جست‌وجوی استاد و پژوهشگر

• Technology-Enhanced Learning
• Accessibility & Universal Design
• Assistive Technology
• +۷ مورد دیگر

Charalampos Karagiannidis is a Professor at the University of Thessaly (UTH) in the School of Educational Design (SED), Department of Information and Communication Technologies in Learning and Special Education. He has been affiliated with UTH since 2005 and previously worked at the University of the Aegean, ITI-CERTH, and ICS-FORTH. His academic roles include chairing the TeDISABLE Special Interest Group (SIG) of the IEEE TCLT. Education: BSc in Mathematics, Aristotle University of Thessaloniki MSc in Information Technology, University of London PhD in Electronics Engineering, University of Kent, UK Research Focus: Technology-Enhanced Learning (TEL) Accessibility & Universal Design Assistive Technologies for Special Needs Augmented Reality (AR) and Gamification in Education Educational Robotics for Inclusion Cognitive Assessment Technologies for Aging Populations Publications Trends: Recent work emphasizes ICT applications for autism spectrum disorders (ASD), inclusive robotics, MOOC design for K-12 education, and digital tools to address mild cognitive impairment. His research often bridges theoretical learning models with practical software development, particularly for marginalized populations. Awards & Recognition: No explicit awards listed, but active participation in 150+ publications, editorial roles, and international conference committees demonstrates peer recognition. Grants & Labs: Involved in projects like the TeDISABLE SIG and development of tools such as the Virtual Learning and Social Stories for Autism (VLSS) system . Collaborates on EU-funded initiatives addressing aging populations and cognitive assessment via digital tools.

Pierpaolo Vivoمشاهده پروفایل

استاد

• Random Matrix Theory
• Statistical Mechanics
• Complexity Science
• +۳ مورد دیگر

Pierpaolo Vivo is a Reader in Disordered Systems at King's College London's Department of Mathematics, part of the Faculty of Natural, Mathematical & Engineering Sciences. He holds a PhD from Brunel University (2008) and conducted postdoctoral research at ICTP Trieste and LPTMS Orsay. His research focuses on Random Matrix Theory, Statistical Mechanics applied to socio-economic systems, and complexity science in legal frameworks. Key research interests include eigenvalue statistics, financial stability modeling, and legal system complexity. His work bridges physics, economics, and law, with recent projects exploring phase transitions in debt recycling and network-based legal visualization tools like Graphie. Major achievements include a UKRI Future Leaders Fellowship (2019) and over 50 peer-reviewed publications. He leads projects on legal system modeling and collaborates internationally on interdisciplinary topics.

Glen Chouمشاهده پروفایل

استادیار

• Robotics
• Trustworthy Autonomy
• Machine Learning
• +۴ مورد دیگر

Glen Chou is an Assistant Professor in the Department of Electrical and Computer Engineering at Georgia Tech. He holds dual B.S. degrees from UC Berkeley (Electrical Engineering & Computer Science and Mechanical Engineering) and M.S./Ph.D. degrees from the University of Michigan (Electrical & Computer Engineering). Prior to Georgia Tech, he was a postdoctoral researcher at MIT CSAIL. Chou directs the Trustworthy Robotics Lab, focusing on algorithms for general-purpose robots and autonomous systems to ensure capability, safety, and resilience in real-world conditions. His research integrates control theory, machine learning, optimization, and formal methods. He emphasizes both theoretical foundations (e.g., proving algorithmic properties) and practical deployment on real robots. Key research areas include trustworthy autonomy, human-robot interaction, and constraint learning from demonstrations. His lab addresses challenges in perception, motion planning, and system reliability through interdisciplinary approaches. Chou has received notable awards including the Robotics: Science & Systems Pioneer (2022), NDSEG Fellowship (2019), and NSF Graduate Fellowship (2019). His work bridges foundational theory with real-world applications, with a focus on safety-critical systems.

Marina Knittelمشاهده پروفایل

استادیار

• Graph Algorithms
• Fair Machine Learning
• Mechanism Design
• +۳ مورد دیگر

Marina Knittel is an Assistant Professor of Computer Science at Reed College in the Division of Mathematical and Natural Sciences, starting Spring 2025. She currently serves as a postdoctoral researcher at UC San Diego working with Profs. Barna Saha and Sanjoy Dasgupta on graph algorithms. She holds a PhD from the University of Maryland (2023) and a BS in Mathematics and Computer Science from Harvey Mudd College. Her research focuses on graph algorithm theory with applications spanning fairness in machine learning, mechanism design, and massively parallel computation. She explores interdisciplinary connections between computer science, economics, and biology, particularly how computational problems increasingly require cross-domain expertise. Knittel's publication portfolio demonstrates consistent focus on scalable algorithms for massive datasets, with recent work emphasizing fairness in clustering and hierarchical methods. Her articles frequently appear in top theoretical computer science venues and show sophisticated mathematical approaches to practical computational problems.

Jean-Jacques Heringsمشاهده پروفایل

استاد

• Game Theory
• Microeconomics
• Networks
• +۴ مورد دیگر

Jean-Jacques Herings is a Full Professor of Quantitative Microeconomics at Tilburg University's Tilburg School of Economics and Management (TiSEM), specifically within the Department of Econometrics and Operations Research. He has held this position since March 2022, having previously been a Professor of Economics at Maastricht University from September 1999 to February 2022. Herings' research focuses on five primary themes: Cooperative game theory, non-cooperative game theory, networks, general equilibrium theory, and equilibrium computation. His work spans theoretical foundations and practical applications, particularly in financial networks, matching markets, and strategic decision-making. He has published over 200 research outputs including articles in top journals such as Econometrica, Journal of Economic Theory, Management Science, and Mathematics of Operations Research. His recent publications reveal a continued focus on game-theoretic applications to economic problems, with particular attention to financial networks, bankruptcy problems, matching theory, and information design. There's a clear trend toward computational methods for finding equilibria and increasingly sophisticated modeling of strategic interactions in networked environments, with over 13 publications in 2024 alone demonstrating his active research program. Johannes Cornelis Ruigrok Prize (1997) Lionel W. McKenzie Prize (2008) VICI grant from NWO Fellow of the Game Theory Society (2017) Secretary-Treasurer of Game Theory Society (2014-2022) Fellow of the Society for the Advancement of Economic Theory (2019) As an advisor, Herings has supervised over 20 PhD students to completion, with research spanning game theory applications in economics, finance, and network theory. His editorial service includes membership on the boards of Games and Economic Behavior, Journal of Mathematical Economics, International Journal of Game Theory, and Mathematics of Operations Research. He also serves on the International Advisory Board of the Center for Mathematical Research in Economics and Finance at the University of Manchester.

Shahin Shahrampourمشاهده پروفایل

استادیار

• Machine Learning
• Optimization and Control
• Distributed Learning
• +۵ مورد دیگر

Shahin Shahrampour is an Assistant Professor in the Department of Mechanical & Industrial Engineering at Northeastern University, with a courtesy appointment in Electrical & Computer Engineering. He holds a Ph.D. in Electrical & Systems Engineering from the University of Pennsylvania, an M.A. in Statistics from The Wharton School, and a B.S. in Electrical Engineering from Sharif University of Technology. Prior to Northeastern, he was at Texas A&M University and held a postdoctoral fellowship at Harvard University. Research Interests: Machine learning, optimization and control, distributed and sequential learning, with a focus on computationally efficient methods for data analytics. Specific areas include manifold optimization, online and reinforcement learning, non-convex optimization, and statistical signal processing. His work bridges theory and applications in networked systems and dynamic environments. Awards & Grants: Received a $500,000 NSF grant (2023) for distributed optimization in non-convex environments. Best Paper Award at IEEE ICASSP 2022 for contributions to signal processing. TEES Engineering Genesis Award (2020) for multidisciplinary research at Texas A&M. Principal Investigator on NSF-funded projects in collaborative online optimization and decentralized learning. Labs & Teams: Leads research in machine learning and control systems at Northeastern University, focusing on interdisciplinary challenges in distributed optimization and real-time learning. His lab emphasizes theoretical foundations and practical implementations in networked and dynamic systems.

Petter Holmeمشاهده پروفایل

استاد

• Network Science
• Complex Systems
• Computational Social Science
• +۳ مورد دیگر

Petter Holme is a Professor at the Department of Computer Science, Aalto University, specializing in network science and complex systems. His research focuses on understanding interconnected systems through network analysis, including topics like epidemic spreading, climate change interactions, and power grid synchronization. He holds a Doctoral degree in Natural Sciences from Umeå University (2004) and has received the prestigious Fellow of the Network Science Society (2024). His work is interdisciplinary, collaborating with social scientists, medical researchers, and engineers. Key areas include temporal networks, computational social science, and data-driven modeling. Education: PhD in Natural Sciences (Umeå University, 2004), Licentiate in Natural Sciences (Umeå University, 2001), Master's in Engineering (Uppsala University, 2000), and Master's in Humanities (Stockholm University, 2000). Research interests span network structure analysis, epidemic models, and social dynamics, with contributions to UN Sustainable Development Goals. He has authored over 116 publications and frequently engages with media on topics like Paxlovid's public health impact and climate change networks.

Yan Liمشاهده پروفایل

استادیار

• Dynamic Optimization
• Robust Optimization
• Stochastic Optimization
• +۵ مورد دیگر

Dr. Yan Li is an Assistant Professor in the Department of Industrial and Systems Engineering at Texas A&M University. He earned his Ph.D. in Operations Research from Georgia Institute of Technology (2024), advised by George Lan and co-advised by Tuo Zhao, with collaborations involving Anton Kleywegt and Alexander Shapiro. His research focuses on the computational perspective of learning optimal decisions from data, emphasizing first-order methods and their applications in data science. B.S. in Mathematics and Applied Mathematics & B.B.A. in Accounting, Nankai University (2016) M.S. in Statistics, Georgia Institute of Technology (2018) Ph.D. in Operations Research, Georgia Institute of Technology (2024) Dr. Li’s research interests span dynamic optimization (Markov decision processes, reinforcement learning), robust/risk-averse optimization, minimax optimization, and optimization for machine learning. His work addresses computation- and sample-efficient algorithms, distributional ambiguity in dynamic optimization, and gradient-based methods for ML applications. Industry collaborations include Meta (ads ranking optimization) and Bytedance (deep retrieval models), with ongoing projects in urban transportation and recommendation systems. His publications include 15 recent articles on policy optimization, stochastic minimax methods, and implicit regularization in reinforcement learning. Awards include the Alice and John Jarvis Ph.D. Student Research Award, The Margaret and Stephen Kendrick Research Excellence Award, and the ISyE Outstanding Graduate Student Instructor Award. Teaching accolades highlight his clarity, passion, and accessibility in courses like ISEN 310 (Uncertainty Modeling) and ISEN 320 (Operations Research I). Peer reviewer for journals like Mathematical Programming and conferences including ICML and NeurIPS Industry partnerships with Ford (multi-agent RL) and Meta (embedding learning) Active in optimization communities (INFORMS, MOPTA)

Mark McMahonمشاهده پروفایل

استاد

• Educational Technology
• Game-Based Learning
• Digital Literacy
• +۴ مورد دیگر

Professor Mark McMahon is a Professor of Games and Interactive Design and Director, International and Strategic, at the School of Arts and Humanities, Edith Cowan University (ECU). He holds a PhD from ECU (2005), a Master of Education (1998), and a Bachelor of Arts from The University of Western Australia (1991). His work bridges educational technology, game-based learning, and digital literacy, with a focus on serious games, problem-based learning frameworks, and cognitive assessment tools. Education: Doctor of Philosophy, Edith Cowan University, 2005 Master of Education, Edith Cowan University, 1998 Bachelor of Arts, The University of Western Australia, 1991 Research Interests: Professor McMahon’s research spans game-based learning, digital literacy, and simulation-based training. He develops tools like the eFun App to measure executive functions in students and explores immersive 3D environments for spatial cognition. His work emphasizes applying technology to enhance learning outcomes and self-regulation, with a focus on problem-based pedagogy and serious games design. Advising & Grants: Current supervisions include projects on schema complexity in problem-solving and creative media education. Completed supervisions cover topics like 3D gaming for submarine training and data visualization aesthetics. Funded projects include studies on executive functions in children and algorithmic employee matching, totaling over $500k in grants. Labs & Teams: His research involves collaborations with industry partners like CingleVue and AusIndustry, focusing on innovative educational tools and assessment systems. He leads initiatives to integrate digital literacy into curricula and supports multidisciplinary teams in project management and skill development.

• Machine Learning
• Online Learning
• Algorithmic Game Theory
• +۴ مورد دیگر

Andrea Celli is an Assistant Professor in the Department of Computing Sciences at Bocconi University. He is affiliated with the ELLIS Society and the Bocconi Institute for Data Science and Analytics. Previously, he was a postdoctoral researcher at Meta (formerly Facebook Research) in London. He holds a Ph.D. in Computer Science from Politecnico di Milano and conducted research at Carnegie Mellon University's Electronic Marketplaces Lab. His research focuses on intersections of computer science, machine learning, and economics, particularly in strategic interactions and online learning environments. Notable achievements include a NeurIPS 2020 Best Paper Award and the 2017 Lesmo Prize for his MSc thesis. His research is supported by grants including an ERC Starting Grant (2024) for the PLA-STEER project and an MUR-PRIN grant (2022). He teaches courses such as Deep Learning and Reinforcement Learning, Machine Learning, and Optimization at the Ph.D. level. His work spans topics like equilibrium finding, online learning under constraints, and mechanism design. Key publications include contributions to ICLR, NeurIPS, EC, and other top venues. Celli advises Master’s students including Annalisa Barbara, Emanuele Coccia, Davide Drago, and Antonio Preiti. He collaborates with postdocs like Riccardo Poiani and Martino Bernasconi. He actively organizes academic events, such as the EC 2025 workshop on Online Learning and Economics. His research emphasizes theoretical foundations while addressing practical challenges in algorithmic game theory and data-driven decision-making.

Zhang Yanمشاهده پروفایل

استاد

• Internet of Vehicles
• Smart grid
• Mobile edge computing
• +۴ مورد دیگر

Zhang Yan is a Full Professor at the Department of Informatics, University of Oslo, Norway. He previously served as Head of Department and Chief Scientist at Simula Research Laboratory (2014–2016). His research focuses on advanced communication technologies including Internet of Things (IoT), 5G/6G networks, mobile edge computing, and blockchain applications. He has held significant roles such as IEEE VTS Distinguished Lecturer (2016–2020) and Chair of IEEE TCGCC (2019–2021). His honors include IEEE Fellow (2020), election to Academia Europaea (2020), and recognition as a Web of Science Highly Cited Researcher (2018–2019). Research interests span interdisciplinary areas like network dynamics, socio-economic systems, and algorithmic design. His work bridges theoretical foundations with practical applications in smart grids, vehicular networks, and global trade systems. Recent publications emphasize network science methodologies applied to economic complexity and information diffusion. Professional contributions include editorial roles for top journals and leadership in EU-funded projects. His awards reflect impactful contributions to both technical innovation and scientific leadership in informatics and communications.

Sven Scheweمشاهده پروفایل

استاد

• Automata Theory
• Game Theory
• Formal Verification
• +۱۲ مورد دیگر

Sven Schewe is a Professor in the Department of Computer Science at the University of Liverpool, affiliated with the School of Electrical Engineering, Electronics and Computer Science. He leads the AI Section and is a founding member and former leader of the Verification Group. He also has secondary affiliations with the Algorithms, Complexity Theory and Optimisation Group and the Institute for Risk and Uncertainty. Research Interests: His research centers on automata theory and game theory, particularly their applications in the verification and synthesis of reactive and safety-critical systems. He investigates infinite-duration games, automata over infinite words and trees, and develops algorithms and tools for automated verification, synthesis, and learning of optimal control strategies. His work extends to reinforcement learning with formal guarantees, cyber-physical systems, and AI safety. Recent Research Trends: His recent publications demonstrate a strong integration of formal methods with machine learning, particularly in adversarial training, neural network robustness, and model-free reinforcement learning under omega-regular objectives. He also applies formal reasoning to interdisciplinary domains such as chemical space exploration and materials science. Scientific Awards: Finalist for the ERCIM Cor Baayen Award 2010 Dr. Eduard Martin Preis 2009 GI Dissertation Award 2008 Advising and Grants: He actively supervises numerous PhD students and postdoctoral researchers. He is Principal Investigator (PI) or Co-Investigator (CI) on multiple major grants, including EPSRC Programme Grants, Royal Society Fellowships, and Horizon Europe projects. His funded research spans topics such as game theory, verification, synthesis, reinforcement learning, and risk analysis. He has hosted visiting researchers and collaborated internationally with institutions in Germany, France, India, Taiwan, and the US. Labs and Teams: He co-founded and led the Verification Group and previously led the AI Section at the University of Liverpool. These groups focus on formal methods, automata, games, and their applications in AI and safety-critical systems.

• Resource Optimization
• Telecommunication Networks
• VLSI Circuit Design
• +۵ مورد دیگر

Professor Arunabha Sen is a faculty member at Arizona State University (ASU), affiliated with the School of Computing and Augmented Intelligence and the College of Health Solutions as a Health Solutions Ambassador. He joined ASU in 1987 and holds a Ph.D. in Computer Science from the University of South Carolina (1987). His research focuses on resource optimization in telecommunication networks, VLSI circuits, hardware-software co-design, and network security. Key areas include algorithm design, combinatorial optimization, and network processor systems. His work spans wireless, optical, and sensor networks, with contributions to video transmission over mobile ad-hoc networks and interference-aware channel assignment. Notable projects include robust network design against WMD attacks and tools for resilient communication networks. He has served on multiple technical committees for conferences like IEEE and IFIP, and contributed to academic initiatives such as capstone courses on network processors. Grants include NSF, DOD-DTRA, and Motorola Labs funding, emphasizing interdisciplinary research in network science and communications. Teaching responsibilities include courses on algorithms, game theory, and network design. His service roles include Associate Editor for IEEE Transactions on Mobile Computing and leadership in graduate program committees. Research outputs include over 30 peer-reviewed publications, with recent work in algorithmic network design and social computing data mining.

• Mathematical Logic
• Proof Theory
• Set Theory
• +۵ مورد دیگر

Juan P. Aguilera is a researcher at the Institute of Discrete Mathematics and Geometry at TU Wien, Austria. His research focuses on mathematical logic, particularly in proof theory, set theory, reverse mathematics, and infinitary logics. He actively participates in academic events, including organizing workshops and giving invited talks globally. His research interests span foundational questions in logic, including Gödel logics, determinacy axioms, and structural reflection principles. He contributes to interdisciplinary areas such as the model theory of non-classical logics and applications of infinitary proof systems. Aguilera has been involved in major logic events like the Logic Colloquium 2025 (TU Wien) and co-organized the Philosophical Transactions of the Royal Society special issue on proof theory (2023). He has given talks at institutions like Ghent University, the University of Hamburg, and ITAM (Mexico City). No scientific awards are explicitly listed, but his prolific engagement in academic conferences and editorial work highlights his contributions to the field. He has secured grants and leads collaborative projects, though specific grant details are not provided. He is affiliated with TU Wien's discrete mathematics group and collaborates internationally on logic and set theory research.

• Wireless Communications
• Cognitive Radio
• Massive MIMO
• +۷ مورد دیگر

Professor Wei Zhang is a Full Professor at the School of Electrical Engineering & Telecommunications, University of New South Wales (UNSW), where he has been serving since May 2008, progressing from Senior Lecturer (2008-2012) to Associate Professor (2013-2017) and finally to Full Professor in November 2017. He received his PhD degree in Electronic Engineering from the Chinese University of Hong Kong in 2005 and was a Research Fellow at the Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology from 2006 to 2007. Professor Zhang's research spans cognitive radio, massive MIMO, 5G/6G networks, UAV communications, orbital angular momentum, and reconfigurable intelligent surfaces. His publications demonstrate a strong theoretical foundation combined with practical implementations, addressing critical challenges in modern wireless systems including spectrum efficiency, secure communications, and network intelligence. With over 200 papers in IEEE journals and conferences along with three authored books, his work has significantly impacted the field of wireless communications. Analysis of his recent publications (2023-2025) reveals a clear trajectory toward next-generation wireless technologies with emphasis on reconfigurable intelligent surfaces (RIS), orbital angular momentum (OAM), non-orthogonal multiple access (NOMA), and the integration of machine learning with traditional communication techniques. A substantial portion of his current work focuses on satellite-terrestrial integrated networks, UAV communications, and secure wireless transmission techniques, showing increasing sophistication in addressing complex communication challenges through innovative approaches. Professor Zhang's scientific achievements have been recognized with prestigious honors including: Fellow of the IEEE Fellow of the IET Distinguished Lecturer of IEEE Communications Society (2016-2017) His leadership in the academic community is evident through his editorial roles as Editor-in-Chief of IEEE Wireless Communications Letters (2016-2019) and currently as Editor-in-Chief of Journal of Communications and Information Networks (JCIN). As Area Editor of IEEE Transactions on Wireless Communications and former editor for multiple IEEE Transactions journals, he has significantly influenced the direction of wireless communications research. His active participation in major IEEE conferences as TPC Chair and Co-Chair demonstrates his commitment to advancing the field through scholarly exchange. Currently serving as Chair of IEEE Wireless Communications Technical Committee and Vice Director of IEEE Communications Society Asia Pacific Board, Professor Zhang continues to shape the future of wireless communications research globally, bridging the gap between academic innovation and industry implementation in next-generation wireless networks.