Matt Reynolds is a Professor in the Department of Electrical and Computer Engineering at the University of Washington, with an adjunct appointment at the Paul G. Allen School of Computer Science & Engineering. His research bridges wireless systems, RFID, and millimeter-wave imaging with commercial applications through multiple technology spin-offs. Education: Ph.D., MIT Media Lab, 2003 (Motorola Fellow) S.B. and M.Eng., Electrical Engineering and Computer Science, MIT Research Interests: Dr. Reynolds pioneers millimeter-wave sensing and imaging , RFID systems , and energy-efficient wireless communication , focusing on ubiquitous computing and embedded sensor networks . His work transforms theoretical physics of sensing into practical home monitoring and industrial applications, emphasizing real-world deployment of wireless systems. Scientific Awards: Six Best Paper Awards 2024 UW ECE Outstanding Teaching Award 2018 ACM Ubicomp 10-Year Impact Award 2019 ACM Ubicomp 10-Year Impact Award Technology Ventures: As co-founder of ThingMagic Inc (acquired by Trimble Navigation), Zensi (acquired by Belkin), SNUPI Inc (acquired by Sears), and current millimeter-wave imaging firm ThruWave Inc, he drives commercialization of research in home sensing and wireless power systems.
Minjoon Seo is an Associate Professor at KAIST AI, Korea Advanced Institute of Science and Technology. He holds a BS in Electrical Engineering & Computer Science from UC Berkeley and previously worked as a software engineer at Oracle. His research focuses on natural language understanding, large-scale end-to-end question answering, and multimodal AI systems combining language and vision. Research Interests: His work spans Natural Language Processing, Machine Learning, Deep Learning, and Language-Vision integration. He develops neural network architectures for machine comprehension and multimodal understanding, with applications in question answering systems and diagram interpretation. Publications: His research demonstrates a consistent focus on multimodal AI systems, with recent works advancing neural approaches to machine comprehension and diagram understanding. Publications show strong emphasis on NLP-CV integration and practical applications in healthcare and education. Awards: Best Paper Nomination at UbiComp 2014 for BiliCam research Professional Activities: Maintains active open-source contributions through GitHub repositories related to question answering systems and NLP research. Co-founded Config Intelligence while maintaining academic position.
Flora Salim is a Professor in the School of Computing Technologies at RMIT University. She serves as co-Deputy Director of the RMIT Centre for Information Discovery and Data Analytics (CIDDA) and an Associate Investigator of the ARC Centre of Excellence in Automated Decision Making and Society. Her research focuses on human behavior modeling, machine learning with time-series and spatio-temporal data, and edge AI applications in IoT and wearables. Flora has secured over $10M in research funding from ARC, industry partners, and government bodies. Notable awards include the 2021 PACM IMWUT Distinguished Paper Award, 2019 Humboldt-Bayer Fellowship, and RMIT's 2018 Research Impact Award. She leads the CRUISE research group and has held visiting professorships at the University of Kassel and University of Cambridge. Editorial roles: Associate Editor of PACM on IMWUT, Area Editor of Pervasive and Mobile Computing Steering Committee member of ACM UbiComp Her work bridges ubiquitous computing and machine learning, with applications in urban analytics, mobility, and health monitoring. Recent projects include self-supervised learning for multimodal data and forecasting with heterogeneous time-series. Supervision areas: Deep learning for sensor data, explainable AI, and wearable-based emotion sensing Teaching programs: Master of Artificial Intelligence and Master of Data Science
Rosa I. Arriaga is an Associate Professor and Associate Chair of Graduate Studies at the School of Interactive Computing , Georgia Institute of Technology. As director of the Ubicomp Health and Wellness Lab , she pioneers technology solutions for chronic disease management and mental health support through human-computer interaction principles. NSF grant recipient for PTSD treatment systems ReplicCHI award winner Google Scholar profile: https://scholar.google.com Her research bridges mHealth systems with behavioral intervention frameworks, creating scalable solutions for asthma management , diabetes care , and autism support . With over 140 publications, her work emphasizes user-centered design and real-world implementation challenges. Recent publications demonstrate growing focus on AI integration in mental health, including synthetic therapy datasets and explainable AI frameworks. Her administrative work involves improving graduate student wellness programs and career navigation structures. NSF Grant : $1.2M for PTSD treatment systems ReplicCHI Award : Methodological validation of asthma SMS interventions Academic Leadership : Graduate Affairs policy frameworks Arriaga's lab explores medical making practices, particularly during pandemic responses, and develops ubiquitous computing solutions for low-resource settings . She teaches user experience design through Georgia Tech's Coursera platform, which has reached over 50,000 learners globally.
Hao-Chuan Wang is an Associate Professor in the Department of Computer Science at the University of California, Davis, with affiliations in the Electrical and Computer Engineering Graduate Program. He previously served as a faculty member at National Tsing Hua University, Taiwan, from 2012 to 2018, where he was promoted to tenured Associate Professor. He holds a Ph.D. in Information Science from Cornell University and has conducted postgraduate research at Carnegie Mellon University and Academia Sinica. His research lies at the intersection of Human-Computer Interaction (HCI), Computer-Supported Cooperative Work (CSCW), and Human-Centered AI, with a strong emphasis on collaborative systems, hybrid and remote work, video-mediated communication, and inclusive design for education and wellbeing. He employs mixed-method, human-centered approaches to design systems that support knowledge transfer, equity, and social interaction in distributed environments. His recent publications focus on AI-supported learning, fairness in group work, reflective tools, and cross-cultural interactions with large language models. These works are published in top-tier venues such as CHI, CSCW, CUI, and WWW, reflecting his impact in the HCI community. His scientific contributions have been recognized with several awards, including Best Student Paper at The Web Conference 2021, Best Demo Award at Augmented Humans 2021, Distinguished Paper Award at PACM IMWUT 2018, and multiple Honorable Mention awards at CHI and CSCW. Best Student Paper Award, The Web Conference (WWW) 2021 Best Demo Award, Augmented Humans International Conference 2021 PACM IMWUT Distinguished Paper Award, Ubicomp 2018 Honorable Mention Paper Award, CHI 2015 Honorable Mention Paper Award, CHI 2018 Honorable Mention Paper Award, CSCW 2018 Best Poster Award, ITS 2006 Wang actively contributes to the academic community through leadership roles in ACM SIGCHI, including serving as VP Finance (2024–2027), Workshop Chair for CHI 2025–2026, and Associate Editor for the Journal of Information Science and Engineering. He has advised numerous students whose research appears in major conferences, and his work bridges computer science, communication, design, and learning sciences, reflecting a deeply interdisciplinary and impactful scholarly profile.
Pascal Knierim is a researcher in the Department of Computer Science at Ludwig Maximilian University of Munich, Germany. He completed his PhD at the same institution in 2020 with a dissertation titled "Enhancing interaction in mixed reality: the impact of modalities and interaction techniques on the user experience in augmented and virtual reality." His research focuses on human-computer interaction, particularly in virtual and augmented reality environments, with an ORCID identifier 0000-0001-9578-9953. Knierim's research interests span virtual reality, augmented reality, mixed reality, ubiquitous computing, and extended reality systems. He has made significant contributions to understanding user interaction in immersive environments, privacy considerations in VR/AR, biometric identification using thermal imaging, and universal interaction frameworks. His work often combines technical innovation with user-centered design principles, resulting in numerous publications at top-tier venues including CHI, MUM, UbiComp, and IEEE Pervasive Computing. Recent work has explored content blocking in extended reality, social anxiety in VR proxemics, user awareness of privacy permissions, and framework development for ubiquitous research preservation. Knierim has collaborated extensively with researchers such as Thomas Kosch, Florian Alt, and Albrecht Schmidt, forming a productive research group within LMU Munich's computer science department. He has also contributed to the academic community through editorial roles for major conferences including Mensch und Computer 2023 and the 22nd International Conference on Mobile and Ubiquitous Multimedia (MUM 2023), demonstrating leadership within his research community. His research demonstrates a strong commitment to both theoretical advancement and practical applications of immersive technologies, with particular attention to user experience, privacy, and accessibility considerations.
Prof. Dr. Andreas Bulling is Full Professor of Computer Science at the University of Stuttgart , leading the Collaborative Artificial Intelligence research group at the Institute for Visualization and Interactive Systems. He is also a founding director of the Stuttgart ELLIS Unit and serves on multiple prestigious boards including IEEE Transactions on Visualization and Computer Graphics . Education: MSc in Computer Science (KIT), PhD in Information Technology (ETH Zurich) Research Interests: Human-Computer Interaction, Eye Tracking, Wearable Computing, Computer Vision, and Privacy-Preserving AI Scientific Leadership: UbiComp Steering Committee member, ACM ETRA General Chair (2020), and extensive editorial/guest editor roles Key Awards: ERC Starting Grant (2018), Henriette Herz Scout (2024), and multiple best paper awards at CHI, ETRA, and UIST Technical Contributions: Developed datasets (LPW, VisRecall++), created novel methods for gaze estimation, mental face reconstruction, and saliency prediction in visualizations His work bridges AI and Human-Computer Interaction with applications in immersive systems and healthcare technologies.
Ke Sun is an Assistant Professor in the EECS Department at the University of Michigan, Ann Arbor. His research develops intelligent, deployable sensing systems for mobile, wearable, and IoT ecosystems, with applications in HCI, cybersecurity, health monitoring, and robotics. His work has been implemented in commercial devices like Amazon Echo and Google Home. Research spans: HCI for Mobile/IoT : Touch/gesture sensing (VSkin, RFCanvas) Cybersecurity : Privacy protection against eavesdropping (EveGuard, StealthyIMU) Health/Environmental Sensing : Vital sign monitoring (LoEar), activity logging (EgoADL) Wireless/Robotics : mmWave radar navigation (milliEgo), acoustic temperature sensing (VECTOR) Publication trends show consistent focus on acoustic/wireless sensing (13/15 papers), cybersecurity (5/15), and cross-modal AI fusion. Recent work explores adversarial ML attacks and LLM vulnerabilities. Awards include: Google Ph.D. Fellowship (2023) UbiComp Distinguished Paper Award (2023) ACM SenSys Best Poster Runner-up (2020) ACM-ICPC Asia Gold Medal (2015) Industry collaboration includes three internships at Amazon Lab126 where his research influenced Echo device development. He serves on program committees for ACM MobiSys/SenSys and organized the ICLR ML for IoT Workshop.
Stephan Sigg is a Professor at Aalto University's Department of Information and Communications Engineering, where he leads the Ambient Intelligence research group . His research focuses on algorithm design for distributed systems, including RF sensing, context-based security, and device-free activity recognition. He serves on editorial boards for Elsevier Journal on Computer Communications and Springer Personal and Ubiquitous Computing , and actively contributes to conferences like IEEE PerCom and ACM Ubicomp. Research Interests: Dr. Sigg specializes in proactive computing, distributed adaptive beamforming, mobile crowdsourcing, and secure spontaneous device pairing. His work bridges wireless communication, machine learning, and ubiquitous systems to develop context-aware solutions for IoT environments. Publication Trends (2019-2025): Recent works demonstrate a strong emphasis on RF-based sensing (WiFi/mmWave radar/RFID) for human activity recognition, 5G-integrated sensing, privacy-preserving AI (federated learning), and healthcare applications. Multimodal approaches combining radar, video, and physiological signals are prominent. Awards: Summa cum laude dissertation honors in Computer Science (2008) VDI-Nordhessen Outstanding Dissertation Prize (2009) Research Leadership: Leads the Ambient Intelligence group exploring RF sensing, edge AI, and human-computer interaction. Collaborates extensively with industry on 5G/6G applications and IoT security. Supervises doctoral candidates in wireless systems and ubiquitous computing.
Afra Mashhadi is an Associate Professor in the Division of Computing & Software Systems at the University of Washington Bothell within the School of Science, Technology, Engineering & Mathematics. She concurrently serves as an Adjunct Associate Professor at the University of Washington Information School (i-School) and holds affiliate positions at the e-Science Institute and Center for Studies in Demography and Ecology (CSDE). Dr. Mashhadi co-chairs the steering committee for the Responsible AI Systems and Experiences Centre (RAISE) and is recognized as a leading advocate for ethics and diversity in computing. Educational Background: Ph.D. in Computer Science, University College London, London, England Her research pioneers computational behavioral modeling through ethical AI frameworks, developing mathematical models that leverage digital data and machine learning to analyze societal phenomena across spatial scales and human behavioral dynamics. This work bridges ubiquitous computing, algorithmic fairness, and privacy-preserving systems with direct applications in social computing and responsible technology deployment. Recent publications demonstrate a cohesive research trajectory focused on ethical AI challenges, particularly examining social reasoning in LLMs, bias quantification in co-authorship networks, fairness benchmarking for generative models, and privacy-preserving federated learning. These works appear in premier venues including ACM WSDM, ICTIR, IEEE DCOSS, and ACM JCSS, reflecting her leadership at the AI-society intersection. Scientific Awards: Sr. Chief Ronald G. Gamboa Endowment Faculty Fellowship Award Scholarly Service: Program Chair: ICWSM 2021, SocInfo 2019 Tutorial Chair: IC2S2 Broadening Participation Chair: ACM Ubicomp 2023 Senior Committee: FAccT, CHI, WebSci, ICWSM Dr. Mashhadi maintains active research affiliations with the Responsible AI Systems and Experiences Centre (RAISE), e-Science Institute, and Center for Studies in Demography and Ecology (CSDE), where she leads interdisciplinary projects connecting computational methods with social science and ethical frameworks through European collaborations and industry deployments including WebSummit trials.
Shahriar Nirjon is an Associate Professor in the Department of Computer Science at the University of North Carolina at Chapel Hill. His research focuses on Embedded Intelligence, developing end-to-end systems that make resource-constrained real-time and embedded sensing systems capable of learning, adapting, and evolving. Dr. Nirjon received his Ph.D. from the University of Virginia in 2014. Before joining UNC Chapel Hill in 2015, he worked as a Research Scientist at HP Labs (2014-2015) and as a Research Intern at Microsoft Research (Summer 2013) and Deutsche Telekom Lab (Summer 2010). His primary research interest is Embedded Intelligence, with recent works broadly categorized into embedded deep learning and multi-modal sensing techniques. Applications of his research span wearables and implantables, long-term monitoring and control systems, smart home environments, and mobile health solutions. Dr. Nirjon's research bridges theoretical foundations with practical implementations, resulting in systems that have real-world impact in healthcare, safety, and everyday computing. His work has been highlighted in prominent media outlets including IEEE Spectrum, The Economist, New Scientist, and BBC. Dr. Nirjon's publication record demonstrates a strong focus on mobile computing systems, embedded sensor networks, and wireless technologies. His recent work shows increasing integration of machine learning and artificial intelligence with embedded systems, particularly in healthcare applications. There's a clear trajectory toward more sophisticated, energy-efficient systems capable of on-device intelligence, with growing emphasis on privacy-preserving techniques and real-world deployments in healthcare settings. Best Paper Award, Challenges in AI and Machine Learning for IoT (AIChallengeIoT '20) Best Presentation Award, Pervasive and Ubiquitous Computing (Ubicomp '20) Best Paper Award, Distributed Computing in Sensor Systems (DCOSS '19) Best Presentation Award, Vehicular Networking Conference App Contest (VNC '18) Best Demo Runner Up, Vehicular Networking Conference App Contest (VNC '18) Best Paper Nomination, Embedded Wireless Systems and Networks (EWSN '17) Best Demo Runner Up Award, Embedded Networked Sensor Systems (SenSys '16) Best Paper Award, Mobile Systems, Applications, and Services (MOBISYS '14) Best Paper Award, Real-Time and Embedded Technology and Applications Symposium (RTAS '12) Dr. Nirjon has advised numerous PhD students including Chong Shao (Google), Shiwei Fang (Assistant Professor at Augusta University), Tamzeed Islam (Research Staff at Amazon), Bashima Islam (Assistant Professor at Worcester Polytechnic Institute), Seulki Lee (Assistant Professor at UNIST, Korea), and Yubo Luo (Black Sesame Technologies Inc.). He currently advises Mahathir Monjur, Zhenyu Wang, and Louie Lu who are in various stages of their PhD programs. His research is supported by significant grants including an NSF CAREER award ($561K), an NSF SCH grant ($941K), and multiple other NSF-funded projects totaling over $2 million. His active projects include Audio Privacy, Pedestrian Safety, IoT Data Privacy, and HVAC Acoustic Fingerprinting. Dr. Nirjon leads research in the Embedded Intelligence Lab at UNC Chapel Hill, where his team develops cutting-edge technologies in mobile computing, embedded systems, and wireless networks. His work spans multiple domains including healthcare (mobile health systems), safety (pedestrian safety applications), and smart environments (smart homes). He collaborates with researchers across disciplines, particularly in healthcare through the Carolina Health Informatics Program (CHIP), and is actively involved in the Be-A-Maker (BeAM) network of makerspaces at UNC.
David Buján Carballal is a Lecturer and Researcher at the Faculty of Engineering, University of Deusto, and a member of the MORElab 'Envisioning Future Internet' Research Group. He is affiliated with DeustoTech (Deusto Institute of Technology) and the Telefónica Deusto Chair. His academic career spans software engineering, semantic web technologies, and digital transformation. BSc in Computing, Faculty of Engineering, University of Deusto MSc in e-Business, University of Deusto PhD in Computer Sciences, University of Deusto Dr. Buján's research focuses on Digital Transformation for smart communities and rural areas, Blockchain Technology applications in traceability, and Cybersecurity solutions for connected industries. His work addresses Grid Computing , Semantic Web , and Context Modelling for tourism applications. Recent publications highlight his contributions to digital ecosystems for rural innovation, blockchain-based energy traceability, and cybersecurity frameworks for connected industries. His projects include EU-funded AURORAL , HAZITEK BLOCKCHAINFOOD , and collaborations with Accenture, Telefónica, and BBK. Scientific Contributions: Member of Deustek Research Group Program Committee member for CAEPIA workshops Article reviewer for IoT, Ubicomp, and Semantic Web conferences Dr. Buján has participated in numerous national and international conferences on semantic technologies, grid computing, and digital ecosystems. He contributes to academic governance through curriculum development and teaching innovation initiatives at the Faculty of Engineering.
Asif Salekin is an Assistant Professor at Arizona State University's School of Biological and Health Systems Engineering (SBHSE), where he directs the Laboratory for Ubiquitous and Intelligent Sensing (UIS Lab). He holds additional affiliations with the School of Medicine and Advanced Medical Engineering, serves as a Research Affiliate at the Mayo Clinic, and maintains affiliations with SUNY Upstate Medical University and Syracuse University. Having joined ASU as a tenure-track Assistant Professor in August 2024, he previously served as an Assistant Professor at Syracuse University from 2020-2024. His research spans Human-Centered Computing, Machine Learning, Cyber-Physical Systems, and Usable Sensing Security and Privacy within Ubiquitous Computing, with a core focus on integrating computing solutions to advance health assessment and monitoring. His work addresses natural distribution shifts in human-centered applications, algorithmic fairness and bias mitigation, multimodal integration, interpretability of ML inference in healthcare, scalable edge computing solutions, trustworthiness in human-centered sensing, and security and privacy challenges in IoT applications. His publications demonstrate a strong trend toward health-focused applications of ubiquitous computing, particularly in mental health assessment, substance use disorder monitoring, childhood speech disorders, and chronic disease management. His recent work shows increasing emphasis on robustness, fairness, and privacy in human-centered AI systems, with significant contributions to stress detection, emotion privacy protection, and reliable health monitoring solutions. IAAI Deployed Application Award (2021) Graduate Student Award for Outstanding Research (UVA CS Department, 2018) Nominated for Best Paper Award (AsthmaGuide, Wireless Health 2016) CUSE Grant: Innovative & Interdisciplinary Research Grant (Syracuse University, 2021) Dr. Salekin actively advises multiple PhD students in Computer Science and Biomedical Engineering programs, with several successful doctoral graduates. His research has been funded by two National Science Foundation grants and three National Institutes of Health grants. He currently serves as an Associate Editor for the Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT) and the UbiComp conference. His work spans multiple labs and collaborative teams including the UIS Lab at ASU, Mayo Clinic research teams, and collaborations with medical professionals at SUNY Upstate Medical University.
Barry Alan Brown is a Professor at the Department of Computer Science, Faculty of Science, University of Copenhagen. He previously served as Research Director at Mobile Life (2011–2017) and Associate Professor at UCSD’s Department of Communication (2007–2011). PhD in Sociology, University of Surrey (1997) His research focuses on Human-Centered Computing , examining digital technology use in everyday contexts, including leisure technologies , autonomous vehicles, and gig economy platforms. Recent work analyzes food delivery labor in India and self-driving car interactions. His 15 most recent articles span 2023–2025, exploring themes like collaborative piecework, robotic interactions, and autonomous vehicle ethics. Key journals include CHI , CSCW , and Ubicomp . Scientific Awards ACM Best Paper Award (CHI) 10-Year Impact Award (Ubicomp) Five ACM Best Paper Nominations He has secured over $8 million (75 million SEK) in grants from Vinnova, NSF, EU, and Wallenberg. His research is widely covered in international press (The Guardian, New York Times, Fortune Magazine) and involves collaborations across Sweden, India, and the U.S.
Dr. rer. nat. Agnes Grünerbl is a researcher at the Embedded Intelligence group within the German Research Center for Artificial Intelligence (DFKI), focusing on Human-Computer Interaction (HCI) and artificial intelligence applications. She contributes to interdisciplinary projects like STELEC (Sustainable Textile Electronics) funded by the European Innovation Council (EIC). Her work explores the integration of Generative AI (GenAI) and "Large Whatever Models" in HCI methodologies, as well as sensor-based state detection for mental health applications. Recent research includes participation in key conferences such as CHI-2024 , UbiComp-2024 , and MobileHCI-2024 , where she presented studies on AI-driven interface design, mental care standards, and mobile cognition-altering technologies. Her projects emphasize sustainability and human-centered design in emerging computing paradigms. Agnes Grünerbl is affiliated with the Embedded Intelligence lab, which develops innovative wearable and textile-based electronic systems. Her collaborations span institutions like the University of Kaiserslautern and international researchers, reflecting her focus on interdisciplinary approaches to computational challenges.
