جستجوی استاد راهنمای دانشگاهی

Jiatao Guمشاهده پروفایل

استادیار

• Machine Learning
• Generative Models
• 3D Generation
• +۳ مورد دیگر

Jiatao Gu is an Assistant Professor in the Department of Computer and Information Science (CIS) at the University of Pennsylvania, with a part-time role as Staff Research Scientist at Apple (MLR). He holds a Ph.D. in Electrical and Electronic Engineering from the University of Hong Kong (2018) and a B.Eng. in Electronic Engineering from Tsinghua University (2014). His research focuses on generative machine learning and AI agent interaction with the physical world, emphasizing multi-modal systems spanning language, images, videos, and 3D. Key themes include efficient modeling , flexible architecture design , and scalable decision-making frameworks . 2025: ICLR paper on DART framework 2024: TMLR work on GFlowNet alignment 2023: NeurIPS research on diffusion stability 2022: ACL papers on speech translation Recent publications explore diffusion models for text-to-image synthesis, 3D reconstruction, and efficient sampling techniques. His work addresses fundamental challenges in attention mechanisms, entropy collapse, and multi-stage distillation while advancing non-autoregressive translation and vision-language reasoning . Prospective students can apply through his recruitment process at UPenn. Prior affiliations include Meta AI (FAIR Labs) and academic collaborations with institutions like New York University's CILVR Lab.

Simon Buckingham Shumمشاهده پروفایل

استاد

• Human-Computer Interaction
• Educational Technology
• Learning Analytics
• +۵ مورد دیگر

Professor Simon Buckingham Shum is a leading academic in Learning Informatics at the University of Technology Sydney (UTS), serving as inaugural Director of the Connected Intelligence Centre since 2014. His work bridges Human-Computer Interaction, Educational Technology, and Learning Analytics to develop AI-driven tools like OnTask that enhance student belonging through personalized feedback. Key research areas: Human-Computer Interaction, Learning Analytics, AI in Education, Collective Intelligence Recent work focuses: LLM-augmented qualitative analysis, Belonging Analytics frameworks, and ethical AI implementation in education CIC received the 2024 Vice-Chancellor’s Student Experience Award for scaling OnTask across multiple faculties. His contributions span over 30 years, including founding roles at The Open University’s Knowledge Media Institute and innovations in Open Educational Resources (OER), SocialLearn, and FutureLearn platforms. Notable awards: 2024 Student Experience Award (OnTask), Fellow of the Royal Society of Arts (RSA), DEFI STRI Researcher at University of Cambridge Education: B.Sc. in Psychology (York), M.Sc. in Ergonomics (UCL), PhD in Human-Computer Interaction (York) He leads multidisciplinary collaborations with teams across Business, Law, and Education faculties, pioneering tools like Theme Explorer and Qreframer bot. His recent focus on the "metacrisis" reframes educational technology’s role in addressing global systemic challenges through transdisciplinary approaches.

Raquel Fernándezمشاهده پروفایل

استاد

• Computational Linguistics
• Dialogue Systems
• Cognitive Science
• +۳ مورد دیگر

Raquel Fernández is Full Professor of Computational Linguistics and Dialogue Systems at the University of Amsterdam, where she leads the Dialogue Modelling Group at the Institute for Logic, Language & Computation (ILLC). As Vice-Director for Research at ILLC and a Fellow of the ELLIS Society, she bridges computational linguistics, cognitive science, and artificial intelligence through her research on language use in multimodal and conversational contexts. PhD in Computational Linguistics from King's College London Prior research positions at University of Potsdam and Stanford University's CSLI Her work explores how cognitive constraints, social interaction, and perception shape language use, with a focus on: Visually-grounded language processing Multimodal dialogue modeling Model uncertainty and calibration Language grounding in multimodal data Language learning and semantic change Dialogue reference resolution Recent publications analyze multimodal reasoning limitations, cross-lingual knowledge consistency, and uncertainty modeling in dialogue systems. She has received multiple accolades including an ERC Consolidator Grant , NWO VENI/VIDI/Aspasia fellowships , and EMNLP/GenBench awards . Outstanding Paper Award (EMNLP 2023) Best Data Award (GenBench Workshop 2023) ELLIS Society Fellow ERC Consolidator Grant #819455 recipient NWO VENI/VIDI/Aspasia awardee As a leader in academic service, she serves on the SIGDAT Executive Committee and chairs multiple conference committees. Her lab develops models for multimodal dialogue, visual storytelling, and grounded language understanding.

Sanjit A. Seshiaمشاهده پروفایل

استاد

• Formal Methods
• Cyber-Physical Systems
• Computer Security
• +۱۰ مورد دیگر

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.

Josef Urbanمشاهده پروفایل

پژوهشگر

• Automated Reasoning
• Machine Learning
• Theorem Proving
• +۵ مورد دیگر

Josef Urban is a leading researcher at the Czech Institute of Informatics, Robotics and Cybernetics (CIIRC) , Czech Technical University in Prague, heading the ERC Consolidator project AI4REASON . Previously, he held positions as a postdoc at Radboud University Nijmegen and assistant professor at Charles University in Prague, where he co-founded the Prague Automated Reasoning Group. Education Ph.D. in Computer Science (2004), Charles University, Prague M.S. in Mathematics (1998), Charles University, Prague B.S. in Economics (1995), Charles University, Prague Research Interests Urban specializes in automated reasoning over large formalized knowledge bases, combining deductive theorem proving and inductive machine learning . His work aims to realize "strong AI" through formalized mathematics, particularly using systems like Mizar and the AI/TP Challenges . He advocates for computer-verifiable mathematics as a foundation for AI progress. Article Trends Urban's publications focus on integrating machine learning with automated theorem proving in systems like ENIGMA and BliStr . Key trends include semantic guidance for ATPs, premise selection in formal libraries, and automated proof compression via concept invention. Scientific Contributions Head of ERC Consolidator project AI4REASON Marie-Curie Fellow at University of Miami Co-founder of Prague Automated Reasoning Group Editor for Formalized Mathematics Advising and Grants Urban has advised numerous PhD and MSc students including Daniel Kuehlwein, Krystof Hoder, and Yutaka Nagashima. He has secured grants like the ERC Consolidator Grant and Marie-Curie Fellowship . Labs and Collaborations Urban leads the AI4REASON team at CIIRC and collaborates with the Foundations Group at Radboud University. He contributes to projects like Mizar TWiki and XML-based API for Mizar , aiming to create a semantic AI ecosystem for formal knowledge.

Wael B. Hallaqمشاهده پروفایل

استاد

• Islamic Law
• Islamic Intellectual History
• Modernity and Its Impact
• +۴ مورد دیگر

Wael B. Hallaq is the Avalon Foundation Professor in the Humanities at Columbia University’s Department of Middle Eastern, South Asian, and African Studies. His work focuses on Islamic law, intellectual history, and the socio-political impacts of modernity. He critiques Orientalist paradigms and explores the interplay between moral theory and legal history in Islamic traditions. His research spans structural dynamics of legal change in pre-modern law, moral theory’s role in Islamic legal history, and the critique of modern state sovereignty. His influential books include *The Impossible State* (2013), which earned Columbia University Press’s Distinguished Book Award, and *Shari‘a: Theory, Practice, Transformations* (2009). Education: No explicit educational details provided in text. His writings bridge legal theory, history, and political thought, challenging Eurocentric frameworks in Islamic studies. His analyses of pre-modern legal systems and modernity’s moral dilemmas have been translated into multiple languages, including Arabic, Hebrew, and Persian. Awards: Columbia University Press Distinguished Book Award (2013–2015) No grants, labs, or advising details explicitly mentioned in the text.

• Artificial Intelligence
• Computer Security
• Multi-Agent Systems
• +۳ مورد دیگر

Dr. Chunyan Mu serves as a Senior Lecturer in the School of Natural and Computing Sciences at the University of Aberdeen, actively contributing to both academic instruction and cutting-edge research in computing science while currently accepting new PhD students. Her research program centers on Trustworthy AI and Safe Autonomy, with specialized expertise in formal verification of responsibility, accountability, and privacy mechanisms within multi-agent systems. She investigates resilience frameworks for autonomous intelligent systems and develops advanced methodologies for information flow security analysis, bridging theoretical computer science with practical security implementations. Analysis of her publication trajectory (2014-2025) reveals consistent innovation in applying formal methods to security-critical systems. Key thematic developments include probabilistic strategy logic for observability analysis, quantitative verification of opacity properties, and game-theoretic approaches to security verification, demonstrating increasing sophistication in handling multi-agent accountability and system resilience challenges. Dr. Mu currently supervises PhD candidates and offers a fully funded doctoral position focused on formal verification of safety properties in autonomous systems, providing comprehensive financial support including tuition coverage, £20,780 annual stipend, and dedicated research funding for candidates with strong backgrounds in formal methods and artificial intelligence.

Begona Dominguezمشاهده پروفایل

استاد

• Macroeconomics
• Monetary Economics
• Public Finance
• +۳ مورد دیگر

Professor Begona Dominguez is a faculty member in the School of Economics at The University of Queensland (UQ), within the Faculty of Business, Economics and Law. She holds a Doctor of Philosophy in Economics from Universitat Autònoma de Barcelona. Her research focuses on Macroeconomics, Public Finance, and Monetary Economics, with emphasis on fiscal policy design, central bank balance sheets, and optimal taxation frameworks. Her key projects include Supporting Entry and Growth of Australian Businesses via Tax and Transfers (2022–2024) and The role of a central bank's balance sheet in shaping the economy (2021–2024) . She is available for PhD supervision and actively contributes to applied macroeconomic analysis, particularly in urban economic advantages and policy evaluation. Publications span topics like fiscal sustainability, inflation dynamics under central bank policies, and the implications of constitutional constraints on taxation. Her work bridges theoretical models (e.g., Ramsey frameworks) with empirical applications in tax policy and public debt management. Professor Dominguez maintains affiliations with the Centre for Applied Macroeconomic Analysis (ANU) and has reviewed prominent texts such as John Taylor's Reform of the International Monetary System . She is based in Room 507, Colin Clark Building at UQ.

Cezary Kaliszykمشاهده پروفایل

استاد

• Automated Reasoning
• Formal Methods
• Formalized Mathematics
• +۷ مورد دیگر

Cezary Kaliszyk is a Professor in Theoretical Computer Science at the University of Melbourne, previously affiliated with the University of Innsbruck. He is actively involved in research and leadership in formal methods, automated reasoning, and machine learning for theorem proving. Research Interests: Automated Reasoning and Interactive Theorem Proving Formalized Mathematics and Proof Automation Machine Learning for Logic and Theorem Proving Integration of AI with Proof Assistants (Coq, Isabelle) Dependent Type Theory and Higher-Order Logic His recent publications (2023–2025) span topics in dependently-typed logic, learning for proof guidance, formalization of surreal numbers, and blockchain-based formal methods. The works consistently bridge formal logic with machine learning, emphasizing automation, explainability, and cross-system integration. Scientific Leadership and Projects: Principal Investigator, ERC project FormalWeb3 Lead Developer, CoqHammer , Tactician , ProofWeb WG5 Leader, COST Action EuroProofNet (until 2024) Contributor to HOL(y)Hammer , Isabelle Enigma He supervises multiple PhD students and has mentored several graduates in formal methods and AI. He teaches courses in theoretical computer science, logic, and machine learning. There are no listed awards in the provided data, but his extensive publication record and project leadership indicate significant recognition in the field. Labs and Research Groups: He leads a research group focused on formal methods and learning-based reasoning, collaborating internationally on projects involving proof automation, formal libraries, and semantic technologies.

Liangming Panمشاهده پروفایل

استادیار

• Natural Language Processing
• Large Language Models
• Machine Learning
• +۳ مورد دیگر

Liangming Pan is an Assistant Professor at the University of Arizona's College of Information Science. His research focuses on building trustworthy large language models (LLMs) with an emphasis on logical reasoning, truthfulness, and safety. He holds a PhD in Computer Science from the National University of Singapore (2022), a Master's from Tsinghua University, and a Bachelor's from Beihang University. Education : PhD in Computer Science, National University of Singapore (2022) Master of Engineering in Computer Science, Tsinghua University (2017) Bachelor of Engineering in Computer Science, Beihang University (2014) Research Interests : Dr. Pan's work centers on enhancing LLMs' reliability through: Logical reasoning mechanisms to ensure faithful deductions Truthfulness verification to combat misinformation Safety protocols to mitigate societal harm Key Contributions : Developed TART, an open-source framework for explainable table-based reasoning Created benchmarks like SCITAB and FactCheck-Bench for evaluating LLMs Advanced techniques for knowledge editing and causal reasoning Awards : Best Paper Runner-Up at NeurIPS Table Representation Workshop (2024) Area Chair Award for Question Answering (IJCNLP-AACL 2023) Service & Outreach : He serves as an Area Chair for EMNLP (2024), COLING (2025), and ACL (2024). He has delivered invited talks at Tsinghua University, Peking University, and other institutions.

Dino Pedreschiمشاهده پروفایل

استاد

• Big Data Analytics
• Social Network Analysis and Mining
• Analysis of Human Mobility
• +۱۷ مورد دیگر

Dino Pedreschi is a Full Professor of Computer Science at the University of Pisa, affiliated with the Department of Computer Science (DI-UNIPI). He co-leads the Pisa KDD Lab, a joint research initiative between the University of Pisa and the Italian National Research Council’s Institute of Information Science and Technology, one of the earliest labs focused on data mining and knowledge discovery. His research spans Big Data Analytics , Social Network Analysis , Human Mobility Analysis , Privacy-by-Design , Explainable AI (XAI) , and ethical data mining . He is a pioneer in privacy-preserving data mining and has contributed significantly to understanding societal impacts of AI and big data. Recent publications highlight trends in explainable AI , fairness-aware data mining , urban mobility modeling , and socio-economic nowcasting , reflecting a strong interdisciplinary focus combining computer science, social science, and policy. Notable scientific awards include: Google Research Award on Privacy (2009) University of Pisa Ordine del Cherubino (2017) Pedreschi has played leadership roles in major conferences such as ECML/PKDD (Co-Chair 2004), ICDM (Vice-Chair 2005), and ICDE (Vice-Chair 2014). He founded the Business Informatics MSc program at the University of Pisa to train interdisciplinary data scientists. He has been a visiting scientist at the University of Texas at Austin, CWI Amsterdam, UCLA, and the Barabási Lab at Northeastern University. He actively contributes to European research initiatives including SoBigData++, FAIR, and TAILOR, and has advised on AI policy, including testimony before the Italian Parliament on AI and labor markets. He is a key member of the Pisa KDD Lab, a leading research group in data science and AI ethics, fostering collaboration between academia and public institutions.

• Programming Languages
• Formal Methods
• Software Engineering
• +۴ مورد دیگر

Alexander Summers is an Associate Professor at the Department of Computer Science , University of British Columbia . He joined UBC in March 2020 after serving as a Senior Researcher (Oberassistent) at ETH Zurich from 2014-2020. His research bridges Programming Languages , Formal Methods , and Software Engineering , with a focus on automated verification tools for heap-based and concurrent programs. MSc Joint Mathematics and Computer Science, Imperial College London (2004) PhD Computer Science, Imperial College London (2009) Postdoc, ETH Zurich (2009-2014) Summers leads the Prusti Project , developing deductive verification tools for Rust, and contributes to the Viper Project for intermediate verification languages. His work addresses challenges in: Memory safety and concurrency verification Ownership models and aliasing control Automated reasoning with SMT solvers Resource-oriented programming specifications Debugging verification condition quantifiers Formal validation of verification infrastructure His research has been recognized with a Amazon Research Award and ACM SIGPLAN Distinguished Paper Awards . He teaches courses like Advanced Software Engineering and Program Verifiers and Program Verification , and supervises graduate students in formal verification and Rust-related research.

Amitabh Chandraمشاهده پروفایل

استاد

• Health Policy
• Public Policy
• Health Economics
• +۵ مورد دیگر

Amitabh Chandra is the Ethel Zimmerman Wiener Professor of Public Policy at Harvard Kennedy School (HKS) and the Henry and Allison McCance Family Professor of Business Administration at Harvard Business School (HBS). He holds dual roles as Director of Health Policy Research at HKS and chairs several initiatives, including the Pagliuca Harvard Life Lab and the joint MS/MBA program in life sciences. His research focuses on healthcare pricing, pharmaceutical innovation, racial disparities in care, and Alzheimer’s treatment economics. Dr. Chandra has advised the U.S. Congress, the Massachusetts government on healthcare reform, and serves on the Congressional Budget Office’s Health Advisors Panel. His affiliations include the Malcolm Wiener Center for Social Policy and the Mossavar-Rahmani Center for Business and Government at HKS. His research spans biopharmaceutical capital allocation, Medicare drug negotiation policies, and the economic implications of healthcare cost-sharing. Notable recent work addresses price regulation in healthcare, orphan drug exemptions, and the impact of the Inflation Reduction Act on pharmaceutical innovation. Key Awards: ASHE Medal (under 40), Kenneth Arrow Award, Eugene Garfield Award Committees: Blavatnik Fellows Board, Health Affairs Council on Spending Grants: NIH funding (NIA, NICHD), Robert Wood Johnson Foundation He explores how economic principles shape healthcare systems, focusing on aligning drug pricing with therapeutic value and improving equitable access to treatments. His work bridges academia and policy, influencing national dialogues on healthcare reform and innovation incentives.

Lance Ripsمشاهده پروفایل

استاد

• cognitive psychology
• reasoning
• concepts and categorization
• +۹ مورد دیگر

Lance Rips is a Professor in the Psychology Department at Northwestern University , Evanston, IL. His research focuses on cognitive psychology, particularly concepts, reasoning, and autobiographical memory. Academic Rank: Professor Institution: Northwestern University Department: Psychology Department Contact: ripslab@gmail.com , rips@northwestern.edu Research interests include: Deductive and inductive reasoning Concepts of objects/events over time Causal cognition Mathematical thinking (numbers, non-Euclidean geometry) Informal argumentation and survey methodology His lab investigates foundational questions in cognition, with recent work on conditional reasoning, object individuation, and developmental understanding of substances. Publications span journals like Cognitive Science , Psychological Science , and Cognition .

Giansalvatore Meccaمشاهده پروفایل

استاد

• Data Quality
• Data Analytics
• Data Integration
• +۷ مورد دیگر

Giansalvatore (Gianni) Mecca is a full professor at the Department of Mathematics, Computer Science and Economics at the University of Basilicata. Born in Potenza, he earned his Computer Engineering degree and PhD from Sapienza University of Rome under Prof. Paolo Atzeni. He joined the University of Basilicata in 1995, initially as a research associate and later as an associate professor. He has held visiting positions at the University of Toronto, Qatar Computing Research Institute, Arizona State University, and Roma Tre University. His research focuses on data quality, analytics, integration, and information extraction, alongside cooperative database systems. He teaches courses in computer programming, databases, and web development for Computer Science and Engineering programs. Key initiatives include the Diogene project, which innovates teaching methodologies in procedural programming and database systems, emphasizing layered instruction and dual-language (C++/FORTRAN) approaches. Diogene’s framework tools like pinco (Web MVC) and PdD (questionnaire generator) reflect his contributions to educational software. His work integrates practical coding examples with layered theoretical explanations, emphasizing algorithmic clarity and cross-language comparisons. Publications include methodological papers on educational systems and teaching practices, such as the 2006 Diogene Working Report on certification frameworks. His teaching materials span procedural programming, XML, and object-oriented design, distributed under Creative Commons licenses.