Mariano Scazzariello is a Lecturer at KTH Royal Institute of Technology, Sweden, affiliated with the School of Electrical Engineering and Computer Science and the Department of Network and Systems Engineering. He teaches the course 'Network Systems with Edge or Cloud Datacenters (IK2227)'. His research focuses on advanced networking topics including machine learning in networks, high-speed packet processing, network emulation, and software-defined networking innovations. His work spans contributions to network emulation tools like Kathará and Megalos, stateful packet processing at terabit scales, and leveraging large language models (LLMs) for network configuration and vulnerability detection. Recent research emphasizes low-latency protocols (e.g., SRv6/DetNet integration) and GPU-centric networking on commodity hardware. Mariano’s publications (2020–2025) highlight expertise in network function virtualization, ASIC-based switching, and optimizing network configurations through AI-driven approaches. He has pioneered frameworks for evaluating routing protocols and virtualizing large network scenarios at scale.
Theo Damoulas is a Professor of Machine Learning at the University of Warwick with a joint appointment in the Department of Computer Science and Statistics. He is a Turing AI Fellow (2021-2026) through UK Research and Innovation, an ELLIS member, and a Visiting Professor at New York University's Center for Urban Science and Progress (CUSP). He founded and leads the Warwick Machine Learning Group and has directed major projects at The Alan Turing Institute including Project Odysseus and the London Air Quality project. Education includes: PhD in Probabilistic Multiple Kernel Learning (University of Glasgow, 2009) MSc in Informatics (Distinction, University of Edinburgh, 2004) MEng in Mechanical Engineering (1st Class, University of Manchester, 2003) His research focuses on probabilistic machine learning and Bayesian statistics, emphasizing the integration of structural priors, spatiotemporal dependencies, physical laws, and causal relationships. Key applications include Digital Twins, urban science, and computational sustainability. His work advances robust and scalable inference methodologies for complex real-world systems. Publications demonstrate strong emphasis on Bayesian methods, spatiotemporal modeling, and uncertainty quantification, with applications spanning battery modeling, urban mobility, federated learning, and causal inference. Recent work shows increased focus on physics-informed models, federated learning frameworks, and causal abstraction techniques. Major scientific awards: Turing AI Acceleration Fellowship (2021-2026) Best Paper Awards (Wilkes 2024, AISTATS 2022, IEEE ICMLA 2010) ACM SIGMOD Most Reproducible Paper (2017) Dissertation Award (Classification Society 2012) Teaching Excellence nominations (Warwick 2015-2017) He actively advises PhD students and secured significant grants including the £multi-million Turing AI Fellowship. Current doctoral researchers investigate federated learning, causal inference, and spatiotemporal modeling. He leads the Warwick Machine Learning Group, a cross-departmental team developing foundational ML methods for scientific and societal challenges.
Professor Winston Hsu is a distinguished faculty member in the Department of Computer Science and Information Engineering at National Taiwan University, where he has served as a full professor since 2015. He is the co-director of the Communications and Multimedia Laboratory (CMLab) and founder of the MiRA (Multimedia indexing, Retrieval, and Analysis) research group. Additionally, he serves as the Founding Director for NVIDIA AI Lab at NTU, the first such lab in Asia. Professor Hsu received his Ph.D. in Electrical Engineering from Columbia University in 2007 under the supervision of Professor Shih-Fu Chang. Prior to his academic career, he was a founding engineer and research manager at CyberLink Corp., now a public image/video software company. National Taiwan University (2007-Present): Professor (2015-Present), Assistant/Associate Professor (2007-2015) MobileDrive (2021-2024): CTO and Vice President (Joint Venture between Foxconn and Stellantis) IBM TJ Watson Research Center (2016-2017): Visiting Scientist Microsoft Research Redmond (2014): Visiting Researcher Columbia University (2007): Ph.D. in Electrical Engineering Professor Hsu's research focuses on machine learning, computer vision, large-scale image and video search and recognition, and embedded AI. His work spans from fundamental research in visual recognition to practical applications in automotive systems, medical imaging, and e-commerce. He has pioneered work in disguised face recognition, low-resolution face hallucination, 3D model search, and virtual try-on systems. His current research emphasizes Embodied AI, integrating perception, action, and learning technologies for applications in automotive and robotics domains. His research group has produced numerous influential publications, particularly in top computer vision and multimedia conferences like CVPR, where they won first place in the Disguised Face Recognition competition in 2018. Their work spans diverse application areas including security, medical diagnostics, automotive systems, and e-commerce solutions, demonstrating strong translation from academic research to real-world impact. IBM Research Pat Goldberg Memorial Best Paper Award (2018) First Place, IARPA Disguised Faces in the Wild Competition (CVPR 2018) Best Brave New Idea Paper Award, ACM Multimedia 2017 NVIDIA AI LAB Award (First in Asia, 2016) First Place, MSR-Bing Image Retrieval Challenge (2013) World's Top 2% Scientists (2023) Professor Hsu actively mentors students and researchers, with his group consistently recruiting PhD students, postdocs, and research assistants. He has successfully bridged academia and industry through multiple collaborations, including his role as CTO at MobileDrive (a joint venture between Foxconn and Stellantis) from 2021-2024. His research has been supported by significant industry partnerships with Microsoft, IBM, and NVIDIA, as well as government grants from Taiwan's Ministry of Science and Technology. His laboratory, the Communications and Multimedia Laboratory (CMLab), maintains strong industry connections and focuses on cutting-edge research in visual AI. The lab has produced numerous award-winning projects and maintains active collaborations with global technology companies, particularly in the automotive and consumer electronics sectors.
James C. Hoe is Professor of Electrical and Computer Engineering at Carnegie Mellon University (College of Engineering). He is on sabbatical at MangoBoost and directs research in computer architecture, reconfigurable computing, and high-level hardware design. Education Ph.D., Electrical Engineering and Computer Science, MIT (2000) M.S., Electrical Engineering and Computer Science, MIT (1994) B.S., Electrical Engineering and Computer Science, UC Berkeley (1992) Research Interests Professor Hoe’s work spans computer architecture , reconfigurable computing , FPGA architectures , and high-level hardware synthesis . His group created the CoRAM abstraction for virtualized FPGA computing and leads efforts in power-efficient accelerators, in-network computing, and security-oriented FPGA systems. Scientific Awards IEEE Fellow (2013) Intel Outstanding Researcher Award (2021) Research Funding & Projects Intel / VMware Crossroads 3D-FPGA Academic Research Center – co-leading exploration of FPGA roles in future datacenters. DARPA BRASS program ($2.7 M, 4 years) – ensuring long-lived software systems remain robust to resource changes. Pigasus open-source IDS – world’s fastest FPGA-accelerated intrusion-detection system (100 Gb/s on one server). Labs & Teams He heads activities within the Computer Architecture Lab at Carnegie Mellon (CALCM) , supervising graduate researchers on CoRAM++, SPIRAL autotuning, and FPGA overlays for stream processing.
Richard Jochelson serves as Dean of Law at the Faculty of Law, University of Manitoba (Robson Hall), a position he has held since July 1, 2016. Previously, he taught criminal law for 10 years at the University of Winnipeg. Dr. Jochelson holds a Ph.D. in Law from Osgoode Hall Law School at York University, an LLM from the University of Toronto Faculty of Law, an LL.B. with Gold Medal from the University of Calgary Faculty of Law, and a B.Sc. in Zoology with Distinction from the same institution. He completed his legal training as a clerk at the Alberta Court of Appeal and Court of Queen's Bench before working at a major Canadian law firm. Dr. Jochelson's research program centers on critical issues in criminal justice and constitutional law, with primary interests in police powers jurisprudence, sexual regulation (particularly obscenity and indecency law), jury systems and representativeness, and legal pedagogy. His interdisciplinary approach bridges law with sociology and psychology, bringing empirical and theoretical rigor to legal scholarship. His work consistently addresses social justice concerns, examining how vulnerable populations interact with the justice system and how concepts like risk, precaution, and visibility shape legal decision-making. He has developed a distinctive methodology combining doctrinal analysis with empirical research on judicial behavior and jury decision-making. His recent publications reveal evolving scholarly priorities that respond to contemporary legal challenges. The 2025 article "Morbid Matters" addresses medical assistance in dying within federal corrections, while his 2024 works on youth terrorism cases and agnotology demonstrate expansion into new interdisciplinary territories. His longstanding commitment to police powers scholarship continues with "Ancillary Police Powers in Canada" (2024). The pandemic period saw significant contributions to understanding digital justice, mental health in legal education, and remote court proceedings. His criminal law scholarship maintains focus on jury representativeness, particularly regarding Indigenous inclusion following Bill C-75's elimination of peremptory challenges. Students' Teacher Recognition Award (CATL) - 2018 Dr. Jochelson has secured multiple SSHRC Insight Grants as both Principal and Co-investigator, demonstrating his ability to lead interdisciplinary research teams. His mentorship extends to junior academics and students, with several publications co-authored with emerging scholars. He has built significant research infrastructure, notably assembling nearly 40 interdisciplinary scholars across Canada for Robsoncrim.com, which has elevated the Criminal Law Edition of the Manitoba Law Journal to prominence as one of Canada's preeminent criminal law publications. As Dean of Law, Dr. Jochelson provides leadership in academic governance and legal education innovation. His service includes extensive committee work on academic affairs, workload policy, and hiring/tenure committees. His commitment to universal design principles informs both his teaching approach and administrative leadership, emphasizing accessibility and student-centered pedagogy that allows flexible evaluation methods tailored to individual learning preferences.
Yvonne Rogers is a Professor of Interaction Design and Director of the UCL Interaction Centre (UCLIC), with a joint appointment as Deputy Head of the Department of Computer Science at University College London. She joined UCL in 2011 after holding professorships at the Open University (2006-2011) and Indiana University (2003-2006). Her pioneering work spans ubiquitous computing, interaction design, and human-computer interaction, with a current focus on human-centered AI. She co-authored the definitive 'Interaction Design' textbook (6 editions, 300,000+ copies) and serves as CTO of LetThink.com. Research interests center on designing technologies that enhance human cognition and daily activities: Ubiquitous Computing: Augmenting learning/work activities through pervasive technologies Human-AI Interaction: Developing AI systems that enhance human decision-making Health Technologies: Creating VR therapies and ADHD support systems Community Resilience: Designing tools for environmental monitoring and sustainable practices Publication analysis reveals three dominant trends: (1) VR applications for mental health (emotion regulation, ADHD support), (2) AI systems for cognitive augmentation, and (3) community-centered tools for healthcare/environmental challenges. Recent work demonstrates strong emphasis on vulnerable populations including children with ADHD, older adults, and postoperative patients. Major scientific recognition includes: International Member, National Academy of Engineering (2024) ACM SIGCHI Lifetime Research Award (2022) Royal Society Robin Milner Medal (2022) Royal Society Fellowship (2022) Microsoft Outstanding Collaborator Award MRC Suffrage and Science Award (2020) Triple Fellow status (ACM, BCS, CHI Academy) Advises PhD students including Leon Reicherts, Sheena Visram, and Tu Duong. Secured major grants including EPSRC Dream Fellowship on ageing/computing and led the Intel Collaborative Research Institute on Sustainable Connected Cities (2012-2018). Directs UCLIC research center and previously established the Pervasive Interaction Lab at Open University.
Antony Franklin is an Associate Professor and Head of the Department of Computer Science and Engineering at the Indian Institute of Technology Hyderabad (IITH), India. He leads the Networked Wireless Systems (NeWS) Lab and is actively involved in 5G research, wireless networks, and cybersecurity. He earned his Ph.D. from IIT Madras in 2010. Education: Ph.D. in Computer Science and Engineering, IIT Madras, 2010 Research Interests: His research spans wireless networks , 5G systems , mobile edge computing , low-latency transport protocols , and cybersecurity . He focuses on next-generation mobile systems, especially 5G, aiming to meet the demands of ultra-low latency, high data rates, and quality of experience for services like IoT, autonomous driving, and VR. He has been involved in developing testbeds and prototypes to validate real-world performance of 5G technologies, including network slicing, LTE-WiFi integration, and edge computing. Scientific Awards: Best Academic Demo Award, IEEE COMSNETS 2018 Second Best Paper Award, IEEE ANTS 2017 Grants & Projects: Network Slice Life-cycle Management for 5G Mobile Networks – SPARC, MHRD (2019–2021) DNS/IPv6 for IoT Security – NASSCOM (2018–2019) CCRAN: Energy Efficiency in Cloud RAN – Intel India (2018–2021) End-to-End 5G Test-Bed – DoT, GoI (2018–2021) M2SMART Smart Cities – SATREPS (2018–2023) Ultra-Reliable Low Latency Protocols – STINT, Sweden (2017–2018) Low Latency 5G Protocols – SERB ECR (2016–2019) Lab & Team: He leads the NeWS Lab (Networked Wireless Systems) at IITH, which focuses on 5G, wireless networks, and IoT systems. The lab is actively involved in developing real-world testbeds and publishing in top-tier conferences and journals.
Hossam Hassanein is a Professor and Director of the School of Computing at Queen's University. He received his B.Sc. in Electrical Engineering from Kuwait University in 1984, M.Sc. in Computer Engineering from the University of Toronto in 1986, and Ph.D. in Computing Science from the University of Alberta in 1990. He joined Queen's University School of Computing in 1999 and has established himself as a leading researcher in telecommunications and networking. Dr. Hassanein's research interests span wireless sensor networks, mobile ad hoc networks, edge computing, Internet of Things (IoT), radio resource management, and data-centric networks. His seminal contributions include pioneering work on WSN planning, load-balanced routing protocols, and energy-efficient network designs. He has championed research in IoT, developing frameworks for smart spaces that use contextual information to enhance IoT applications in healthcare, transportation, and infrastructure. His recent publications (2023-2025) demonstrate a strong focus on cutting-edge areas including extreme edge computing, vehicular networks, and AI/ML integration in networking. Research trends show increasing emphasis on practical applications in telesurgery, digital twins, and industrial IoT, addressing challenges in resource allocation, task offloading, and real-time processing in constrained environments. Dr. Hassanein has received numerous recognitions for his work: Fellow of the IEEE Queen's University School of Graduate Studies Award for Excellence in Graduate Student Supervision (2015) Multiple best paper awards from top international conferences As founder and director of the Telecommunications Research Lab (TRL), Dr. Hassanein has supervised over 75 students who have made substantial contributions in academia and industry. The TRL is one of Queen's largest research groups with extensive international collaborations. Dr. Hassanein has successfully attracted significant research funding from government and industry sources in the competitive telecommunications field. The Telecommunications Research Lab has developed innovative platforms including SPROUTS, a rugged sensor platform used in mining, steel manufacturing, and smart-grid monitoring. TRL's work has had significant impact in WSN planning, data dissemination, and resource reuse in wireless networks, with contributions featured in IEEE Wireless Communications Magazine.
Sishuai Gong is an Assistant Professor in the Department of Computer Science at the University of North Carolina at Chapel Hill, focusing on system reliability and security. His research bridges machine learning, software engineering, and computer architecture to address challenges in large-scale software systems. Education : Ph.D. in Computer Science from Purdue University (2025), B.S. in Computer Science from the University of Science and Technology of China (2019). Research Interests : System reliability and security, kernel concurrency testing, verified security modules, and machine learning for systems. He develops interdisciplinary techniques to identify and mitigate functional interference bugs in OS virtualization and latency-sensitive applications. Scientific Awards : Jay Lepreau Best Paper Award at OSDI (2024) Google Cloud Research Innovator (2024) Bilsland Dissertation Fellowship at Purdue (2024) Teaching : Offering COMP 790: Reliable and Secure Systems (Fall 2025) with a focus on empirical studies, static/dynamic analysis, and machine learning for systems. Course grading includes paper presentations (30%), class participation (30%), and research projects (40%).
David R. Koes is an Associate Professor in the Department of Computational and Systems Biology at the University of Pittsburgh, affiliated with the School of Medicine. He holds roles such as Associate Director of the Joint CMU-Pitt Computational Biology PhD Program (CPCB) and is involved in multiple graduate programs including Intelligent Systems and Computational Biomedicine. His research focuses on developing computational algorithms and systems for drug discovery, emphasizing open-source software and machine learning applications in biomedical data. Koes teaches courses like MSCBIO2025 (Bioinformatics Programming in Python) and MSCBIO2065 (Scalable Machine Learning for Big Data Biology). He has secured NIH funding (R35GM140753) and collaborated on projects with institutions like NVIDIA and Google Cloud. His lab develops tools such as GNINA, Pharmit, and 3Dmol.js, and actively contributes to open drug discovery initiatives. Education: PhD in Computer Science from Carnegie Mellon University (CMU). Research Interests: Leveraging computation and AI for drug design, molecular docking, pharmacophore modeling, and open science. Specific areas include developing scalable machine learning pipelines, virtual screening systems, and tools for 3D molecular analysis. Grants and Funding: Current NIH R35 grant and prior support from NSF, Relay Therapeutics, and others. His work emphasizes translating computational methods into practical drug discovery solutions. Lab and Teams: Directs a lab focused on computational drug discovery, collaborating with multiple academic and industry partners. Supervises graduate students and postdocs in projects spanning AI-driven drug design, molecular modeling, and software development.
Xing Gao is an Assistant Professor at the University of Delaware, affiliated with the Department of Computer and Information Sciences and jointly with the Department of Electrical and Computer Engineering. His office is located at 316B FinTech Innovation Hub on the STAR Campus. He holds a PhD from the College of William and Mary (2018) and a BS from Beijing Institute of Technology (2011). Research Interests: Cybersecurity in Software Supply Chain, Web 3, High-Performance Computing, Large Language Models, with a focus on Security, Cloud Computing, and Mobile Computing. Education: PhD | 2018 | College of William and Mary BS | 2011 | Beijing Institute of Technology His recent work explores cybersecurity vulnerabilities in cloud gaming services (CCS'22), container registries (USENIX-SEC'22), and software supply chains, with specialized attention to GPU cache attacks (USENIX-SEC'24) and Ethereum smart contracts (WWW'24). His research spans theoretical and applied aspects of system security, including CI/CD pipelines (CCS'24), SDN backdoors (INFOCOM'23), and hardware-level threats (ACSAC'21). Scientific Awards NSF CAREER Award (2024) NSF CRII Award (2020) NDSS Distinguished Poster Award (2016) He serves as Registration Chair for ACM/IEEE Symposium on Edge Computing (2023) and Publicity Co-Chair for IEEE Conference on Communications and Network Security (2022). He is actively involved as TPC Member in multiple top-tier conferences including USENIX Security (2026,2025), CCS (2026,2025,2024), and IEEE DSN (2024). He has also reviewed for journals like IEEE Transactions on Dependable and Secure Computing. Labs & Teams X-Lab at the University of Delaware, a research group focused on cybersecurity in emerging technologies.
Elahe Soltanaghai is an Assistant Professor in the Department of Computer Science and a Faculty Affiliate in Electrical and Computer Engineering at the University of Illinois Urbana-Champaign. She is also a 2022 NCSA Fellow and received her PhD in Computer Science from the University of Virginia (2019), MS in Computer Engineering from Sharif University of Technology (2014), and dual BS degrees in Computer and Information Technology Engineering from Amirkabir University of Technology (2011, 2013). PhD: University of Virginia, Computer Science, 2019 MS: Sharif University of Technology, Computer Engineering, 2014 BS (Computer Engineering): Amirkabir University of Technology, 2011 BS (Information Technology Engineering): Amirkabir University of Technology, 2013 Her research spans wireless sensing and communication, focusing on Millimeter-wave Radar Sensing (for automotive, mixed reality, structural monitoring), Machine Learning for Wireless Systems (adaptive sensing/communication), Forest IoT (through-canopy biomass and soil sensing), Metaverse Technologies (gaze-based VR/AR), and Low-Power Backscatter Communication (WiFi/power-line tags). She directs the Wireless, Sensing & Embedded Networked Systems (iSENS) Lab and co-directs the Illinois Center for IoT. Her work bridges wireless networking with cyber-physical sensing , emphasizing environmental monitoring (e.g., wildfire fuel detection via radar tags) and human-computer interaction (e.g., gaze-tracking in VR). Recent articles include innovations in passive radar profiling , through-canopy biomass characterization , and integrated communication-sensing protocols . Scientific Awards: Google Research Scholar Award (2022) N2Women Rising Star (2021) ACM SIGMOBILE Dissertation Award (2020) EECS Rising Stars (2019) NCSA Faculty Fellowship (2023) Best Demo Runner-up, IPSN (2023) Teaching Excellence Award (2023) Grants: NASA FireTech Program Grant (2025) NSF Grant for Radar-based Perception (2024) Insper-Illinois Grant for VR Research (2024) Keysight Research Gifts (2022, 2023) T-Mobile Research Gift (2022)
Olga Papaemmanouil is a Professor of Computer Science at Brandeis University and Senior Associate Provost for Academic Affairs and Curriculum. She is affiliated with the Michtom School of Computer Science and the Volen National Center for Complex Systems. Ph.D. in Computer Science, Brown University (2008) M.S. in Information Systems, University of Economics and Business, Athens (2001) B.S. in Computer Science and Informatics, University of Patras, Greece (1999) Her research focuses on data management, integrating machine learning with cloud databases, query optimization, and performance prediction. She has pioneered techniques for interactive data exploration, reinforcement learning in query scheduling, and economic models for database provisioning. Recent publications highlight her work on learned query optimizers , deep reinforcement learning for database operations, and platform-independent neuroscience data interfaces . NSF Career Award (2013) Amazon Research Award (2019) Huawei Innovation Research Awards (2017, 2018) SIGMOD Best Demonstration Award (2015) Paris Kanellakis Fellowship (2002) She has secured multiple NSF grants and developed systems like Neo (learned query optimizer) and XCloud (performance management for cloud data services). Her work bridges database systems and machine learning for scalable data analytics.
Professor Rainer Böhme is a prominent academic in the field of IT security and privacy at the University of Münster's School of Business and Economics, Department of Information Systems. He also holds a professorship for Security and Privacy at the University of Innsbruck's Institute of Computer Science. His research spans multiple dimensions of digital security, with particular expertise in steganography, digital forensics, privacy-enhancing technologies, and the economic aspects of cybersecurity. Dr. Böhme earned his Doctoral Degree from TU Dresden's Faculty of Computer Science in 2008, following studies in Communications, Economics and Computer Science at Technische Universität Dresden and Université Paris XII. His academic journey includes positions as Assistant Professor at the University of Münster (2010-2015), Postdoctoral Fellow at the International Computer Science Institute in Berkeley (2009-2010), and Scientific Staff at TU Dresden's Chair of Privacy and Data Security. His research interests focus on steganography and steganalysis, digital forensics, privacy-enhancing technologies, security and usability, economic and behavioral aspects of information privacy, virtual currencies, and the economics of information security. His work bridges technical security mechanisms with economic and behavioral considerations, creating a unique interdisciplinary approach to cybersecurity challenges. Analysis of his recent publications reveals a strong trend toward the economics of security, particularly regarding blockchain technologies, cryptocurrency, and privacy valuation. His work increasingly examines the intersection of technical security mechanisms with market dynamics, regulatory frameworks, and user behavior. The research spans theoretical game-theoretic models, empirical studies of user behavior, and practical applications in digital forensics and privacy protection. Program Co-Chair, Financial Cryptography and Data Security (2015) Program Co-Chair, New Security Paradigms Workshop (NSPW) (2015) General Chair, 8th International Conference on IT Security Incident Management & IT Forensics (2014) Organizer and Program Co-Chair, 1st Workshop on Bitcoin Research (2014) Associate Editor, Electronic Commerce Research (since 2013) Associate Editor, EURASIP Journal on Information Security (since 2013) Professor Böhme has supervised multiple Master's theses in Information Systems, including work on static code analysis for smart contracts, remote maintenance protocol security, and application protection requirements in retail banking. His research is supported by significant grants from the German Federal Ministry of Research, Technology and Space, the DFG, and the EU FP7 program, with projects focusing on digital forensics, privacy-enhancing technologies, and cryptocurrency crime prevention. He leads the IT Security Research Group at the University of Münster, which investigates theoretical and applied aspects of information security with particular emphasis on the economic dimensions of security decisions.
Rosa I. Arriaga is an Associate Professor in the School of Interactive Computing at Georgia Institute of Technology, where she directs the Ubicomp Health and Wellness Lab. Her research focuses on Human-Computer Interaction (HCI), Ubiquitous Computing, and mHealth, with applications in mental health, chronic disease management (e.g., diabetes), and pediatric asthma care. She designs technology systems to improve patient engagement, continuity of care, and clinician-patient communication. Research Areas: Chronic Care Management PTSD Therapy Support (PECSS project) Diabetes Management (DUCSS project) mHealth System Design AI in Healthcare Key Projects: PECSS: Leverages ubiquitous computing and machine learning to address clinical challenges in PTSD therapy. DUCSS: A diabetes management system to streamline patient education and self-monitoring, particularly for underserved populations. ZenVR: A virtual reality system for meditation education, validated through longitudinal studies. Teaching: Teaches undergraduate courses in HCI and graduate courses in Human-Centered Computing (HCC). Her Coursera course Intro to User Experience Design has over 50K learners. Grants & Partnerships: Funded by GT-Emory AI Humanity, American Diabetes Association, and Georgia Center for Diabetes Translation Research. Collaborations with Emory University, University of Rochester, and medical professionals. Labs & Teams: Leads the Ubicomp Health and Wellness Lab, fostering interdisciplinary research with graduate and undergraduate students focusing on health technology innovation.
