Parastoo Abtahi is an Assistant Professor in the Computer Science Department at Princeton University. She leads the Situated Interactions Lab (Ψ Lab) as part of the Princeton HCI Group, focusing on AR/VR and spatial computing. Prior to Princeton, she worked at Meta Reality Labs Research. PhD in Computer Science from Stanford University BSc in Electrical and Computer Engineering from University of Toronto (Engineering Science program) Her research explores wearable interactive technologies that augment human intelligence in physical contexts through: Input on-the-go: Low-effort, privacy-preserving multimodal interfaces Intelligent output: Timely, minimal multisensory systems Situated AI: Personalizable, predictable, safe physical-digital interaction Recent publications analyze: Drone-based haptic illusions for AR/VR Microgestures for mobile AR input Interactivity in explainable AI systems Temporal dynamics in VR haptics Awards include: 2025 Google Research Scholar Award CHI 2019 & 2018 Honorable Mentions She teaches courses like: COS 436: Human-Computer Interaction COS IW: AR Meets AI
Meng Wu is an Assistant Professor in the School of Electrical, Computer and Energy Engineering (ECEE) at Arizona State University, specializing in advanced optimization, control, and machine learning methods for integrating distributed energy resources (DERs) into power systems. Her work addresses critical challenges in power system planning, operations, stability, and electricity markets under high DER penetration. Education: Ph.D. in Electrical and Computer Engineering, Texas A&M University, 2017 M.Eng. in Electrical and Computer Engineering, Cornell University, 2011 B.Eng. in Electrical Engineering & Automation, Tianjin University, China, 2010 Research Interests: Dr. Wu's research focuses on DER integration through transmission-distribution coordination , spatio-temporal price forecasting , and optimal market participation strategies. Key areas include: Physics-guided machine learning for DER-penetrated distribution systems Computational algorithms for wholesale-distribution market coordination Dynamic modeling of DERs and composite loads for voltage stability Optimal bidding strategies for energy storage and DER aggregators Publication Trends: Her 2021-2024 publications reveal a concentrated effort on DER market integration using parametric programming and deep learning, with emphasis on real-time locational marginal price forecasting, transmission-distribution coordination, and degradation-aware energy storage operations. Scientific Awards: Best Paper Award, IEEE PES General Meeting (2021) Best Conference Paper Award, North American Power Symposium (2019) Invited Participant, US Frontiers of Engineering Symposium, NAE (2021) Advising and Grants: Dr. Wu mentors multiple PhD and Master's students, including recent graduates Zhongxia Zhang (PhD) and Sayyid Mohssen Sajjadi (MS). Her group secured PSERC funding for projects on DER aggregation and adaptive transmission-distribution modeling, with industry partnerships at ISO New England and Quanta Technology. Research Group: Leading an active research team at ASU, she collaborates with the Power Systems Engineering Research Center (PSERC) on DER integration challenges, advising students through FURI, MORE, and Barrett Honors College programs.
Toby Jia-Jun Li is an Assistant Professor in the Department of Computer Science and Engineering at the University of Notre Dame, where he leads the SaNDwich Lab. He also serves as the Director of the Human-Centered Responsible AI Lab in the Lucy Family Institute for Data & Society and is a Faculty Fellow at the Institute for Educational Initiatives (IEI). Previously, he was affiliated with Carnegie Mellon University's Human-Computer Interaction Institute (HCII) and GroupLens Research. Dr. Li's research spans the intersection of Human-Computer Interaction (HCI), End-User Software Engineering, Machine Learning (ML), and Natural Language Processing (NLP), with recent work focusing on addressing societal challenges in the future of work through human-AI collaborative approaches. His work has resulted in over 40 publications at premier venues including CHI, UIST, CSCW, ACL, and ICSE, with 8 papers winning Best Paper or Honorable Mention awards. His recent publications demonstrate a strong focus on human-AI collaboration across various domains, including code understanding, privacy, accessibility, and creative tools. The work shows a trajectory toward increasingly sophisticated integration of human-centered design with AI capabilities, particularly using large language models to enhance human productivity and address societal challenges. Google Research Scholar Award recipient Recipient of Yahoo! Fellowship ($100,000/year) Best Paper Award at UIST 2020 Best Paper Honorable Mention Award at CHI 2021 Best Paper Award at CSCW 2024 Best Paper Award at CHI 2025 Dr. Li actively mentors Ph.D. students and has established collaborations with Google, Microsoft Research, IBM Research, Adobe, Verizon, and J.P. Morgan. His research has been supported by NSF, Google Research Scholar Program, AnalytiXIN Initiative, Yahoo! InMind project, and J.P. Morgan. He is currently recruiting Ph.D. students and undergraduate researchers for his SaNDwich Lab, which focuses on developing interactive systems to empower individuals to create, configure, and extend AI-powered computing systems.
Jiliang Tang is an MSU Foundation Professor in the Department of Computer Science and Engineering at Michigan State University (MSU), part of the College of Engineering. He holds a PhD from Arizona State University (2015) and previously worked as a research scientist at Yahoo Research. His research focuses on graph machine learning, trustworthy AI, and applications in education and biology. He has received numerous awards, including the 2022 AI's 10 to Watch, IAPR J.K. Aggarwal Award, and NSF CAREER Award. Education: PhD in Computer Science, Arizona State University, 2015 (Advisor: Huan Liu) Research Interests: Graph Neural Networks (GNNs) and Deep Learning on Graphs Trustworthy AI: Safety, Robustness, and Fairness AI+X Applications: Education Technology and Biological Data Analysis His work bridges theoretical advancements and practical applications, with contributions to graph representation learning, privacy in generative models, and educational AI systems. Awards & Recognition: Over 8 best paper awards (or runner-ups) Rock Star Award from Association of Chinese Scholars in Computing Extensive media coverage for innovations in AI education and biology Grants & Projects: NSF CAREER Award (2019) for research on signed networks Co-PI on a $1.7M grant for 5G research Leadership in projects like DSE Lab and Data Science initiatives Labs & Teams: Directs the Data Science and Engineering (DSE) Lab at MSU, focusing on advancing AI for real-world challenges. The lab collaborates with industry leaders and publishes widely in top conferences (e.g., KDD, SIGIR, ACL).
Dr. Yayun Du is an Assistant Professor in the Department of Electrical and Computer Engineering at Vanderbilt University School of Engineering. She holds a Ph.D. in Robotics and System Control (Minor: Solid Mechanics) from UCLA (2022) and was a postdoctoral scholar at Northwestern University's Rogers Group through 2024. Current faculty at Vanderbilt University Ph.D. from University of California, Los Angeles Postdoctoral experience at Northwestern University Her research integrates bioelectronics and robotics through three core directions: 1) Developing multimodal wearable/implantable sensors for health monitoring, 2) Creating human-in-the-loop interaction systems using brain-computer interfaces, and 3) Applying machine learning to medical environment robotics. She has deployed four sensor types across seven hospitals globally, serving users from neonates to elderly patients. Dr. Du's recent publications focus on wireless bioelectronic devices ( PNAS ), sustainable sensor materials ( ACS Sustainable Chemistry & Engineering ), and agricultural robotics ( ICRA , IROS ). She serves as Associate Editor for ICRA 2025 and has received two Best Paper Award final nominations at IROS 2021. Finalist - Best Paper Award in Agri-Robotics (IROS 2021) Finalist - Best Paper Award in Robot Mechanisms and Design (IROS 2021) As head of the Du Group, she leads interdisciplinary research with applications in both healthcare and agricultural contexts, collaborating with Vanderbilt Institute for Surgery and Engineering (VISE) and clinical partners. Her work emphasizes deployable systems that transition from academic research to real-world implementation in medical and industrial environments.
Alan Stocker is a Professor in the Department of Psychology at the University of Pennsylvania, affiliated with the Neuroscience Graduate Group, Bioengineering Graduate Group, and Computational Neuroscience Initiative. His research focuses on understanding how prior beliefs and expectations shape visual perception, combining theoretical models with psychophysical and physiological experiments. Key areas include optimal inference frameworks, neural coding efficiency, and decision-making under uncertainty. Education: PhD in Physics (ETH Zurich, 2002); MSc in Biomedical Engineering and Materials Science (ETH Zurich, 1995). Prior appointments include postdoctoral work at New York University and ETH Zurich. Research Interests: Behavioral Neuroscience, Cognitive Neuroscience, Sensation and Perception. Specific projects explore statistical properties of visual environments, subjective expectations from past decisions, and neural computations underlying perception. Advising: Current advisees include Cheng Qiu (Postdoc), Ansh Soni, and Mengting Fang (Graduate Students). Courses taught: Perception, Visual Neuroscience, and Probabilistic Models in Perception and Cognition. Labs/Teams: Leads the Computational Perception and Cognition (CPC) Laboratory, emphasizing theory-driven experimentation. Collaborates widely across disciplines including bioengineering and electrical systems engineering.
Prof. Dr. Oliver Müller is a Professor at the Department of Philosophy, University of Freiburg, and serves as Vice Dean of the Faculty of Philosophy. His academic journey includes a doctorate from Humboldt University Berlin (2005) and a habilitation in Philosophy (2012). Müller leads research on Philosophical Anthropology, Philosophy of Technology, and Ethics, with a focus on human-machine interactions and Anthropocene ethics. He supervises doctoral and postdoctoral researchers across projects like livMatS and BrainLinks-BrainTools. Research interests span neuroethics, transhumanism, and socio-technological systems, emphasizing ethical frameworks for emerging technologies. Publications explore AI ethics, drone warfare, and phenomenological embodiment, reflecting interdisciplinary engagement with neuroscience and environmental philosophy. Honors include the MTZ Bioethics Award and Heisenberg Fellowship. Müller directs participatory discourse initiatives bridging art and science, fostering public engagement with technological ethics. His work advances critical dialogues on human enhancement and ecological responsibility in the digital age.
Lorin Schöni is a PhD candidate at ETH Zürich, actively contributing to the Security, Privacy and Society research group since October 2022. Concurrently, he serves as a Lecturer at the Department of Humanities, Social and Political Sciences, where he teaches the course Focus on the Human: Human-Centered Security and Privacy Lab (Autumn Semester 2025, Unit 851-0391-00L). His research focuses on human-centered approaches to cybersecurity , particularly through three key domains: Human-Computer Interaction - Investigating design decisions that influence user behavior in digital security contexts Extended Reality Applications - Developing immersive training systems for phishing prevention Usability Engineering - Creating intuitive security interfaces with explainable AI components Recent publications highlight his work at the intersection of autonomous motivation theory and personalized cybersecurity training , with notable presentations at top venues including CHI 2025 and SOUPS 2024. His research aims to transform security from a restrictive framework into a collaborative partnership between users and digital systems, as emphasized in his award-winning work on human-centered cybersecurity.
Howie Choset is a Professor of Robotics at the Robotics Institute, Carnegie Mellon University. He directs the Undergraduate Robotics Minor and leads the Biorobotics Laboratory, where his research focuses on snake robots, motion planning, and medical robotics. He is also affiliated with the Manufacturing Futures Institute. Ph.D., Mechanical Engineering, California Institute of Technology (1996) M.S., Mechanical Engineering, California Institute of Technology (1995) B.S.E., Computer Science and Engineering, University of Pennsylvania (1990) B.S., Economics, The Wharton School of Business (1990) Choset's research centers on robotics for confined and complex environments, particularly through the development of snake robots. His work integrates mechanism design, path and motion planning, and estimation to enable applications in surgery, manufacturing, infrastructure inspection, and search and rescue. He is a pioneer in medical robotics and has co-founded Medrobotics to commercialize minimally invasive surgical robots. His recent publications highlight a strong focus on ergodic exploration, multi-agent systems, motion planning under uncertainty, and medical robotics. Themes include optimizing robot trajectories for information gathering, solving complex path planning problems with dynamic obstacles, and advancing autonomous systems for disaster response and space exploration (e.g., the EELS robot for Enceladus). MIT Technology Review Top 100 Innovators under 35 (2002) Best Paper Award, RIA (1999) Best Paper Award, ICRA (2003) Best Paper, IEEE Bio Rob (2006) Best Video, ICRA (2011) Nominations for best papers at ICRA, IROS, and CLAWAR Choset has advised numerous students, many of whom have won top awards. His lab has received significant funding for robotics research, including projects in surgical robotics, additive manufacturing, and autonomous exploration. He is the lead author of the textbook Principles of Robot Motion and is actively involved in educational innovation through custom robotics labs. He leads the Biorobotics Laboratory at CMU, which develops advanced robotic systems like snake robots and the EELS (Exobiology Extant Life Surveyor) robot for NASA missions. The lab collaborates with industry and government agencies on applications ranging from surgery to space exploration.
Professor Michael C.L. CHAU serves as Professor and Deputy Area Head of Innovation and Information Management at The University of Hong Kong's Faculty of Business and Economics. He also holds the position of Associate Director at the HKU HKJC Centre for Suicide Research and Prevention, and serves on the HKU Senate and Court. His academic journey includes a Ph.D. in Management Information Systems from the University of Arizona and a B.Sc. in Computer Science (Information Systems) from the University of Hong Kong. Dr. Chau's research spans business analytics, artificial intelligence, web mining, fintech, smart health, and security informatics. His work focuses on applying data/text/web mining techniques to business, education, and social domains. He leads the Artificial Intelligence Research Group at HKU Business School, which has secured significant funding from the Hong Kong Research Grants Council, Food and Health Bureau, and other agencies for projects including 'The Invisible Hand in Crowdfunding' and 'Factors Moderating the Predictive Power of Social Media Sentiment on Stock Returns'. His publication portfolio includes over 150 articles in premier journals like MIS Quarterly, JMIS, and IEEE Transactions, with recent work exploring large language models, hate speech detection, and disaster-related social media analysis. His research demonstrates strong interdisciplinary connections across computer science, information systems, and business applications. INFORMS ISS Design Science Award (2020) IEEE ITSS Leadership Award in Intelligence and Security Informatics (2020) AIS Sandra Slaughter Service Award (2016) HKU Outstanding Young Researcher Award (2014) Faculty Research Postgraduate Supervision Award (2020 & 2025) Cited over 9,400 times (h-index = 47) Dr. Chau actively mentors doctoral students and has supervised numerous PhD graduates who now hold academic positions at institutions including Fudan University, Xi'an Jiaotong-Liverpool University, and the University of Maryland. His research grants portfolio demonstrates sustained funding success across diverse areas including blockchain, mental health applications, and social media analytics. The Artificial Intelligence Research Group he leads maintains strong industry connections through projects with Hong Kong Red Cross and the Hospital Authority.
Salim ROSTAMI is an Associate Professor at the IÉSEG School of Management in France, specializing in Operations Management. He holds a Ph.D. in Economics and Mathematics Sciences from KU Leuven (2019) and a Master’s in Engineering from KU Leuven (2013), alongside a Bachelor’s in Industrial Engineering from Ferdowsi University of Mashhad (2012). His research focuses on scheduling under uncertainty, project planning, combinatorial optimization, and healthcare logistics. Notable achievements include the 2016 2nd Best Conference Paper Award from the University of Valencia. Education: Ph.D., Economics and Mathematics Sciences, Operations Management, KU Leuven, Belgium (2019) Master, Engineering, Operations Research, KU Leuven, Belgium (2013) Bachelor, Engineering, Industrial Engineering, Ferdowsi University of Mashhad, Iran (2012) His work spans stochastic resource-constrained project scheduling, sequential testing of systems, and chemotherapy appointment scheduling. He has published widely in journals like the European Journal of Operational Research and Flexible Services and Manufacturing Journal. Teaching roles include courses on operations management and project management across undergraduate and graduate programs. Awards: 2016: 2nd Best Conference Paper Award, University of Valencia His research emphasizes practical applications in healthcare and project management, leveraging dynamic programming and metaheuristic algorithms. Collaborations include work with institutions like École des Mines de Saint-Étienne and KU Leuven.
Jean-Claude Besse is a Lecturer in the Department of Physics at ETH Zürich, specializing in superconducting circuits and quantum optics. His research focuses on quantum computing, microwave photonics, and artificial atoms. Research Interests: Besse works on the fabrication of superconducting circuits, modular quantum computing processors, and microwave quantum optics using artificial atoms. His work includes single-photon detection, parity measurements, entanglement stabilization, and quantum networking. He has developed technologies like high-fidelity multiplexed readout and tunable ZZ gates. Key Contributions: Besse led breakthroughs in non-destructive single-photon detection, deterministic remote entanglement, and loophole-free Bell inequality violations. His research enables error-corrected quantum communication protocols and scalable microwave quantum systems. Publications Trends: Recent articles emphasize modular quantum architectures, entanglement stabilization, and microwave photon engineering. Topics include cluster state generation, defect mode mitigation, and reinforcement learning for quantum feedback systems. Labs & Teams: Affiliated with the Laboratorium für Festkörperphysik at ETH Zürich, Besse contributes to advancing superconducting quantum technologies and microwave quantum optics.
John D Brennan is a Professor in the Department of Chemistry & Chemical Biology at McMaster University. He is affiliated with the Biointerfaces Institute and focuses on developing innovative biosensing technologies and functional nucleic acid-based assays. His research integrates materials science, biochemistry, and analytical chemistry to create practical diagnostic tools for healthcare applications. Key research areas include the design of DNA aptamers and DNAzymes for detecting biomarkers (e.g., eosinophil peroxidase, SARS-CoV-2 spike proteins), development of paper-based diagnostic platforms, and optimization of sol-gel materials for enzyme entrapment. His work emphasizes high-throughput screening, point-of-care testing, and CRISPR-based biosensing systems. Notable contributions include a rapid sputum-based assay for asthma biomarkers and a universal DNA aptamer for SARS-CoV-2 variants. His lab also explores functional nucleic acid circuits and their integration into scalable diagnostic devices. Brennan’s teaching includes advanced courses in analytical chemistry and biochemical assay development. His work has been featured in journals like *Angewandte Chemie*, *Analytical Chemistry*, and *ChemBioChem*, with a focus on translating fundamental research into practical clinical applications.
Elison Matioli is a Professor at the Institute of Electrical Engineering (STI) at EPFL and director of the POWERlab. He holds a B.Sc. in Applied Physics and Applied Mathematics from Ecole Polytechnique (France), a B.Sc. in Electrical Engineering from the University of São Paulo (Brazil), and a Ph.D. in Materials Science from the University of California, Santa Barbara. His postdoctoral research at MIT focused on electrical engineering and computer science. His research centers on advanced semiconductor devices, particularly GaN-based power electronics, microfluidic cooling systems, and nanotechnology innovations for high-power applications. Key areas include developing high-efficiency GaN transistors, optimizing power conversion systems, and exploring terahertz generation through nanoplasma switches. His work emphasizes integrating novel materials (e.g., diamond, LiNiO) and cooling solutions to enhance device performance and reliability. Publications highlight breakthroughs in GaN power devices, microfluidic integration for thermal management, and ultrafast switching technologies. His contributions span device physics, fabrication techniques, and energy-efficient systems, with applications in next-generation power electronics and renewable energy infrastructure.
James A. Evans is a Professor at the University of Chicago, where he serves as Director of the Knowledge Lab and Faculty Director of the Masters Program in Computational Social Science. He is also an External Professor at the Santa Fe Institute. His research bridges computational methods with social theory to analyze collective cognition, innovation, and knowledge production across science, technology, and broader societal domains. Director, Knowledge Lab Faculty Director, Masters Program in Computational Social Science External Professor, Santa Fe Institute Evans’s research explores how social and technical institutions shape discovery processes, utilizing machine learning, network modeling, and large-scale data analysis. His work spans fields like computational social science, sociology of science, and data science, focusing on team dynamics, peer review, and the global structure of scholarship. His recent publications examine team size effects on innovation, discursive influence in academia, and the interplay between tradition and novelty in research strategies. Articles trend toward interdisciplinary approaches combining social theory, computational methods, and science policy. Evans supports novel observatories for human understanding through crowdsourcing, sensor networks, and semantic modeling. He has received funding from the National Science Foundation, National Institutes of Health, and Air Force Office of Scientific Research, with findings featured in major media outlets like Nature , Science , and The New York Times .
