engineering, and Preliminary Introduction to the Theory of Computation. His laboratory work focuses on developing practical verification tools for industrial applications in cyber-physical and IoT systems.

• Formal Verification
• Autonomous Systems
• Robotics
• +۳ مورد دیگر

Matt Luckcuck is a Lecturer in Computer Science at the College of Science and Engineering. His research focuses on formal verification of autonomous systems, safety-critical software, and robotics. He has contributed to standards development for autonomous systems through the IEEE P7009 initiative. Key research interests include formal methods for robotics, verification of multi-agent systems, and safety protocols for hazardous environments. His work bridges theoretical formal models with practical applications in autonomous robotics and modular system design. Recent publications emphasize compositional verification techniques, heterogeneous system validation, and scalable planner architectures for multi-agent competitions. His research has been applied to inspection robots, aircraft engine controllers, and space rover systems. Luckcuck collaborates extensively with industry and academic partners on safety-critical Java specifications and autonomous system standards. He has published over 15 peer-reviewed articles and contributed to multiple international conferences on formal methods and robotics.

Konstantinos Sarakinosمشاهده پروفایل

استاد

• Thin Film Physics
• Surface Science
• Materials Physics
• +۳ مورد دیگر

Professor Konstantinos Sarakinos holds a position at the Department of Physics, University of Helsinki, and is the Chief Scientific Officer of MIMSI Materials AB. His research focuses on thin film synthesis, surface physics, and materials engineering with applications in energy and nanotechnology. He has held roles at Linköping University (Sweden) and KTH Royal Institute of Technology. Sarakinos earned a Ph.D. from RWTH Aachen University and a Docent title from Linköping University. Education: Ph.D. in Physics (RWTH Aachen, 2008), M.Sc. in Nanosciences (Aristotle University, 2004), M.Sc. in Mechanical Engineering (Aristotle University, 2002). His work combines experimental and computational methods to study material growth mechanisms and nanostructure formation under non-equilibrium conditions. Research interests include manipulating metal film morphology on weakly-interacting substrates, developing hierarchical heterostructures, and exploring compositionally complex materials. He leads projects funded by the Academy of Finland and EU (e.g., SilverAlloyPVs/EIT project). His publications span over 79 peer-reviewed articles focusing on thin film growth dynamics, surface chemistry, and materials for energy applications.

Ahmed Mohammed Said Lutfi Abdelhadyمشاهده پروفایل

استادیار

• Chemistry
• Materials Science
• Energy Applications
• +۳ مورد دیگر

Dr. Ahmed Abdelhady is an Assistant Professor of Chemistry at Khalifa University since 2022. He previously held postdoctoral and research positions at KAUST (2013–2016), the Italian Institute of Technology (2016–2021), and the Polish Center for Technology Development (2021–2022). His academic journey began with a Ph.D. in Chemistry from the University of Manchester (2011), followed by a role as Assistant Professor of Inorganic Chemistry at Mansoura University. Education : Ph.D. in Chemistry, University of Manchester (2011) B.Sc. in Chemistry, University of Mansoura (2002) Dr. Abdelhady specializes in materials chemistry, with a focus on semiconductors and nanomaterials. His work explores halide perovskite single crystals and nanocrystals , metal chalcogenide quantum dots , and their optoelectronic applications. He leads the CRYStallization of structurally and compositionally engineered 2D and quasi-2D halide perovsKITES for optoelectronic applications (CRYSKITES) project. He has co-authored publications in high-impact journals such as Nature Communications , Journal of the American Chemical Society , and Advanced Materials . Dr. Abdelhady is affiliated with the Center for Catalysis and Separation Research and has mentored graduate students like Mohammed Misbah Uddin .

Matthieu Labeauمشاهده پروفایل

مدرس ارشد

• Natural Language Processing
• Machine Learning
• Representation Learning
• +۲ مورد دیگر

Matthieu Labeau is a Senior Lecturer at Télécom Paris, affiliated with the Department of Image, Data, Signal (IDS). He joined the institution in 2019 after completing his PhD at the University of Paris-Saclay and a postdoctoral position at the University of Edinburgh. His research primarily centers on Natural Language Processing (NLP), with specialized interests in representation learning, language modeling, and conversational AI. His work spans: Core NLP : Contextual word representations, semantic alignment, and polysemy analysis. Machine Learning : Hierarchical classification, graph prediction, and few-shot learning techniques. Applications : Emotion recognition in dialogues, persuasiveness decoding, and educational NLP tools. Labeau leads research in the Signal, Statistics and Learning (S2A) team at the Information Processing and Communication Laboratory (LTCI). His recent publications demonstrate a strong focus on improving language model interpretability and efficiency, with innovations in tokenization effects and multimodal fusion. Though no awards or grants are mentioned, his consistent output in top-tier venues (e.g., NeurIPS, ACL, AAAI) highlights significant scholarly contributions. He actively collaborates on tools like EZCAT for conversation annotation and mentors researchers in NLP projects. Current work explores LLM capabilities in persuasion assessment and optimal transport methods for graph-based learning.

Gregory Chocklerمشاهده پروفایل

استاد

• Distributed Computing
• Blockchain Technology
• Fault-Tolerant Systems
• +۳ مورد دیگر

Professor Gregory Chockler is a full professor at the University of Surrey's Department of Computer Science, affiliated with the School of Computer Science and Electronic Engineering. He is Joint Head of the Distributed and Networked Systems Group and a member of the Surrey Centre for Cyber Security. His career spans roles at MIT, IBM Research, Royal Holloway University of London, and multiple visiting positions at institutions like EPFL and KTH. Education: Bachelor's and Master's degrees in Computer Science (Israel) PhD from the Hebrew University of Jerusalem Postdoctoral research at MIT (2003-2005) Research Interests: Chockler focuses on distributed systems, blockchain, and fault-tolerant computing. His work includes scalable consensus protocols, secure distributed storage, and applications of distributed algorithms in cloud and blockchain systems. Recent efforts emphasize resilient blockchain systems and efficient consensus mechanisms under communication failures. Key Contributions: His research has led to advancements in IBM WebSphere products, including Speculative Paxos for cloud management and event-monitoring techniques. Current projects explore NVM-based durable systems (e.g., Mangosteen) and channel reliability in distributed networks. Awards & Grants: IBM Outstanding Technical Achievement Award (2010s) Stellar Development Foundation Grant (2020) Facebook Faculty Award (2015) Advising & Collaboration: Supervises PhD students in distributed systems and collaborates with industry partners like IBM, Stellar, and Facebook. His work bridges academia and industry, addressing real-world scalability and security challenges. Labs & Teams: Leads the Distributed and Networked Systems Group, contributing to Surrey's Cyber Security Centre. Active in collaborative frameworks like CoMiFin for financial infrastructure protection.

• Knowledge Graph Construction & Curation
• Neural-Symbolic Reasoning
• Large Language Models (LLMs)
• +۴ مورد دیگر

Dr. Jiaoyan Chen is a Lecturer (teaching & research) in the Department of Computer Science at The University of Manchester, transitioning to Senior Lecturer (Associate Professor) in July 2025. Previously, she was a Senior Researcher at the University of Oxford (2017-2022) and held visiting roles at Zurich University and Heidelberg University. She holds a PhD and BEng in Computer Science from Zhejiang University. Her research focuses on neural-symbolic systems, integrating knowledge graphs/ontologies with large language models and machine learning. Key areas include knowledge graph construction/curation, ontology embeddings, and data-intensive systems. She leads EPSRC-funded projects like 'OntoEm' (427.9K GBP) and collaborates on initiatives such as the Manchester-Melbourne-Toronto AI for Child Protection project. Teaching responsibilities include units like 'Data Engineering Technologies' and 'Advanced Topics in Knowledge Representation.' She actively supervises 9 PhD/postdoc researchers across topics like knowledge-aware AI and semantic search. Professional services include associate editor roles at Transactions on Graph Data and Knowledge and membership in the EPSRC Peer Review College. Her software contributions include OWL2Vec* (ontology embedding framework) and DeepOnto (ontology engineering toolkit). Recent achievements include ACL 2025 acceptances and an IEEE TKDE survey paper on ontology embeddings.

• Categorical Probability
• Programming Languages
• Formal Methods
• +۵ مورد دیگر

Elena Di Lavore is a Research Associate at the University of Oxford's Department of Computer Science, working with Sam Staton. Previously, she held postdoctoral positions at the University of Pisa and completed her PhD at Tallinn University of Technology under Paweł Sobociński. Her research focuses on categorical probability, formal methods, quantum computing, and compositional systems. She has contributed to areas such as Mealy machines, program logics, and explainable AI. Education: BSc in Mathematical Engineering (Politecnico di Milano), BSc in Mathematics (Università di Pisa), MSc in Mathematics and Foundations of Computer Science (University of Oxford), PhD in Compositional Systems and Methods (Tallinn University of Technology). Research interests include categorical foundations for AI, quantum bisimulation, and monoidal width. She has received the Kleene Award and Distinguished Paper Award at LiCS 2022. Her work bridges category theory with practical applications in programming languages and systems. Awards: Kleene Award (2022), Distinguished Paper (LiCS 2022) Service: Program committee member for MFPS 2025, ACT 2025, and steering committee of the Adjoint School. Labs/Teams: Compositional Systems and Methods group (Tallinn University of Technology), collaboration with Sam Staton's Oxford team.

Emanuele D’Osualdoمشاهده پروفایل

استاد

• Formal Methods
• Programming Languages
• Verification
• +۶ مورد دیگر

Emanuele D’Osualdo is a Tenure-track Professor of Formal Methods for Software Engineering at the University of Konstanz. Previously, he held postdoctoral positions at MPI-SWS Saarbrücken (2020-2024) under Derek Dreyer and at Imperial College London (2015-2020) as a Marie Curie Fellow under Prof. P. Gardner. His research focuses on formal methods for software verification, including static analysis, model checking, and compositional verification techniques for concurrent and probabilistic systems. Research interests span Programming Languages, Verification, Security, Concurrency Theory, and Probabilistic Programming. Notable contributions include the Soter tool for Erlang verification, the James Bound library for π-calculus analysis, and foundational work on hierarchical communication topologies. His 2016 doctoral thesis on concurrency verification earned the CPHC/BCS Distinguished Dissertation Award. Recent work includes Bluebell (POPL 2025), advancing probabilistic reasoning via relational lifting, and compositional approaches to hypersafety (OOPSLA 2022). Active in academic service, he has delivered keynotes at HYPER’25 and participates in major conferences like CAV and POPL. Awards: 2016 CPHC/BCS Distinguished Dissertation Award Tools: Soter (Erlang verifier), James Bound (π-calculus library) Grants/Advising: Supervises graduate students at University of Konstanz (details forthcoming) Led the Formal Methods research group focused on concurrency, security, and probabilistic systems at the University of Konstanz.

• Real-Time Systems
• Embedded Systems
• Worst-Case Execution Time (WCET) Analysis
• +۵ مورد دیگر

Overview Peter Puschner is a full Professor at the Faculty of Informatics at TU Wien, specializing in Computer Engineering and Real-Time Systems. He serves as Faculty Representative for Research and Infrastructure, overseeing strategic initiatives in informatics research and infrastructure development. His academic role also includes leading the Service Unit Infrastructure (E199-02) and heading the Cyber-Physical Systems department (E191-01). Education and Roles Puschner holds a Diplom-Ingenieur (Dipl.-Ing.) and a Dr.techn. from TU Wien, alongside the title Ao.Univ.Prof. His roles include teaching and supervising students in advanced topics such as Operating Systems, Real-Time Systems, and Scientific Research methodologies. He has been actively involved in curriculum design for Computer Science and Business Informatics programs. Research Interests His research focuses on: Timing Analysis: WCET analysis for real-time systems, especially in multi-core and mixed-criticality environments. Embedded Systems: Designing time-predictable architectures for safety-critical applications. Communication Networks: Time-triggered protocols for automotive and industrial systems. Publications and Tools Puschner has authored over 160 publications, including seminal work on the Platin WCET analysis tool and the T-CREST multi-core architecture. His recent work emphasizes compiler-driven timing predictability and dual-path code paradigms. Grants and Awards Recipient of the Marie-Curie Fellowship (2003) and a founding member of the IFIP 10.2 WG on Embedded Systems. His projects have been funded by the EU (e.g., T-CREST, Multicores Partitioning), FWF, and industry collaborations. Students and Supervision He has supervised numerous PhD and Master’s students, including Elias Maroun (2024), Matthias Platzer (2022), and Bledar Cilku (2018). Key topics include WCET analysis, memory hierarchy design, and secure communication protocols. Labs and Teams Puschner leads the Real-Time Systems Lab, collaborating with industry partners (e.g., automotive, aerospace) to develop safety-critical embedded systems. His team contributes to open-source tools like Platin and the Patmos processor.