جست‌وجوی استاد و پژوهشگر

• Computing Education Research
• Educational Technology
• Large Language Models in Education
• +۳ مورد دیگر

Arto Hellas is a Senior Lecturer at the Department of Computer Science, University of Helsinki, where he leads the Lecturer Hellas Arto group. His work focuses on computing education research (CER) and educational technology, particularly leveraging large language models (LLMs) to enhance programming education and automated assessment tools. He also explores web development optimization through edge computing and serverless architectures. Research Interests: Hellas's research spans the integration of AI into education, programming pedagogy, and educational technology. He investigates how LLMs can generate feedback, analogies, and exercises for students, as well as their impact on MOOCs and classroom dynamics. His work addresses challenges in student performance analysis, synthetic data generation for educational purposes, and the ethical implications of AI in learning environments. His studies on web development emphasize distributed systems and edge computing applications to improve web service delivery. Scientific Awards: ICER 2022 Best Paper Award for work on LLM-generated programming exercises SIGCSE TS 2022 Best Paper Award in Computing Education Research UKICER 2023 Best Paper Award Advising & Grants: Hellas currently leads the CoCoAI: Human-Centered AI for Computer Science Education project (2025–2027), focusing on personalized learning through LLMs. He has supervised 2 theses but no student names were explicitly provided. His grants and projects highlight contributions to educational technology, including datasets like the IDE Action Log Dataset and Morning or Evening? circadian rhythm study. Labs & Teams: Active within the Lecturer Hellas Arto group, his collaborations span computing education, AI ethics, and web development. His team's work has been featured in media, such as a 2023 article discussing AI's role in developing a chess website in days.

Scott Boormanمشاهده پروفایل

استاد

• Comparative and Historical Sociology
• Economic Sociology
• Social Networks
• +۴ مورد دیگر

Scott A. Boorman is a Professor of Sociology at Yale University, known for integrating mathematical and computational methods into sociological inquiry. He holds a Ph.D. in Sociology from Harvard University (1973) and is a graduate of Yale Law School, with legal licensure in New York and Massachusetts. His research focuses on evolutionary biosociology, social network analysis, and complex statutory evolution, challenging traditional rational-choice models. Education: Ph.D. in Sociology, Harvard University (1973); Yale Law School Research interests include mathematical models of social structures, blockmodeling algorithms for social networks, and theoretical alternatives to rational-choice theory. His work bridges sociology with biology, law, and economics, exemplified by his studies of Maoist strategy, genetic altruism, and legislative evolution. Publications span disciplines, including foundational texts like The Protracted Game and influential articles in Proc. Nat. Acad. Sci. and Bell Journal of Economics . His 2000 Cowles Foundation paper outlines groundbreaking critiques of rational-choice paradigms. Affiliations include the Yale Institute for Network Science (YINS) and the Center for Historical Enquiry & The Social Sciences (CHESS). He teaches courses such as Analysis of Social Structure and Social Processes at the graduate level, emphasizing quantitative methods.

Seth Bernsteinمشاهده پروفایل

دانشیار

• Soviet History
• Post-Soviet Studies
• Digital Humanities
• +۳ مورد دیگر

Seth Bernstein is an Associate Professor of History at the University of Florida's College of Liberal Arts and Sciences. His research focuses on Soviet and post-Soviet history, digital humanities, and Stalinist-era social dynamics. He holds a Ph.D. from the University of Toronto (2013) and previously taught at the Higher School of Economics in Moscow. His major works include Return to the Motherland: Displaced Soviets in WWII and the Cold War (2023) and Raised under Stalin: Young Communists and the Defense of Socialism (2017). He has translated seminal works like Alexander Vatlin's Agents of Terror and Liudmila Novikova's An Anti-Bolshevik Alternative . His current projects explore Soviet Jewish arrests post-1953 and machine learning analysis of secret police archives. His digital humanities work employs GIS, databases, and neural networks, published in Memory Studies and Slavic Review . Bernstein's research bridges historical analysis with computational methods, examining themes like repatriation trauma, Stalinist repression, and youth politicization. He contributes to debates on archival ethics and digital memory politics in post-Soviet contexts.

• Psychology
• Neuroscience
• Cognitive Science
• +۳ مورد دیگر

Merim Bilalic is a Professor in the Psychology Department at Northumbria University. He holds a DPhil in Psychology awarded in 2016. His research focuses on cognitive science, neuroscience, and expertise development, particularly in domains like chess, sports, and AI collaboration. Key interests include decision-making processes, cognitive biases, and the neural mechanisms underlying expert performance. Recent work explores the impact of the pandemic on sports dynamics, AI's role in transforming human expertise, and survey methodology improvements. Bilalic collaborates internationally on projects analyzing home advantage in sports, perceptual-cognitive expertise, and educational rankings. His research bridges theoretical frameworks with practical applications, often employing large datasets and Bayesian modeling. Education: DPhil in Psychology (2016–Present). Research Interests: Cognitive processes in expertise, perceptual decision-making, AI-human interaction in sports, pandemic effects on behavior, and methodology in education surveys. Notable contributions include studies on working memory-fluid intelligence relationships and the role of grit in athletic success. Recent Articles Highlight Trends: Analysis of cognitive reflection in experts, AI-driven performance enhancements, pandemic-driven behavioral shifts, and methodological critiques in survey binning. These studies emphasize interdisciplinary approaches, combining neuroscience, behavioral economics, and computational methods. Advising/Grants: Supervised one doctoral student (details unavailable). Collaborations span institutions globally, focusing on elite performance and cognitive modeling. No specific grants mentioned. Labs/Teams: Involved in interdisciplinary teams studying perceptual expertise in sports and radiology, leveraging neuroimaging and big data analytics.

Nancy J. Cookeمشاهده پروفایل

استاد

• Human Systems Engineering
• Team Cognition
• Human-AI-Robot Teaming
• +۵ مورد دیگر

Nancy J. Cooke is a Professor of Human Systems Engineering at Arizona State University's Polytechnic School within the Ira A. Fulton Schools of Engineering. She also serves as Senior Scientific Advisor to the Global Security Initiative’s Center for Human, AI, and Robot Teaming. Her research focuses on team cognition, human-AI collaboration, cybersecurity, and emergency response systems. She holds a PhD in Cognitive Psychology (New Mexico State University, 1987) and has held academic roles since 1987, including past presidencies of major professional societies like the Human Factors and Ergonomics Society. Her work is funded by agencies like DARPA, the Office of Naval Research, and NASA. Dr. Cooke’s research interests include developing methodologies to assess team cognition, improving human-autonomy team performance, and addressing challenges in distributed command-and-control systems. She leads initiatives like the DEXTAR cyber defense simulator and directs the Advanced Distributed Learning Partnership Lab. Her awards include the HFES Arnold M. Small Distinguished Service Award (2014) and recognition as a National Associate of the National Research Council. Education: PhD Cognitive Psychology (New Mexico State University, 1987) Key Affiliations: Center for Human, AI, and Robot Teaming; Cognitive Engineering Research Institute Recent Grants: Cybersecurity defense projects, human-robot teaming studies Her lab facilities include the GHOST Lab and DEXTAR simulator. She has advised over 30 graduate students and serves on numerous national committees, including the National Academies’ Intelligence Science and Technology Experts Group.

Heather Sheridanمشاهده پروفایل

دانشیار

• Reading Research
• Cognitive Psychology
• Visual Expertise
• +۴ مورد دیگر

Heather Sheridan serves as Associate Professor and Area Head in the Department of Psychology at the University at Albany, State University of New York. Her office is located in Social Sciences 317 with contact number 518-898-8423. Her research program investigates reading as a multifaceted cognitive domain to explore language processing, attentional mechanisms, visual perception, and memory systems. Dr. Sheridan examines visual expertise development across domains including chess, individual performance differences, and the critical eye-mind link connecting ocular behavior to cognitive processing. Her work addresses lexical ambiguity resolution, re-reading phenomena, and cross-language variations using integrated methodologies such as eye tracking, computational modeling, distributional analyses, and ERP/EEG to map the temporal dynamics of perceptual and neural processes during reading. She also investigates broader questions in learning, memory consolidation, and conscious versus unconscious cognitive operations. No information regarding scientific awards, student advising, research grants, or laboratory facilities appears in the provided text.

Knut Peder Heenمشاهده پروفایل

دانشیار

• Sport Management
• Sports Economics
• Game Theory
• +۷ مورد دیگر

Knut Peder Heen is an Associate Professor at Molde University College, Faculty of Business Administration and Social Sciences. He is actively engaged in research and academic commentary, with a strong focus on sport management, economics, and game theory. His collaborative work with Kjetil K. Haugen spans diverse topics from football regulations to ethical and economic paradoxes. Institution: Molde University College School: Faculty of Business Administration and Social Sciences Position: Associate Professor Email: knut.p.heen@himolde.no Office: C-324, Molde His research interests include sport management, sports economics, game theory, behavioral economics, and public policy analysis. He is a member of the Sport Management Research Group (SpM), contributing to interdisciplinary studies in sports and society. His work often intersects economics, ethics, and technology in sports, particularly football. The analysis of his recent publications reveals a consistent focus on strategic behavior in sports, integrity in competition, and critical evaluation of technological interventions like VAR in football. He also explores broader societal issues such as food waste, political discourse, and academic integrity, demonstrating a multidisciplinary approach. His articles frequently appear in both academic journals and the university's public outreach platform, Panorama, indicating a commitment to knowledge dissemination. Notable research themes include: Economic incentives in sports point systems Detection of cheating in chess using heuristics Evolution of artificial turf in football Ethical implications of IQ and genetic diversity Critique of political use of scientific rhetoric While no formal list of students or scientific awards is provided, his extensive publication record suggests significant academic mentoring and research leadership. He has contributed to policy-related research, including regional air transport and nuclear industry impact assessments through Møreforsking Molde AS. His work reflects a blend of theoretical rigor and practical relevance in sports, economics, and public discourse.

Micah Goldblumمشاهده پروفایل

استادیار

• Machine Learning
• AI Safety
• Automated Data Science
• +۵ مورد دیگر

Micah Goldblum is an Assistant Professor at Columbia University, focusing on machine learning research with emphasis on AI safety, automated data science, and large-scale model training strategies. His work explores foundational topics like generalization theory, Bayesian inference, and algorithmic reasoning. He received a Ph.D. in Mathematics from the University of Maryland, advised by Tom Goldstein and Wojciech Czaja, followed by a postdoctoral fellowship at New York University under Yann LeCun and Andrew Gordon Wilson. His research portfolio includes developing robust benchmarks for large language models (e.g., LiveBench), analyzing inductive biases in ML systems via Kolmogorov complexity, and advancing adversarial detection techniques like Binoculars. Key contributions span LLM evaluation, diffusion model theory, and fairness in computer vision systems. Goldblum’s work on Bayesian model selection and compression bounds for large language models has provided critical theoretical insights. Goldblum has been recognized with the 2022 ICML Outstanding Paper Award for his work on Bayesian model selection. His research also addresses societal challenges, such as protecting privacy in facial recognition systems (LowKey) and mitigating biases in neural architectures. Collaborations include leading projects like the Battle of the Backbones vision benchmark and exploring adversarial robustness in federated learning. His labs and teams focus on interdisciplinary applications of ML, including automated benchmarking, secure AI deployment, and ethical alignment of LLMs. Goldblum’s publications consistently bridge theory and practice, with recent breakthroughs in diffusion model design, continual learning algorithms, and understanding the intrinsic properties of data distributions.

Konstantin Zuevمشاهده پروفایل

استاد آموزشی

• Statistical Data Analysis
• Network Data Analysis
• Machine Learning
• +۷ مورد دیگر

Konstantin Zuev is a Teaching Professor of Computing and Mathematical Sciences at the California Institute of Technology (Caltech), affiliated with the Division of Engineering and Applied Science. He holds dual Ph.D.s in Mathematics (Lomonosov Moscow State University) and Civil Engineering (Hong Kong University of Science & Technology). Zuev is also the Undergraduate Option Representative for Information and Data Sciences and Graduate Minor Advisor for the same field. His research focuses on statistical data analysis, network science, machine learning, and computational methods for complex systems. His teaching includes courses like Applied Linear Algebra, Probability Models, and Statistical Inference. Zuev has received multiple prestigious awards, including the 2023 ASCIT and GSC Teaching Awards, the 2021 Humboldt Research Fellowship, and the 2019 Northrop Grumman Prize for Excellence in Teaching. His work spans interdisciplinary topics such as financial market dynamics, epidemiological modeling, and academic curriculum analysis through network theory. Zuev’s research has been published in journals like *Proceedings of the National Academy of Sciences*, *Scientific Reports*, and *Physical Review E*. He is actively involved in consulting projects with organizations like Virtualitics, Inc., focusing on applications in healthcare and network analytics. Beyond academia, he advises student groups like the Caltech Chess Club and Karate Club, reflecting his passion for fostering community engagement and mentorship.

Nicholas Robertsمشاهده پروفایل

مدرس

• Mathematics Education
• Pure Mathematics
• Computer Science
• +۴ مورد دیگر

Nicholas Roberts is a Lecturer of Mathematics in the Department of Mathematics/Computer Science within the School of Natural and Social Sciences at Purchase College, State University of New York (SUNY). He also works as a certified New York State math teacher for grades 7–12, teaching at a high school on Long Island, NY. Education: BA in Mathematics/Computer Science, Purchase College (magna cum laude) MA in Pure Mathematics, Stony Brook University His academic and professional focus centers on mathematics education, pure mathematics, and interdisciplinary connections with computer science and economics. He has a strong interest in innovative teaching methods, particularly in online instruction, where he serves as a recognized SUNY Online Teaching Ambassador. His broader intellectual pursuits include music (notably trumpet performance), chess, financial markets, and language learning (Spanish). Nicholas is actively involved in student mentorship, advising the Mu Alpha Theta Math Honor Society and the chess club at his high school. His work reflects a commitment to engaging and inspiring students through both curricular and extracurricular activities. Recognition: SUNY Online Teaching Ambassador He does not have any listed research publications or formal advisees at the graduate level. His current contributions are primarily in teaching and educational leadership at both the high school and college levels.

Priya Nambisanمشاهده پروفایل

دانشیار

• Social Media and Mental Health
• Digital Technologies in Aging Research
• Health Care Innovation
• +۴ مورد دیگر

Priya Nambisan is an Associate Professor in Health Care Informatics at the University of Wisconsin-Milwaukee, directing both the SMAHRT Lab and ARDT Lab. Her career spans interdisciplinary research at the intersection of digital technologies and healthcare. Post Doctoral Fellow, Center for Health Enhancement Support Systems (CHESS), University of Wisconsin-Madison (2006) PhD in Communication & Digital Technologies, Rensselaer Polytechnic Institute (2005) MS in Nutrition Science, Syracuse University (1997) M.Sc. & B.Sc. in Public Health and Extension Education, University of Kerala (1993) Her research focuses on digital health technologies and their impact on aging populations, mental well-being, and healthcare innovation. Key areas include: Social media's role in health behavior and decision-making AI-driven patient self-care platforms (e.g., CDSSS-myHESTIA) Health disparities in low-income communities Emergency preparedness in long-term care facilities Recent publications emphasize AI applications in intergenerational support systems, chronic condition management for aging populations, and social media analytics for suicide risk detection in vulnerable groups. Scientific Awards : U.S. Fulbright Scholar (2024-2025) Teacher Excellence Awards (CETL, UWM, 2023-2024) AMIA-selected dissertation work (2005) Multiple institutional scholarships and fellowships Current grants include: NIMH R01 funding (2024-2027) for digital photovoice suicide detection research Fulbright Scholar Award (2024-2026) for India aging population platform adaptation NMDSI funding (2024-2025) for lung disease prediction via local LLMs Labs she directs ( SMAHRT and ARDT ) focus on technology-enabled health solutions through rigorous interdisciplinary research.

Manuel Quevedo-Lopezمشاهده پروفایل

استاد

• Flexible Electronics
• Semiconductor Technology
• Materials Science
• +۴ مورد دیگر

Dr. Manuel Quevedo-Lopez is a Professor and Department Head of Materials Science and Engineering at The University of Texas at Dallas, where he holds the Texas Instruments Distinguished University Chair in Nanoelectronics. He leads the Flexible and Large Area Nanoelectronics (FLAN) laboratory and serves as director of the Center for Harsh Environment Semiconductors and Systems (CHESS), established in 2022 to advance semiconductor technology for extreme environments. Education: PhD in Materials Science and Engineering from the University of North Texas (2002) MS in Materials Science and Engineering from Saltillo Institute of Technology BS in Chemistry and Biology from the University of Sonora, Mexico His research focuses on materials and devices for large area sensors and flexible electronics, integrating physics, chemistry, and engineering. Key projects include nuclear threat detection, nanomaterials for flexible electronics, process integration, memory integration, and device modeling and simulation. His work has led to a cost-effective neutron radiation detection technology with applications in security and military operations. Scientific Awards: Texas Instruments Distinguished University Chair in Nanoelectronics Six patents related to neutron radiation detection technology Member of Mexican National Research System Level III Dr. Quevedo-Lopez has secured funding from the Air Force Office of Scientific Research, Department of Homeland Security, National Science Foundation, and Texas Instruments. He emphasizes mentorship, fostering student engagement in research, and building lifelong academic relationships. He contributes to international collaboration as an advisory board member of ConTex, a UT System-Conacyt initiative, and maintains an adjunct appointment at the University of Sonora.

Pawel Sobocinskiمشاهده پروفایل

استاد

• Applied Category Theory
• Compositional Systems
• Theoretical Computer Science
• +۱۰ مورد دیگر

Paweł Sobociński is a Professor of Trustworthy Software Technologies at the Department of Software Science, School of Information Technologies, Tallinn University of Technology (TalTech), where he also leads the Laboratory for Compositional Systems and Methods. He is a principal investigator in several major research projects including the Estonian Research Council’s PRG1210 (ALICE), the EU-funded CHESS cybersecurity hub, and the EXAI Centre of Excellence in AI. His academic background includes faculty positions at the University of Southampton and research roles at the University of Cambridge and institutions in France and Italy. His research lies at the intersection of computer science and mathematics, with a focus on applied category theory. He investigates compositional modeling of systems, where the behavior of complex systems emerges from the structured interaction of their components. His work employs string diagrams, process algebras, Petri nets, and categorical semantics to develop formal methods for verifying and reasoning about concurrent and cyber-physical systems. He is particularly known for his contributions to graphical linear algebra and diagrammatic reasoning. The recent publications highlight a strong trend in diagrammatic methods, especially string diagrams, for expressing logic, algebra, and system behavior. These works span from foundational categorical structures to applications in electrical circuits, concurrency, and formal verification, demonstrating a unifying thread of compositional reasoning. His leadership in organizing conferences like LICS 2024 and ICALP 2024 underscores his central role in the theoretical computer science community. His scientific recognition includes numerous invited talks and tutorials at major international venues such as CONCUR, QPL, MFPS, and ETAPS, as well as leadership roles in academic organizations. He is an Associate Editor for journals including Compositionality , Mathematical Structures in Computer Science , and Logical Methods in Computer Science , and has served on the steering committee of ETAPS. Sobociński has supervised multiple PhD students and postdoctoral researchers, including Owen Stephens, Fabio Zanasi, Mario Román, and Elena di Lavore. He is also the director of the PhD programme in ICT at TalTech and has received research grants from the Estonian Research Council, the European Commission, and the Estonian Ministry of Education and Research, supporting his work in trustworthy software, AI, and cybersecurity. He leads the Laboratory for Compositional Systems and Methods at TalTech, a research group focused on developing and applying compositional techniques in software science, with applications in AI, security, and formal verification. The lab fosters international collaboration and is active in organizing workshops and summer schools.

Brendan Sullivanمشاهده پروفایل

استادیار

• Graph Theory
• Combinatorics
• Pursuit-Evasion Games
• +۵ مورد دیگر

Brendan Sullivan is an Assistant Professor of Mathematics at Emmanuel College , specializing in graph theory and combinatorics . He holds a Doctorate of Arts (2013) and MS in Mathematics (2010) from Carnegie Mellon University, along with a BA in Mathematics & Physics (2007) from Hamilton College. Education Doctorate of Arts in Mathematics, Carnegie Mellon University (2013) MS in Mathematics, Carnegie Mellon University (2010) BA in Mathematics & Physics, Hamilton College (2007) His research focuses on mathematical puzzles and their applications, particularly in Lazy Cops & Robbers pursuit-evasion games on graphs, voting theory , and the Basel Problem . He has collaborated with Emmanuel students on graph theory research and is compiling a comprehensive book on the Basel Problem. Scientific Recognition Hugh D. Young Graduate Student Teaching Award (2013), Carnegie Mellon University He has created educational materials including crossword puzzles for Mathematics Magazine and a textbook for proof-writing instruction used at Carnegie Mellon University. His publications extend into fractal geometry and materials science , reflecting interdisciplinary interests.

Matija Piškorecمشاهده پروفایل

پژوهشگر

• Machine Learning
• Complex Systems
• Statistical Inference
• +۵ مورد دیگر

Matija Piškorec is a Senior Research Associate at the Faculty of Informatics, University of Zurich. His research spans machine learning, complex systems, and blockchain technologies, with a focus on statistical inference of social influence and network analysis. Primary Affiliation: Faculty of Informatics, University of Zurich Research Interests Machine learning and complex systems Statistical inference of influence in online social networks Blockchain technologies and distributed ledger systems Information visualization and interactive web applications in computational biology Publications His recent work explores blockchain networks like Polkadot and Ethereum, analyzing their structure and consensus mechanisms. Earlier research focuses on social network influence, financial data cohesiveness, and computational biology tools. Awards No scientific awards or honors were explicitly mentioned in the text. Additional Contributions Developed web-based visualization tools (e.g., MultiNets) and applied machine learning to diverse domains, including microbiology and finance.