جست‌وجوی استاد و پژوهشگر

Deepti Aggarwalمشاهده پروفایل

مدرس

• Digital health
• Wearable technology
• Human-computer interaction
• +۶ مورد دیگر

Dr. Deepti Aggarwal is a Lecturer in Emerging Digital Health Technologies at Deakin University's School of Information Technology within the Faculty of Science Engineering and Built Environment. Previously, she held research positions at RMIT University's School of Media and Communications and the University of Melbourne's Department of Computing and Information Systems. She maintains honorary affiliations with the Murdoch Children's Research Institute and Royal Children's Hospital in Melbourne. Her educational background includes a PhD from the University of Melbourne, a Master's by Research in Computer Science from the International Institute of Information Technology in Hyderabad, and is currently pursuing a Graduate Certificate of Higher Education at Deakin University. She has extensive experience in interdisciplinary health technology research, collaborating with clinicians at major medical institutions. Dr. Aggarwal's research focuses on the intersection of design, health, and technology with particular emphasis on wearable and tangible interactions, IoT, Virtual Reality, and playful systems to promote healthy eating practices among children and adults. Her work explores how emerging technologies can create awareness about positive eating habits and facilitate the adoption of nutritious eating in everyday life through innovative interfaces and experiences. Her publication portfolio demonstrates consistent contributions to human-computer interaction and digital health, with recent work focusing on emerging digital health technologies and smart systems. Her research shows a clear trajectory from foundational work in telehealth and physiotherapy to broader applications in nutrition and healthy behaviors, utilizing increasingly sophisticated interactive technologies. Winner of the 2017 Fresh Science Award in Victoria Finalist for the Premiers Design Award 2022 Honorable Mention Award at ACM CHI PLAY 2020 Finalist for the 2019 IxDA Interaction Awards Finalist for the 2018 Victorian Premier's Design Award Dr. Aggarwal has received significant research recognition, including extensive media coverage of her PhD work on smart socks (SoPhy) reaching over 86 million people globally, with features in BBC News, ABC News, and selection for the London Science Museum's 'From the Lab' video series. She has secured research funding including the ECR PRESS SCHEME 2023 grant. She is actively involved with multiple research groups including the Immersive Technologies Lab at Deakin University, the Hearty Adventures in Food and Play Research Lab at RMIT University, and the National Nutrition Network for Early Childhood Education and Care, demonstrating her commitment to interdisciplinary collaboration in health technology innovation.

Yuejie Chiمشاهده پروفایل

استاد

• Theoretical Statistics
• Data Science
• Generative AI
• +۵ مورد دیگر

Yuejie Chi is the Charles C. and Dorothea S. Dilley Professor of Statistics and Data Science at Yale University, with a secondary appointment in Computer Science. She is a member of the Yale Institute for Foundations of Data Science. Previously, she held the Sense of Wonder Group Endowed Professor position at Carnegie Mellon University with affiliations in the Machine Learning Department (MLD) and CyLab. Her career includes a visiting researcher position at Meta's Fundamental AI Research (FAIR) group. Dr. Chi received her Ph.D. and M.A. in Electrical Engineering from Princeton University in 2012 and 2009, respectively, and her B.E. (Hon.) in Electrical Engineering from Tsinghua University, Beijing, China, in 2007. Her educational background laid the foundation for her interdisciplinary research approach spanning statistics, computer science, and engineering domains. Professor Chi's research focuses on the theoretical and algorithmic foundations of data science, with particular emphasis on generative AI, reinforcement learning, and signal processing. Her work lies at the intersection of statistics, learning, optimization, and sensing, addressing fundamental challenges in improving the performance, efficiency, and reliability of AI systems in data-intensive but resource-constrained scenarios. Her group's research is highly interdisciplinary, tackling problems that require theoretical rigor alongside practical implementation considerations. Theoretical foundations of generative models and diffusion processes Algorithmic guarantees for reinforcement learning systems Robust and efficient optimization methods for large-scale problems Low-dimensional structures in high-dimensional data Professor Chi's recent publications reveal a strong trajectory toward addressing fundamental theoretical questions in AI while maintaining practical relevance. Her work demonstrates increasing focus on the interplay between theoretical guarantees and practical implementation, particularly in generative models and reinforcement learning systems. Notable themes include non-asymptotic convergence analysis, robustness guarantees, communication efficiency in distributed settings, and bridging theoretical insights with real-world applications. Among her distinguished recognitions are the Presidential Early Career Award for Scientists and Engineers (PECASE) from the White House, the inaugural IEEE Signal Processing Society Early Career Technical Achievement Award, the SIAM Activity Group on Imaging Science Best Paper Prize, and the IEEE Signal Processing Society Young Author Best Paper Award. She is an IEEE Fellow (Class of 2023) for contributions to statistical signal processing with low-dimensional structures. Additional honors include young investigator awards from NSF, ONR, and AFOSR, and she has been named a Goldsmith Lecturer by IEEE Information Theory Society (2021), a Distinguished Lecturer by IEEE Signal Processing Society (2022-2023), and a Distinguished Speaker by ACM (2023-2026). Professor Chi has mentored an impressive cohort of PhD students and postdoctoral researchers, many of whom have received prestigious fellowships and awards. Her advisees have secured positions at leading institutions including Johns Hopkins University, MIT, UNC Chapel Hill, and major technology companies like Meta, Apple, and Google. Her group has produced numerous award-winning papers and dissertations, including the IEEE SPS Best PhD Dissertation Award. She has successfully secured significant research funding from federal agencies and industry partners to support her interdisciplinary research program. Professor Chi leads a vibrant research group at Yale that maintains active collaborations across multiple disciplines and institutions. Her group's work spans theoretical analysis, algorithm development, and practical implementation, with emphasis on both foundational understanding and real-world applicability. The group has developed several influential frameworks including Robust Gymnasium, a unified modular benchmark for robust reinforcement learning, and has made significant contributions to understanding the theoretical properties of modern AI systems.

Stefan Wagnerمشاهده پروفایل

استاد

• Software Quality
• AI-Supported Software Engineering
• Empirical Studies
• +۳ مورد دیگر

Stefan Wagner is a full professor of software engineering at the Technical University of Munich (TUM), where he leads the Chair of Software Engineering within the Informatics Heilbronn 3 department. He earned his PhD in computer science from TUM and has established himself as a leading researcher in software engineering with a unique interdisciplinary background combining computer science and psychology. Dr. Wagner's research spans multiple areas of software engineering including software quality, human factors, AI-based software engineering, automotive software, and empirical studies. His work often bridges theoretical foundations with practical applications, particularly in the automotive domain and AI-assisted development. He has published over 130 peer-reviewed scientific articles and authored the book 'Software Product Quality Control.' His recent publications demonstrate a growing focus on AI integration in software engineering, with particular attention to large language models, empirical validation of AI-assisted development practices, and the human aspects of these emerging technologies. There's also a strong thread of research on automotive software systems, technical debt, and software quality measurement. 2022 Class of IEEE Computer Society Distinguished Contributors Senior member of IEEE and ACM Best Full Paper Award, ACM/IEEE International Symposium on Empirical Software Engineering and Measurement 2020 Best Paper Award, EAI International Conference on Cognitive Computing and Cyber Physical Systems 2020 Keynote at the International Conference on Software Quality 2020 Google Research Award 2009 Dr. Wagner actively mentors students and early-career researchers, with several frequent co-authors on his publications likely representing his advisees. His research has been supported by various funding sources enabling his work on automotive software, AI in software engineering, and empirical studies. He serves on the editorial boards of IEEE Software, Empirical Software Engineering, and the Journal of Systems and Software, contributing significantly to the academic community. His research group appears to focus on several key areas including AI-assisted software development, automotive software systems, and empirical software engineering methods. The group maintains active collaborations with industry partners, particularly in the automotive sector, and engages in interdisciplinary research bridging computer science with psychology and human factors.

Bob De Schutterمشاهده پروفایل

استاد

• Game Design
• Gerontology
• Human-Computer Interaction
• +۳ مورد دیگر

Bob De Schutter is a Professor at Northeastern University with a joint appointment in Khoury College and the College of Arts, Media and Design (CAMD), where he coordinates the Game Science and Design program. As founder of Lifelong Games, he pioneers gerontoludic design—a framework challenging ageism in gaming by creating meaningful, emotionally resonant experiences for older adults that prioritize playfulness over utilitarian 'brain training' applications. De Schutter holds a PhD in Communication Science and a Master's degree in Arts. His educational journey began with childhood game development, leading to groundbreaking work that bridges academic research and practical design. His formal training informs his player-centered approach, emphasizing iterative design with diverse aging populations to create inclusive gaming experiences. His research revolutionizes game design for aging populations through three core pillars: gerontoludic design (extending the MDA framework with age-specific aesthetics), AI-supported accessibility (adapting interfaces to physical/cognitive needs), and gaminiscing—using games to evoke personal memories and foster intergenerational connection. He challenges the gaming industry's youth-centric focus by demonstrating how games preserve cultural heritage (e.g., Brukel's WWII narratives) and support cognitive/social well-being in later life through immersive storytelling. De Schutter's publication history reveals a consistent trajectory from foundational theory (2011-2016) to applied innovation (2015-2017), with increasing emphasis on virtual reality and procedural generation. His work consistently argues that games for older adults must prioritize emotional depth and meaningful play rather than reductionist 'cognitive training,' while addressing systemic ageism in game development pipelines and industry practices. His scientific recognition includes: Gold medal at the Serious Play Awards for Brukel De Schutter actively mentors students through Northeastern's co-op program and project-based courses, integrating real-world development into education. As coordinator of the Game Science and Design program, he shapes curriculum that blends technical skills with creative design, emphasizing portfolio development. His advocacy extends to industry leadership through the International Game Developers Association and IndieCade, where he promotes inclusive design standards. He leads Lifelong Games, a research lab producing award-winning titles like Brukel and Cardistry. The lab collaborates with students (e.g., Brandon Lyman, Reina Chan) and faculty like Prof. Chris Barney on projects merging machine learning with storytelling to create personalized memory-driven games. Current initiatives include Restless (procedural generation for diverse narratives) and scaling Cardistry's AI-generated 'gaminiscing' cards, with plans to expand the lab's capacity for student hires and game production.

Aimee A. Kaneمشاهده پروفایل

دانشیار

• Organizational Behavior
• Group and Team Processes
• Knowledge Transfer
• +۵ مورد دیگر

Dr. Aimee A. Kane holds the Donahue Chair in Management and serves as an Associate Professor of Management at the Palumbo-Donahue School of Business, Duquesne University. Her interdisciplinary research examines group and team processes, with recent work exploring how AI influences collaboration. She teaches courses on management, organizational behavior, and leadership at undergraduate, graduate, and executive levels. Dr. Kane earned her Ph.D. and M.S. in Organizational Behavior and Theory from Carnegie Mellon University's Tepper School of Business and a B.A. in Spanish from Duke University. Her educational background reflects her interdisciplinary approach to organizational studies. Her research focuses on identifying processes that enable those separated by boundaries (social, informational, technological) to collaborate effectively. She employs various methodologies including small group experiments, automated text analysis, social network analysis, questionnaires, and interviews. Recent work explores how AI influences collaboration and decision-making in teams, with publications extending into 2025. Her research spans knowledge transfer, team receptivity to newcomers, boundary spanning, and language processes in groups. Dr. Kane's recent publications demonstrate a focus on AI collaboration, emotional contagion in online environments, and language analysis in group settings. Her work shows consistent progression in methodology sophistication and interdisciplinary integration across psychology, computer science, and organizational behavior. Most Valuable Paper (MVP) Co-Winner, Group Dynamics: Theory, Research and Practice, 2023 Best Article Award, Small Group Research, 2019 Dean's Award for Excellence in Research, 2023 Dean's Award for Excellence in Teaching, 2022-2023 William and Helen Lyons Faculty Fellowship in Management, 2022 Harry W. Witt Faculty Fellowship in Management, 2018-2021 Dr. Kane serves as an Associate Editor at Group Dynamics: Theory, Research and Practice and on editorial boards of Academy of Management Discoveries and Small Group Research. At Duquesne University, she serves on the Faculty Senate Executive Committee and previously served as an Assembly Member from 2020-2024. She played a key role in university initiatives including the COVID Health and Safety Task Force responsible for the COVID-19 Dashboard and served for 9 years on the Institutional Review Board (IRB), receiving the Eugene P. Beard Outstanding Service Award in 2021. Dr. Kane leads research on knowledge transfer, computer-supported collaboration, team receptivity to newcomers, boundary spanning, and language & group processes. Her work has been supported by grants from the Army Research Office, National Science Foundation, and the A.J. and Sigismunda Palumbo Charitable Trust. She has developed teaching materials including the case study 'Stranded in the Nyiri Desert' and conducted webinars on remote collaboration during the pandemic.