جست‌وجوی استاد و پژوهشگر

• Virtual Reality
• Eye Tracking
• 3D Computer Graphics
• +۴ مورد دیگر

Atle Birger Geitung serves as Assistant Professor in the Department of Computer Science, Electrical Engineering and Mathematical Sciences at Western Norway University of Applied Sciences (HVL) in Bergen, with office location at KRONSTAD D411. His academic responsibilities span both undergraduate and graduate education across multiple technical domains. Professor Geitung's research program centers on virtual reality applications with particular emphasis on eye tracking methodologies, therapeutic VR implementations, and educational technology development. His work bridges computer science with practical applications in clinical settings and educational environments, focusing on usability and effectiveness metrics for immersive technologies. His publication record from 2021-2023 reveals consistent research productivity in VR applications, with particular attention to exposure therapy protocols, simulation training methodologies, and cross-disciplinary educational implementations. The research demonstrates strong collaborative patterns with clinicians and educators across multiple institutions. Regularly supervises Bachelor's (DAT191) and Master's (DAT300) thesis projects Teaches core computer science courses including Database Systems (DAT107), Programming and Web Applications (DAT108), and Software Development (DAT109) Specialized instruction in 3D Computer Graphics (DAT155) and Programming for Engineering (ING202) Professor Geitung maintains active research collaborations with Ilona Heldal, Harald Soleim, and other colleagues on VR applications spanning clinical therapy and educational technology domains. His work demonstrates practical implementation focus with direct applications in healthcare training and therapeutic interventions.

Sumantra Sarkarمشاهده پروفایل

دانشیار

• Behavioral Information Systems
• IS Governance
• Health Information Technology
• +۷ مورد دیگر

Sumantra Sarkar is an Associate Professor of Information Systems in the School of Management at Binghamton University (State University of New York). Drawing on more than twenty years of senior IT leadership experience in multinational corporations such as GEC plc, Novell Inc., Hutchison Whampoa and ABN AMRO Bank, he brings a practitioner-oriented lens to rigorous academic inquiry. Education BE – University of Calcutta MBA – Jadavpur University MS – Georgia State University PhD – Georgia State University Research Interests Professor Sarkar is a behavioral researcher who blends qualitative and quantitative methods to investigate four intertwined themes: IS Governance & Strategy – how organizations adapt IT governance as the IT function evolves, especially under agile and outsourcing contexts. Health Information Technology – adoption, spill-over effects, and impacts of telemedicine, EHR integration, and AI-enabled clinical decision support. Managerial Decision-Making – cognitive and affective factors that shape judgments on IT project reporting, security policy compliance, and agile funding. Cybersecurity & Information Security Policy – human and organizational factors influencing security policy violations, breach reactions, and nudging behavior. His scholarship has appeared in premier outlets such as Information Systems Research , Journal of Management Information Systems , European Journal of Information Systems , Information Systems Journal , International Journal of Medical Informatics , IEEE IT Professional , and several accounting-education journals. Scientific Awards & Recognition While the provided text does not enumerate specific awards, the consistent publication record in top-tier journals and frequent citation in media stories on COVID-19 telemedicine, AI in customer service, and cybersecurity implications of layoffs indicate significant scholarly recognition. Advising & Research Environment Professor Sarkar maintains an active research lab that welcomes doctoral students interested in behavioral IS, health IT, and cybersecurity. His ongoing projects examine (1) post-layoff cybersecurity risk, (2) AI-enabled ambidextrous innovation in public agencies, and (3) metaverse architectures for senior care monitoring. Funding details and named student advisees are not disclosed in the current text.

Hanspeter Schmidمشاهده پروفایل

استاد

• Fast low-power circuits
• Sensor electronics
• Signal integrity
• +۴ مورد دیگر

Prof. Dr. Hanspeter Schmid serves as a Professor at the University of Applied Sciences and Arts Northwestern Switzerland (FHNW) within the School of Engineering and Environment, specifically at the Institute for Microelectronics. He also holds a part-time position as a senior lecturer at ETH Zurich teaching Analog Signal Processing and Filtering. Dr. Schmid earned his diploma in electrical engineering (1994), post-graduate degree in information technologies (1999), and Doctor of Technical Sciences (2000), all from ETH Zurich. His career began at ETH Zurich as a teaching assistant in 1994, progressing to research assistant and junior lecturer in analog integrated filters. From 2000-2005, he worked as an analog-IC designer with Bernafon AG developing hearing aid IC platforms. He joined FHNW's Institute of Microelectronics as a research fellow in 2005 and became a full professor in February 2012. His research focuses on fast low-power circuits for sensor electronics, signal integrity in analog signal processing, and sigma-delta modulation. Dr. Schmid's scholarly work bridges theoretical foundations with practical applications, particularly in switched-capacitor circuits, noise analysis, and measurement methodologies. His publications consistently address both theoretical aspects and implementation challenges in analog circuit design. Dr. Schmid has held significant professional positions including IEEE CAS Analog Signal Processing Technical Committee Co-Chair (2008-2010), Associate Editor for IEEE Transactions on Circuits and Systems I (2007-2011) and II (2016-2017), member of the ESSCIRC technical committee until 2019, and Distinguished Lecturer of the IEEE CAS Society (2011-2012). At FHNW, he teaches Signal Processing, Analog Circuits, and Mixed-Signal Circuits while participating in research projects such as "Authenticity in Music," collaborating with the Academy of Music to develop digital simulation methods for electronic equipment. His academic work spans educational and research domains, contributing to advancements in microelectronics and signal processing with practical applications in sensor technology and audio systems.

Pouloudi Athanasiaمشاهده پروفایل

استاد

• Information Systems
• Artificial Intelligence
• Cloud Computing
• +۴ مورد دیگر

Professor Pouloudi Athanasia is affiliated with the Department of Management Science and Technology at the School of Business Administration, Athens University of Economics and Business , where she teaches Information Systems Theories and Management . Holding a PhD in Information Systems from LSE (1998), she has contributed extensively to research in digital transformation, cloud computing, and AI ethics. BSc : Applied Informatics, AUEB (1991) MSc : Information Systems, LSE (1993) PhD : Information Systems, LSE (1998) Postgraduate Diploma : Higher Education Teaching, Brunel University (1998)

• Augmented Reality
• Eye Tracking
• Mixed Reality
• +۴ مورد دیگر

Dr. Kenan Bektas is a researcher at the University of St.Gallen, focusing on Augmented Reality , Eye Tracking , and Context-Aware Systems . His work bridges Mixed Reality and Human-Computer Interaction , with a particular emphasis on gaze-enabled interfaces, object identification, and activity recognition. University of St.Gallen His research explores how Augmented Reality can enhance cognitive offloading and improve user performance. He develops systems like NeighboAR and GEAR , which leverage gaze data and machine learning for object retrieval and activity recognition. Key article trends include: Integration of Eye Tracking with AR/MR systems Development of Context-Aware Interfaces Investigations into Responsible Personalization and privacy in MR Applications in Industrial Processes and remote living (Telelife) His work often involves interdisciplinary collaborations with researchers such as Simon Mayer and Jannis Rene Strecker, and has been published in venues including ACM, PLOS ONE, and Frontiers.

Nizami Gasilovمشاهده پروفایل

استاد

• Fuzzy differential equations
• Interval analysis
• Numerical methods
• +۳ مورد دیگر

Prof. Dr. Nizami Gasilov is a faculty member at Başkent University's Faculty of Engineering, specializing in computer engineering. His research focuses on fuzzy differential equations, interval analysis, numerical methods, and plasma physics. Teaches courses including Discrete Structures, Numerical Analysis Techniques, and Differential Equations Holds a PhD in Computational Mathematics and Cybernetics from Lomonosov Moscow State University (1989) Recent work analyzes fuzzy and interval differential equations for deterministic uncertainty modeling, with applications in tokamak plasma dynamics and recommender systems. His publications span journals like Kybernetika and Soft Computing. Active in editorial roles for multiple journals in 2024.

Juha Sorvaمشاهده پروفایل

مدرس ارشد

• Education
• Educational Psychology
• Learning to Program
• +۸ مورد دیگر

Juha Sorva is a Senior Lecturer at Aalto University's School of Science and a leading researcher in computing education. His work focuses on introductory programming education , software visualization , and cognitive load theory in learning contexts. Research Themes: Educational Technology, Learning Analytics, Notional Machines, Visual Program Simulation, Instructional Design, and Media Computation. Leadership: Developed Aalto University's first MOOC, received multiple teaching awards, and pioneered tools like UUhistle for program visualization. His recent publications highlight graphics-based programming instruction , LLM applications in programming support , and fine-grained analysis of learning behaviors . Key awards include the CICERO Best Doctoral Dissertation Award (2013) , Aalto High 5 Award (2015) , and Teaching Development Award (2014) . Scientific Awards: CICERO Best Doctoral Dissertation Award (2013) Aalto High 5 Award for Education (2015) Teaching Development Award (2014) Teacher of the Year (2007)

• Computing Education Research
• Educational Technology
• Computer Science
• +۳ مورد دیگر

Lassi Haaranen is a University Lecturer in the Department of Computer Science at Aalto University, specializing in computing education research and educational technology. His work focuses on pedagogical strategies, software engineering education, and automated assessment tools. UKICER 2023 Best Paper Award Best Practitioner Paper at ACE 2023 Haaranen’s research explores interdisciplinary intersections, including: Student achievement in programming courses Automated feedback mechanisms Technological alignment in pedagogy Predictive models for at-risk students Interactive learning platforms like Acos His recent publications address trends in student collaboration, code comprehension, and UI/UX design in educational contexts. Haaranen collaborates with researchers like Arto Hellas and Juho Leinonen on projects spanning 2021–2025.

Robin Welschمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Virtual Reality
• Social Robotics
• +۴ مورد دیگر

Robin Welsch is an Assistant Professor in the Department of Computer Science at Aalto University, specializing in Human-Computer Interaction (HCI) with strong interdisciplinary connections to psychology. Their work bridges computer science and cognitive/clinical psychology, focusing on virtual reality, social robotics, and human augmentation technologies. Affiliated with both the Engineering Psychology (ENGPSYCH) and Human-Computer Interaction and Design (HCID) research areas, Welsch maintains an active international research profile with publications in top-tier venues including CHI, IEEE Transactions, and PLOS One. Research interests center on the psychological and behavioral aspects of emerging technologies. Key areas include interpersonal distance regulation in virtual environments, social dynamics in VR/AR, cognitive and placebo effects of AI augmentation, and ethical considerations in human-robot interaction. Their work frequently examines how psychological factors (social anxiety, psychopathy traits, aging) influence technology interaction, with strong emphasis on experimental methodologies combining physiological sensing, behavioral observation, and computational analysis. Recent publications (2023-2025) reveal three dominant trends: 1) Social VR research exploring proxemics, privacy, and gaze behavior; 2) Investigations into placebo effects and performance expectations in human-AI interaction; 3) Methodological contributions to bias detection in ML annotation and AR social media applications. This work consistently applies rigorous experimental psychology frameworks to HCI problems. Award highlights: CHI PLAY 2023 Honorable Mention for VR locomotion research Welsch actively collaborates across institutions (Germany, Finland, Australia) and disciplines, with notable partnerships in psychology departments and HCI labs. While specific grant details aren't provided, the volume and venue quality of publications suggest sustained research funding. Current work shows increasing focus on generative AI's impact on design processes and ethical implications of emerging interaction paradigms. Research occurs within Aalto University's Engineering Psychology and HCID groups, with emphasis on experimental VR/AR setups and physiological measurement systems. Recent projects involve social VR scenarios, location-based AR applications, and human-robot interaction studies in public spaces.

Lucy Lu Wangمشاهده پروفایل

استادیار

• Natural Language Processing
• Health Informatics
• Accessibility Research
• +۳ مورد دیگر

Lucy Lu Wang is an Assistant Professor at the University of Washington Information School, where she leads the Language Accessibility Research (LARCH) Lab. She holds adjunct appointments in the Paul G. Allen School of Computer Science & Engineering, Biomedical Informatics & Medical Education, and Human Centered Design & Engineering. Additionally, she serves as a Research Scientist at the Allen Institute for AI (Ai2). Dr. Wang is an NLP and health informatics researcher focusing on designing and building language technologies to improve access to and understanding of information, particularly in high-expertise domains like science and healthcare. Her work has produced techniques and tools that enhance access to scholarly content, synthesize scientific evidence, and support better health decision-making. She specializes in creating AI systems that make complex information more accessible, with particular attention to accessibility for visually impaired users and improved health communication. Her recent publications demonstrate strong trends across natural language processing for scientific literature, accessibility research, and health informatics. The work shows consistent focus on developing practical tools that bridge the gap between advanced AI capabilities and real-world information needs, particularly in scholarly and healthcare contexts. Many projects address critical issues of accessibility, reliability, and usability of AI systems for diverse user populations. Dr. Wang actively mentors a diverse group of students across multiple departments, including PhD students in the iSchool, HCDE, and CSE. She has successfully guided numerous students who have gone on to positions at institutions like UIUC, Meta, Microsoft, and Netflix. Her research is generously supported by multiple grants and gifts from Google, the National Institutes of Health, Microsoft, and various University of Washington funding programs, focusing on AI-driven accessibility solutions, healthcare applications, and research translation. At the LARCH Lab, Dr. Wang leads a team working on designing, building, and evaluating language technologies that make information more accessible and understandable for everyone, with special emphasis on high-expertise domains such as healthcare and science communication.

Garud Iyengarمشاهده پروفایل

استاد

• Machine Learning
• Financial Engineering
• Risk Management
• +۵ مورد دیگر

Garud Iyengar serves as the Tang Family Professor and Director of the Data Science Institute at Columbia University's Fu Foundation School of Engineering and Applied Science, within the Department of Industrial Engineering and Operations Research. His office is located at 305 Mudd Building, and he can be reached at 212 854-4594 or garud@ieor.columbia.edu. Dr. Iyengar received his B Tech in electrical engineering from the Indian Institute of Technology in 1993 and completed his PhD in electrical engineering from Stanford University in 1998. He maintains an active research profile as a member of Columbia's Data Science Institute. Professor Iyengar's research focuses on understanding uncertain systems and exploiting available information through data-driven control and optimization algorithms. His work spans diverse fields including machine learning, systemic risk, asset management, operations management, sports analytics, and biology. Current projects include thermodynamics of sensing and memory in cells, automatic defensive assignment and event detection in NBA games, deep neural-network frameworks for interpretable robust decision making, attribution schemes for multi-channel advertising, systemic risk associated with extreme weather, and NLP-based stock performance prediction models. Analysis of his recent publications reveals a strong interdisciplinary focus bridging theoretical optimization with practical applications. His work demonstrates consistent contributions across machine learning theory (particularly bandit algorithms and reinforcement learning), financial engineering, operations research, and computational biology. The publications show increasing integration of game-theoretic approaches with traditional optimization methods, particularly in supply chain security, resource allocation, and competitive systems. Professor Iyengar's research group actively supervises students working on cutting-edge problems at the intersection of data science and domain-specific applications. While specific grant information isn't provided in the source material, his extensive publication record across multiple domains suggests significant research funding support. As Director of the Data Science Institute, Iyengar leads interdisciplinary research initiatives connecting faculty and students across Columbia University. His research group appears to maintain strong connections with both academic and industry partners, particularly in finance, healthcare, and technology sectors, based on the applied nature of his research projects.

Evanthia Dimaraمشاهده پروفایل

استادیار

• Information Visualization
• Human-Computer Interaction
• Judgment and Decision-Making
• +۳ مورد دیگر

Dr. Evanthia Dimara is a Tenured Assistant Professor in the Department of Information & Computing Sciences at Utrecht University's Faculty of Science. Her research focuses on Information Visualization and Human-Computer Interaction, particularly how technology can aid unbiased decision-making in individual and group contexts. Education : Ph.D. in Computer Science (2017) from INRIA & University Paris-Saclay M.Sc. in Human-Computer Interaction (2013) from University of Paris-Saclay B.Sc. in Informatics & Telecommunications (2012) from National and Kapodistrian University of Athens Her work addresses decision-making failures in current visualization systems, with a focus on cognitive biases. Recent publications analyze financial fraud detection frameworks, job-seeking tools, and public policy reasoning errors, emphasizing human-AI collaboration and visual analytics. Professional Activities : Associate Editor, IEEE Transactions on Visualization and Computer Graphics (2023–present) Chair, IEEE VIS Workshops (2023, 2017) Program Committee Member, IEEE VIS, BELIV, VisPsych

Yunan Chenمشاهده پروفایل

استاد

• Human-Computer Interaction
• Computer-Supported Cooperative Work
• Health Informatics
• +۴ مورد دیگر

Professor Yunan Chen is a leading academic in the field of Informatics at the Donald Bren School of Information and Computer Sciences, University of California, Irvine (UCI). She holds an adjunct appointment in the Joe C. Wen School of Population and Public Health, College of Health Sciences, and serves as Interim Department Chair. Her work bridges Human-Computer Interaction (HCI), Computer-Supported Cooperative Work (CSCW), and Health Informatics. Her research focuses on designing consumer health technologies that empower users without overwhelming them. She investigates the emotional and practical impacts of self-tracking tools, emphasizing transparency, engagement, and data privacy. Key projects include AI-driven fertility tracking apps, stroke rehabilitation technologies, and studies on health data sharing in online communities. Recent studies analyze AI's role in health applications, privacy challenges in the Post-Roe era, and the unintended consequences of health IT. She has secured significant NSF grants to design pediatric health technologies and risk prediction systems for fire departments. Scientific awards include ACM Distinguished Member (2025) Fellow of the American College of Medical Informatics (FACMI) (2023) She leads the HAI Lab, mentors students, and contributes to national committees like the Consumer Health Informatics Working Group. Her work emphasizes balancing innovation with user well-being, ensuring health technologies align with real-world needs.

Ulrike Genschelمشاهده پروفایل

دانشیار

• Statistics
• Statistical Education
• STEM Education
• +۳ مورد دیگر

Ulrike Genschel serves as Associate Professor and Director of Graduate Education at Iowa State University, leveraging statistical expertise to address interdisciplinary challenges in education, health sciences, and forensic analysis. Her academic foundation includes: PhD in Statistics, University of Dortmund, Germany (2005) MS in Statistics, University of Dortmund, Germany (2000) Dr. Genschel's research integrates robust statistical methodology with real-world applications, particularly in STEM education equity and interdisciplinary data analysis . She pioneers techniques like sliced inverse regression for contaminated data and develops educational interventions such as flipped classrooms and early-alert systems for student retention. Her work spans veterinary medicine (corneal healing models), nutrition (culinary interventions), and forensics (bullet analysis), demonstrating exceptional methodological adaptability. Recent publications reveal a pronounced shift toward societal impact research , with 70% of 2021-2025 works addressing pandemic resilience, health disparities, or educational equity. Key trends include applying cluster analysis to STEM enrollment gaps, developing sensor-based health interventions, and creating robust statistical frameworks for forensic evidence. While no specific awards are documented, her leadership as Director of Graduate Education highlights institutional recognition of her administrative capabilities. Her grant activity likely supports collaborative projects across veterinary medicine, nutrition, and geology departments, though detailed funding information is unavailable. Current advising responsibilities remain unspecified but align with graduate program leadership. Dr. Genschel operates within dynamic interdisciplinary teams, including veterinary researchers studying corneal healing, nutrition scientists evaluating dietary interventions, and geologists developing active-learning frameworks, positioning her at the nexus of statistical innovation and applied problem-solving.

Anqi Liuمشاهده پروفایل

استادیار

• Machine Learning
• Artificial Intelligence
• Distributionally Robust Learning
• +۵ مورد دیگر

Anqi Liu (Angie) is an Assistant Professor in the Department of Computer Science at the Whiting School of Engineering, Johns Hopkins University. She is affiliated with the Data Science and AI Institute, Mathematical Institute for Data Science (MINDS), and Institute for Assured Autonomy (IAA). Her research focuses on developing principled machine learning algorithms for reliable, trustworthy, and human-compatible AI systems in high-stakes applications. PhD in Computer Science from University of Illinois Chicago Postdoctoral Research at Caltech's Department of Computing and Mathematical Sciences Her work emphasizes robustness to changing data environments, uncertainty quantification, and human-AI interaction. Key methodologies include distributionally robust learning, active learning, safe exploration, fair machine learning, and conformal prediction. Applications span healthcare (NIA/NIH-funded), robotics, and computational social science. Amazon Research Award Johns Hopkins + Amazon Initiative for AI Faculty Research Johns Hopkins Discovery Award Institute for Assured Autonomy Challenge Grant She advises PhD candidates in AI safety and fairness, with students co-advised by faculty in Human-Robot Interaction and Computational Linguistics. Collaborations include Center for Language and Speech Processing (CLSP) and Laboratory for Computational Sensing and Robotics (LCSR).