Find Academic Supervisors

Necmiye OzayView profile

Associate Professor

• Control Systems
• Optimization
• Formal Methods
• +5 more

Necmiye Ozay is an Associate Professor in Robotics and Electrical and Computer Engineering at the University of Michigan. Her research focuses on control systems, formal methods, and cyber-physical systems, with applications in autonomy, system identification, and verification. She leads a diverse research group encompassing PhD, MS, and undergraduate students, as well as postdoctoral researchers. Her work bridges theory and practice, addressing challenges in safety-critical systems design and data-driven control. Her educational background includes a PhD in Electrical and Computer Engineering from Northeastern University and a Master’s from Penn State. She has received significant funding from NSF, ONR, and industry partners, supporting projects like the CLEVR-AI initiative and Scenic ecosystem development. Her research has been recognized through awards and collaborations at institutions like MIT, Berkeley, and Johns Hopkins. Key research areas include model-based control synthesis, robust system identification, and anomaly detection in cyber-physical systems. Notable contributions include methods for correct-by-construction control, hybrid system analysis, and learning-based approaches for autonomous systems. She actively contributes to conferences such as HSCC and CDC, and her lab’s work impacts automotive safety, energy systems, and robotics. Ozay’s advising spans over 50 students and postdocs, many of whom hold academic or industry roles. Her lab maintains active collaborations across disciplines, emphasizing interdisciplinary solutions to real-world control challenges.

Mohammed AledhariView profile

Assistant Professor

• Artificial Intelligence
• Machine Learning
• Data Science
• +3 more

Mohammed Aledhari is an Assistant Professor at the University of North Texas, specializing in cybersecurity, machine learning, and data science. His research focuses on applications in computational medicine, bioinformatics, and autonomous systems. He holds a Ph.D. from Western Michigan University and degrees from the University of Basrah and the University of Anbar. His research interests include social cybersecurity techniques, federated learning in IoT, and AI-driven solutions for healthcare and transportation. Recent work explores blockchain-enabled digital twins, DDoS attack detection, and equitable ASD diagnostics using machine learning. His publications span cybersecurity frameworks, autonomous vehicle communication protocols, and biomedical IoT innovations. Notable contributions include optimizing intrusion detection in IoMT networks and developing interpretable machine learning models for healthcare. While no formal awards or grants are listed, his work emphasizes interdisciplinary applications of AI in healthcare, transportation, and energy markets. His email is Mohammed.Aledhari@unt.edu .

James MalazitaView profile

Associate Professor

• Game Studies
• Platform Studies
• Feminist Technoscience
• +7 more

James Malazita is Associate Professor of Science & Technology Studies and Associate Director of the Games and Simulation Arts and Sciences (GSAS) program at Rensselaer Polytechnic Institute (RPI). He is affiliated with the Department of Science and Technology Studies in the School of Humanities, Arts, and Social Sciences, and contributes to the GEM (Games and Experiential Media) research group. Education: Ph.D. in Communication, Culture, and Media, Drexel University (2014) BS/MS in Digital Media, Drexel University (2009) Malazita's research lies at the intersection of game studies, platform studies, feminist technoscience, and social justice in computing. He critically investigates how game engines like Unreal shape technological and cultural infrastructures, particularly through the lenses of gender, race, and power. His forthcoming book, Enacting Platforms: Feminist Technoscience and the Unreal Engine (MIT Press, July 2024), offers a groundbreaking feminist and critical analysis of one of the most influential game development platforms. His work also extends to digital humanities, critical design, and the politics of computer science education. His recent publications reveal a strong thematic focus on the co-production of technology and society, with recurring interests in epistemic cultures, disciplinary formation, localization, and critical pedagogy. These works span journals in game studies, design, digital humanities, and STS, reflecting an interdisciplinary approach that bridges technical systems and humanistic critique. Scientific Support and Affiliations: Supported by NEH Office of Digital Humanities Supported by NEH Division of Educational Programs Supported by Popular Culture Association Supported by New Jersey Historical Commission Supported by Red Hat Inc. Supported by Rensselaer’s Teaching and Learning Collaboratory Member of GEM (Games and Experiential Media) ORCID: 0000-0003-3206-3682 Malazita advises graduate students in STS and Games, with former advisees placed at Yale, NYU, and UT Austin. He teaches courses in game studies, human-centered design, interpretive methods, and critical technology studies. His current course includes STSO 2610: DSIS Studio II (Spring 2024). His research raises fundamental questions about the material and cultural limits of platforms, the analyst-platform relationship, and the future of the web as shaped by game technologies.

• Pediatric Primary Care
• Obesity
• Breastfeeding
• +4 more

Ada M. Fenick, MD, is a Professor of Pediatrics (General Pediatrics) at Yale School of Medicine. She holds multiple leadership roles including Associate Director for Pediatrics in the Biopsychosocial Approach to Health clerkship, Medical Director of School-Based Health Centers, and Medical Director of the Medical-Legal Partnership Project. Her clinical practice focuses on economically disadvantaged pediatric populations, emphasizing developmental aspects of child health and addressing toxic stress impacts. Education: BS in Biomedical Sciences (University of Michigan, 1990), MD (University of Michigan, 1993), Pediatric Residency (Weill-Cornell/NY Medical Center, 1996) Research: Centers on pediatric primary care innovations such as group well-child care models, medical-legal partnerships, and obesity prevention. Key themes include health equity, social determinants of health, and curriculum development. Her recent work emphasizes leveraging medical student experiences to improve curricula addressing social drivers of health. Over 20 peer-reviewed publications since 2020 focus on topics like electronic phenotyping algorithms for obesity screening and frameworks for group pediatric care implementation. Awards: Includes Howard A Pearson MD Teaching Award (2013) and multiple institutional recognitions for clinical excellence and innovation. She leads initiatives like the Yale Primary Care Pediatrics Curriculum and collaborates with community organizations to enhance access to early intervention services for vulnerable children. Her work integrates clinical care, education, and policy advocacy to promote holistic child health outcomes.

• Nonlinear Control
• Robust Control
• Adaptive Control
• +7 more

Mike Grimble is a Research Professor in the Department of Electronic and Electrical Engineering at the University of Strathclyde, Faculty of Engineering. His work is centered on advanced control systems with applications across automotive, aerospace, marine, and industrial domains. He is actively involved in theoretical and applied research, particularly in nonlinear and robust control methodologies. Research Interests: Theory and application of nonlinear and robust control for multivariable systems Adaptive control and estimation methods Benchmarking and performance assessment of control systems Condition monitoring and industrial applications Real-time control and embedded systems His recent publications highlight a strong trend in applying predictive and adaptive control techniques to electric vehicles, battery systems, underwater robotics, and industrial machinery. These works emphasize real-time implementation, energy optimization, and robustness—critical for modern sustainable and autonomous systems. Scientific Recognition and Activities: Invited speaker on the benefits and challenges of advanced control in industrial applications (2013) Contributor to UN Sustainable Development Goals, particularly in sustainable industry and innovation Active research output with over 158 publications, including journals, conferences, and book chapters Research Leadership and Funding: Principal Investigator on multiple EPSRC and RSE-funded projects Co-investigator in interdisciplinary initiatives such as the Medical Devices Doctoral Training Centre Organizer of international workshops on hybrid and predictive control Labs and Research Teams: He is associated with the Industrial Control Centre at the University of Strathclyde, a leading hub for control engineering research. His collaborations span departments and institutions, involving real-time LabVIEW implementations, hardware demonstrations, and partnerships with industry players like National Instruments and Quanser Inc.

Anett HoppeView profile

Researcher

• Search as Learning
• Educational Technology
• Artificial Intelligence in Education
• +5 more

Dr. Anett Hoppe is a research staff member at the Leibniz Information Centre for Science and Technology (TIB) in Hannover, Germany, where she works in the Visual Analytics research group. Her research focuses on the intersection of artificial intelligence, education technology, and information science, with particular emphasis on how people learn through search processes and educational video consumption. Dr. Hoppe completed her academic journey with: Ph.D. in Semantic Web technologies for online user profiles from the University of Burgundy, Dijon, France Her primary research interests span Search as Learning, software-based support for scientific reproducibility, and ethical considerations in computer-based decision making. She investigates how visual elements, reading sequences, and AI technologies impact knowledge acquisition during web search and educational video consumption. Her work bridges human-computer interaction, educational psychology, and information retrieval to create more effective learning experiences, with recent publications examining the role of large language models, vision-language models, and visual complexity in educational contexts. Analysis of her recent publications (2024-2025) reveals a strong interdisciplinary focus combining computer science, educational psychology, and information science. Her research examines video-based learning effectiveness, knowledge gain prediction, educational resource discovery, and the impact of visual elements on learning outcomes. She consistently explores how AI technologies can be leveraged to enhance educational experiences while maintaining attention to ethical considerations and scientific reproducibility. Dr. Hoppe maintains active collaborations with researchers across multiple institutions, with frequent co-authorship patterns indicating strong research partnerships, particularly with Ralph Ewerth and other members of the Visual Analytics group at TIB. Her work supports TIB's mission to advance knowledge infrastructure and scholarly communication through innovative technological solutions while directly addressing practical challenges in educational technology and information retrieval.

Alexander JacobyView profile

Senior Lecturer

• Japanese Cinema
• Classical Japanese Film
• Contemporary Japanese Cinema
• +7 more

Dr Alexander Jacoby is a Senior Lecturer in Japanese Studies at Oxford Brookes University, affiliated with the School of Education, Humanities and Languages. He is also the Director of the Europe Japan Research Centre, where he promotes academic collaboration between Europe and Japan. His teaching spans undergraduate and postgraduate levels, covering Japanese cinema, manga, anime, classical arts, and translation. Research Interests: Alexander's primary research focuses on classical and contemporary Japanese cinema. He explores themes such as family dynamics, gender, space, and national identity in Japanese film. His work bridges academic scholarship and public film criticism, contributing to both scholarly journals and major cultural publications. Publication Trends: His recent articles examine socio-cultural themes in modern Japanese cinema, particularly family structures and contested national narratives. These works reflect a consistent engagement with postwar Japanese society as portrayed through film, with an emphasis on directors like Hirokazu Koreeda and Yoshimura. Notable Presentations: 'Hirokazu Koreeda's Family Values' (2021) 'Crime and Punishment in the Films of Hirokazu Koreeda' (2018) 'Female Self-Determination in Yoshimura's Kyoto' (2017) Professional Engagement: Jacoby has curated Japanese film retrospectives at prestigious institutions including the British Film Institute (London), Museum of Modern Art (New York), Il Cinema Ritrovato (Bologna), and Giornate del Cinema Muto (Pordenone). He has also served as Year Abroad Tutor, supporting student exchanges and international learning. Labs and Research Groups: He chairs the Europe Japan Research Centre, a hub for interdisciplinary research on Japan-Europe relations in media, culture, and society.

Gabriele SchweikertView profile

Senior Lecturer

• Computational Biology
• Machine Learning
• Epigenetics
• +6 more

Dr. Gabriele Schweikert is a Senior Lecturer and Principal Investigator with a joint appointment between the Division of Computational Biology in the School of Life Sciences at University of Dundee and Cyber Valley in Tuebingen. Her research focuses on applying machine learning techniques to understand epigenetic mechanisms and molecular processes in living cells. Dr. Schweikert completed her PhD at the Max Planck Institute Tuebingen working with Schoelkopf, Weigel, and Raetsch labs on machine learning for computational gene finding. She subsequently joined Adrian Bird's lab at the Wellcome Trust Center for Cell Biology in Edinburgh, a pioneer in epigenomic research. Prior to her current position, she held prestigious Marie Curie and EMBO Fellowships at the School of Informatics, University of Edinburgh. Her research interests center on using machine learning to decode epigenetic mechanisms that determine cellular identity and function. She investigates how cells with identical DNA can differentiate into specialized cell types through epigenetic regulation, with particular focus on applications in understanding tumorigenesis where epigenetic machinery malfunctions. Her work combines high-throughput epigenomic data with advanced computational approaches to address complex biological questions. Analysis of her recent publications reveals a strong focus on epigenomic data analysis, machine learning applications in biology, and computational approaches to understanding gene regulation. Her work spans from fundamental epigenetic mechanisms to practical applications in disease research, with growing emphasis on individual-specific epigenomic analysis and explainable AI in biomedical contexts. UKRI Future Leaders Fellowship (2020, £1.6 million) Marie Curie Fellowship EMBO Fellowship Dr. Schweikert actively supervises PhD students and has received significant research funding for projects including 'Machine Learning Methods to Re-Annotate Histone Modifications,' 'Unlocking The Alternative Splicing Code,' and 'GPU-Based Machine Learning System For Fundamental Biological Research.' She is involved in multiple interdisciplinary collaborations and frequently presents her work at major conferences including ELLIS Health program retreat, Epigenetics Meetings, and RECOMB workshops. She maintains active research laboratories in both Dundee and Tuebingen, fostering international collaboration between computational biologists, machine learning experts, and experimental biologists to advance our understanding of epigenetic regulation in health and disease.

• Networked Systems
• Distributed Systems
• Social Computing
• +5 more

Krishna Gummadi is a Scientific Director and Professor at the Max Planck Institute for Software Systems (MPI-SWS) in Germany, where he leads the Networked Systems Research Group. He also holds a professorship at the University of Saarland, demonstrating his dual commitment to research and academic instruction in computer science. His educational background includes: Ph.D. in Computer Science and Engineering from the University of Washington (2005) B.Tech. in Computer Science and Engineering from the Indian Institute of Technology, Madras (2000) Gummadi's research spans networked and distributed computer systems with a current focus on social computing systems. His work addresses critical challenges in algorithmic fairness, privacy in social media, trustworthiness of online identities, and information dissemination in social networks. He approaches these problems through interdisciplinary methods combining user-centric studies, data-centric analysis, and systems-centric design to create practical solutions that enhance fairness, transparency, and user control in online platforms. His methodology integrates large-scale observational studies, computational modeling, and system implementation to tackle complex human-computer interaction challenges at societal scale. His recent publications reveal a strong emphasis on fairness in algorithmic decision making, with significant contributions to quantifying and addressing discrimination in machine learning systems. His work bridges computer science, social science, and ethics, creating frameworks for fair classification, understanding media bias, and developing privacy-preserving techniques that maintain functionality while protecting user data. The research demonstrates a progression from technical system design to addressing societal implications of computing systems. Among his notable scientific achievements: ERC Advanced Grant in 2017 for 'Foundations for Fair Social Computing' Test of Time Awards at ACM SIGCOMM and AAAI ICWSM Casper Bowden Privacy Enhancing Technologies (PET) and CNIL-INRIA Privacy Runners-Up Awards IW3C2 WWW Best Paper Honorable Mention Multiple Best Paper awards across prestigious conferences Gummadi has advised numerous PhD students and postdoctoral researchers who have gone on to prominent positions in academia and industry. His ERC Advanced Grant has supported extensive research into fair social computing, while his leadership in major conferences (including serving as General Chair for ICWSM 2016 and Program Chair for WWW 2015) has shaped research directions in the field. His teaching portfolio includes courses on Distributed Systems, Human-Centered Machine Learning, and Social Media Analysis. He leads the Networked Systems Research Group at MPI-SWS, which has developed several publicly available systems including tools for fair classification, privacy risk assessment, trust evaluation in social media, and information diet management. The group's work bridges theoretical advances with practical implementations that address real-world challenges in social computing, with numerous software releases and datasets made available to the research community.

Miles M. IshigakiView profile

Professor

• Music Performance
• Music Education
• Clarinet Performance
• +3 more

Miles M. Ishigaki serves as Professor of Music in the Department of Music within California State University, Fresno's College of Arts and Humanities. He has taught applied clarinet, chamber music, music theory, and music appreciation at Fresno State since 1987 while directing the university clarinet choir. From 1989-2017, he held the position of state chair for the National Association of College Wind and Percussion Instructors, demonstrating sustained institutional commitment. His academic credentials include: Doctor of Musical Arts in Performance, University of Oklahoma (1988) Doctoral study in Music Performance, University of Arizona (1981-1982) Master of Music in Performance, Colorado State University (1981) Dual Bachelor's degrees: Music Education and Music Performance, University of Northern Colorado (1978) Dr. Ishigaki's research centers on the dialectic between intuition and analytical understanding in musical performance, particularly regarding clarinet repertoire. His seminal work documents interpretive approaches of legendary clarinetists including Larry Combs, Stanley Hasty, and Leon Russianoff, focusing on Stravinsky's Three Pieces for Solo Clarinet. His collaborative research with Dr. Michael Rogers bridges music theory and performance practice, revealing how structural analysis informs expressive execution. This scholarly trajectory consistently examines the cognitive and technical dimensions of artistic mastery. His publications from 1988-2017 reveal evolving emphases from symposium documentation and performance analysis toward technology integration in music education, culminating in the 2017 Music Fundamentals ebook. Collectively, his work establishes clarinet pedagogy as both scientific discipline and artistic practice, with growing attention to digital learning environments while maintaining core focus on interpretive authenticity. His recognitions include: 2013 Provost's Teaching Award in Technology for innovative digital pedagogy 2006 Honorary Alumnus distinction from University of Northern Colorado Dr. Ishigaki has mentored exceptional students who have earned Fulbright Scholarships, McNair Doctoral grants, and participation in national honor ensembles. His studio consistently produces competition winners while he maintains active performance engagements with regional orchestras and international venues. Beyond academia, he serves as COO of I&M, Inc., applying sustainable technology principles to water and energy systems, demonstrating interdisciplinary impact beyond music. As founder of both the West Coast Clarinet Congress and Fresno State Faculty Clarinet Quartet, he cultivates professional communities while maintaining Yamaha Artist status. His community outreach through organizations like the Japanese American Citizen's League and Valley Children's Hospital reflects deep civic engagement alongside scholarly pursuits.

Bryon AragamView profile

Associate Professor

• Causality
• Statistical Machine Learning
• Probabilistic Modeling
• +6 more

Bryon Aragam is an Associate Professor of Econometrics and Statistics and Robert H. Topel Faculty Scholar at the University of Chicago Booth School of Business. His research focuses on the intersection of causality, statistical machine learning, and probabilistic modeling, with particular emphasis on applications to artificial intelligence systems including large language models like ChatGPT and generative models like DALL-E. Dr. Aragam completed his PhD in Statistics and a Masters in Applied Mathematics at UCLA, where he was an NSF graduate research fellow. Prior to joining the University of Chicago, he was a project scientist and postdoctoral researcher in the Machine Learning Department at Carnegie Mellon University. Research Focus: Causal structure learning in probabilistic generative models Key Areas: Causal machine learning, deep generative models, latent variable models, statistical learning theory Applications: AI interpretability, ethics, and fairness in artificial intelligence systems Teaching: Business Statistics, Econometrics and Statistics Colloquium His recent publications demonstrate a strong theoretical foundation combined with practical applications, particularly in understanding and improving AI systems. His work spans causal discovery, graphical models, deep learning, and latent variable modeling, with particular attention to the theoretical properties of these methods and their applications to real-world AI challenges. The research shows a progression toward increasingly complex problems in causal representation learning and AI interpretability. Scientific Awards: Robert H. Topel Faculty Scholar NSF Graduate Research Fellow Dr. Aragam's work has been published in top statistics and machine learning venues including the Annals of Statistics, Neural Information Processing Systems (NeurIPS), the International Conference on Machine Learning (ICML), and the Journal of Machine Learning Research (JMLR). His research group publishes broadly across both statistical and machine learning communities, demonstrating the interdisciplinary nature of his work at the intersection of statistics, machine learning, and causal inference. As a data science consultant for technology and marketing firms, Dr. Aragam has applied his expertise to problems in survey design, customer retention, logistics, and ranking, bridging the gap between theoretical research and practical applications.

James Herbert-ReadView profile

Associate Professor

• Behavioural Ecology
• Marine Biology
• Collective Animal Behaviour
• +4 more

Dr James Herbert-Read is an Associate Professor and Whitten Lecturer in Marine Biology at the Department of Zoology, University of Cambridge. He serves as Deputy Head of Department (Postgraduate Education) and leads the Marine Behavioural Ecology Group. His research focuses on understanding how animals, particularly marine organisms, collect and process information from their environments to make behavioral decisions, with emphasis on social interactions, adaptation mechanisms, and ecological constraints. His group employs theoretical frameworks, controlled experiments, and quantitative field studies to investigate behavioral diversity in marine species. Key themes include collective behavior, predator-prey dynamics, camouflage strategies, and the impacts of environmental stressors on animal decision-making. Recent publications highlight work on lionfish vocalization mechanisms, cuttlefish camouflage, citizen science applications in marine research, and behavioral responses to visual and acoustic noise. Scientific awards and affiliations include: Whitten Lecturer in Marine Biology Associate Professor, University of Cambridge He has supervised research projects on topics such as: Social attraction in invasive fish species Evolution of coordinated movement Neurophysiological basis for leadership in shoals Maternal effects on offspring exploration

Matloob KhushiView profile

Senior Lecturer

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +7 more

Dr. Matloob Khushi serves as a Senior Lecturer in Computer Science at Brunel University London's College of Engineering, Design and Physical Sciences. With over 25 years of combined academic and industry experience, his work bridges theoretical AI advancements with practical applications in finance, healthcare, and public health domains. His research has established significant collaborations with international banks, healthcare institutions, and technology startups. Dr. Khushi earned his PhD in AI and Data Science from the University of Sydney, developing novel algorithms for genomic data analysis. His postdoctoral research at the Children's Medical Research Institute (2014-2017) pioneered AI-based diagnostic tools for medical condition detection. More recently, he developed bioinformatics tools for environmental assessment under a UKRI NEC grant. Research Focus FinTech Innovation : Creator of the SS Ratio (incorporating volatility and drawdown sensitivities), advanced portfolio optimization models, and synthetic data generation techniques for fraud detection and credit risk assessment Bioinformatics Leadership : Developer of AI tools for genomic analysis and early cancer detection, featured in SBS News and The Daily Telegraph Public Health NLP : Architect of systems for vaccine misinformation detection, mental health monitoring, and health surveillance on social media His publication portfolio shows consistent growth from foundational bioinformatics work to current multimodal AI applications, with increasing interdisciplinary collaboration across finance and healthcare sectors. Awards and Recognition Ranked among Stanford/Elsevier's top 2% of global AI scientists Recipient of Best Paper Awards from IEEE Transactions on Computational Social Systems and PeerJ Media recognition for cancer detection research by major news outlets Mentorship and Teaching Dr. Khushi has supervised six PhD candidates to completion and over 100 postgraduate dissertations. He teaches CS3002 Artificial Intelligence and mentors students in Final Year Projects. His supervision focuses on Deep Learning/NLP for FinTech prediction and Public Health Surveillance applications, emphasizing practical implementation of theoretical concepts.

Michael KnapView profile

Associate Professor

• Condensed Matter Theory
• Quantum Many-Body Systems
• Non-Equilibrium Quantum Dynamics
• +5 more

Michael Knap is an Associate Professor of Collective Quantum Dynamics at the Technical University of Munich (TUM), within the Department of Physics at the TUM School of Natural Sciences. His research group focuses on condensed matter theory, quantum many-body systems, and quantum simulation. Knap holds office in room 5101.01.037 at James-Franck-Str. 1, 85748 Garching b. München, and can be reached at michael.knap@ph.tum.de or +49 (89) 289 - 53777. Prof. Knap's research delves into the rich physics of quantum many-body systems, particularly exploring non-equilibrium dynamics and transport phenomena in ultracold quantum gases, interacting light-matter systems, and correlated quantum materials. His work spans multiple subfields including topological phases of matter, quantum simulation with trapped ions, fracton physics, and quantum computation. He develops novel numerical approaches based on quantum information theory and utilizes artificial intelligence and machine learning to tackle challenging problems in condensed matter physics. His group's research connects fundamental theoretical questions with experimental implementations in quantum simulators. The analysis of Prof. Knap's recent publications (2023-2025) reveals a strong focus on topological quantum matter, quantum simulation, and emergent phenomena in constrained quantum systems. His work frequently bridges condensed matter theory with quantum information science, as evidenced by publications on fracton hydrodynamics, higher-form symmetries, and quantum error correction. There's a clear progression toward increasingly complex quantum systems and connections to experimental implementations on quantum processors. His research shows significant interdisciplinary reach, connecting condensed matter physics with quantum computing and quantum information theory. ERC Consolidator Grant (2025) ERC Starting Grant (2019) Supervisory Award, TUM Department of Physics (2018) Promotio sub auspiciis Praesidentis rei publicae, Austria (2013) Prof. Knap has established a robust research program supported by prestigious European Research Council grants. His group actively collaborates with both theoretical and experimental groups worldwide, particularly in the quantum simulation community. He has supervised numerous students through Master's Seminars on Collective Quantum Dynamics covering topics like quantum simulation with trapped ions and theoretical quantum computation. His research has received significant attention, with several publications featured as Editors' suggestions and Research Highlights in leading journals. The Collective Quantum Dynamics group maintains strong connections with experimental quantum simulation efforts, particularly in the areas of ultracold atoms and trapped ion systems. Knap's theoretical work often provides frameworks for interpreting experimental results in quantum simulators, creating a productive feedback loop between theory and experiment. His group participates in collaborative research networks focused on advancing quantum simulation capabilities and understanding fundamental aspects of quantum many-body physics.

Alexandra PapoutsakiView profile

Associate Professor

• Human-Computer Interaction
• Eye Tracking
• Shared Gaze for Remote Collaboration
• +5 more

Alexandra Papoutsaki is an Associate Professor of Computer Science at Pomona College since 2017. Her research focuses on Human-Computer Interaction , particularly in webcam-based eye tracking and shared gaze for remote collaboration . Ph.D. in Computer Science from Brown University M.Sc. in Computer Science from Brown University B.Sc. in Computer Science from Athens University of Economics and Business Her work spans personal informatics , crowdsourcing methodologies , and remote usability testing , with recent projects examining collaborative drawing interfaces, baby tracking reflection, and digital health communities. Earlier contributions include computational biology research in genome-wide survival analysis and pan-cancer mutation networks. Key trends in her publications include: Remote collaboration tools enhanced by eye tracking Personal data systems for health and creative domains Foundational work in crowdsourcing quality control Interdisciplinary approaches combining computer science with psychology and medicine Scientific recognition includes: NSF CRII Grant (2020-2022) Wig Distinguished Professor Award (2020) Best Paper at RECOMB (2013) She has developed multiple open-source platforms including WebGazer for scalable eye tracking and Remotion for mobile usability testing. Her research team has published extensively in top venues like CHI, IMWUT, and IJCAI.