Dr. Chengmo Yang is a Professor in the Department of Electrical and Computer Engineering at the University of Delaware, with a joint appointment. She received her PhD and MSc in Computer Science from the University of California, San Diego, and a BSc in Microelectronics from Peking University, China. PhD, University of California, San Diego MSc, University of California, San Diego BSc, Peking University, China Her research focuses on enhancing security, reliability, non-volatility, and energy efficiency in embedded systems, cyber-physical systems (CPS), and Internet-of-Things (IoT). She leads the Computer Architecture, Reliability, and Security (CARES) group and has authored over 70 peer-reviewed publications. Recent publications emphasize neural network accelerators, non-volatile memory (NVM) optimization, and security frameworks for embedded systems. Her work explores fault tolerance, wear leveling, and side-channel attack mitigation in NVM-based FPGAs, STT-RAM, and SSDs. National Science Foundation Career Award (2013) University of Delaware Mid-Career Faculty Excellence in Scholarship Award (2020) Best paper award at ICESS (2019) Three best paper nominations at DAC, DATE, and GLSVLSI (2019) Dr. Yang serves as Associate Editor for IEEE TCAD and ACM TODAES. She is the Diversity & Inclusion Representative for IEEE CEDA and has organized numerous conferences including Technical Program Chair for CODES-ISSS 2022. Her lab has hosted current and former students like Fanruo Meng (PhD candidate), Fateme Hosseini (Qualcomm), and Patrick Cronin (Intel), focusing on graduate-level research in hardware security and reliability.
Cicek Cavdar is an Associate Professor at the School of Electrical Engineering and Computer Science (EECS) at KTH Royal Institute of Technology , Sweden. She leads the Intelligent Network Systems research group and specializes in Telecommunication Networks , with a focus on Beyond 5G/6G Mobile Networks , Energy Efficiency , and AI-Assisted Network Management . PhD in Computer Science (2009) from University of California, Davis and Istanbul Technical University Her research spans Cell-Free Massive MIMO , Reconfigurable Intelligent Surfaces (RIS) , UAV Communication Systems , and Green Network Technologies . She actively contributes to 6G Network Architecture and Non-Terrestrial Networks , including satellite and aerial systems. Recent publications highlight AI-driven network optimization for handover management, energy-aware resource allocation , and multi-agent reinforcement learning in complex communication environments. She teaches advanced courses in Communication Systems , Machine Learning , and Software Engineering at KTH.
Maja J Matarić is the Chan Soon-Shiong Chaired and Distinguished Professor of Computer Science at the University of Southern California's Viterbi School of Engineering, with courtesy appointments in Neuroscience and Pediatrics. She serves as founding director of the USC Robotics and Autonomous Systems Center, co-director of the USC Robotics Research Lab, and Principal Scientist at Google DeepMind. Previously, she held leadership roles as USC's interim Vice President of Research (2020-2021) and Vice Dean for Research (2006-2019). Her educational background includes: PhD in Computer Science and Artificial Intelligence from MIT (1994) MS in Computer Science from MIT (1990) BS in Computer Science from University of Kansas (1987) Matarić pioneers Socially Assistive Robotics (SAR) , a field her lab named, focusing on human-robot interaction that provides assistance through social rather than physical support. Her research targets critical health and wellness challenges including post-stroke rehabilitation, autism spectrum disorder therapy, cognitive exercises for Alzheimer's patients, ADHD academic support, and mental health interventions. She develops systems modeling user engagement, personality, and motivation, with extensive real-world deployments in schools, rehabilitation centers, and homes. Analysis of her recent publications reveals dominant themes in cognitive health robotics (2025 CHI paper on LLM-powered elder care), pediatric assistive technology (2025 IDC speech therapy review), and adaptive preference modeling (2025 HRI contrastive learning work). Her research consistently bridges machine learning with human-centered design for vulnerable populations. Major scientific recognition includes: ACM Athena Lecturer Award (2024) ACM Eugene L. Lawler Humanitarian Award (2024) ACM Fellow (2020) Presidential Mentoring Award (2011) Multiple society fellowships (AAAS, IEEE, AAAI) As a dedicated mentor, Matarić has championed underrepresented groups through CRA-W, placing numerous women in faculty positions. She leads USC Viterbi's K-12 STEM Outreach Program serving low-income Los Angeles schools and authored The Robotics Prime for student education. Her research has secured significant funding enabling real-world technology transfer, with documented impact in rehabilitation centers and homes through deployable SAR systems. Her Robotics Research Lab at USC drives innovation in embodied AI, with current projects spanning LLM-integrated elder care robots, ADHD academic companions, and autism therapy systems. The lab emphasizes co-design with end-users and rigorous real-world validation across diverse populations.
Anthony Rowe is the Siewiorek and Walker Family Professor of Electrical and Computer Engineering at Carnegie Mellon University (CMU) and a Chief Scientist at Bosch Research. His primary affiliation is with the CyLab and the Wireless, Sensing and Embedded Systems (WiSE Lab) at CMU. He specializes in networked embedded systems, sensor networks, and extended reality (XR) technologies. His research emphasizes energy-efficient sensing, real-time localization, and XR integration with physical systems. Research Focus: His work spans XR systems (e.g., AR/VR edge networking in ARENA), mmWave radar for sensing (e.g., tire wear monitoring via Osprey), distributed edge computing (Silverline), and low-power wide-area networking (OpenChirp). Recent efforts include AI-integrated XR platforms (XaiR) and radar tomography (DART). Grants & Projects: Leads the CONIX Research Center ($27.5M NSF/DARPA grant), Bosch-funded edge computing projects, and DOE initiatives on microgrids. Notable projects include ARENA (XR edge architecture), GridBallast (smart grid control), and rural microgrid deployments in Haiti. Awards: Best Student Paper (ISMAR 2024), Best Paper (IPSN 2020), and the Steven J. Fenves Research Award (2015). Recognized for innovations in localization (MobiCom 2021), radar (ICRA 2023), and energy systems (BuildSys 2010). Teaching: Teaches courses on embedded systems (18-349/18-449), real-time systems, and mixed reality (18-453). Courses emphasize hands-on design and real-world applications. Labs & Teams: Directs the WiSE Lab, collaborating with Bosch Research and industry partners. The lab develops open-source frameworks like ARENA and OpenChirp, and contributes to standards for edge computing and sensing.
Roger Giner-Sorolla is Professor of Social Psychology at the University of Kent's School of Psychology, where he has been a faculty member since 2001 after completing his PhD at New York University in 1996. He served as Editor-in-Chief of the Journal of Experimental Social Psychology from 2016-2022 and currently leads a Leverhulme Foundation grant examining moral heroism across professions. His academic journey includes a postdoctoral fellowship at the University of Virginia and has established him as a leading figure in social and moral psychology. Professor Giner-Sorolla's research focuses on the social role of emotions, particularly moral emotions including self-condemning emotions (guilt and shame) and other-condemning emotions (anger, contempt, and disgust). His work extends to intergroup apologies, dehumanization, emotionally driven prejudice, and collective moral roles, with a notable side interest in the ironic enjoyment of music and aesthetic experiences. He is a strong advocate for transparency in scientific reporting, having written extensively on improved reporting guidelines, pre-registration, and open science practices. Analysis of his recent publications reveals a consistent focus on moral psychology with expanding interdisciplinary reach. His work bridges traditional social psychology with emerging areas including cross-cultural emotion research, replication science, and historical memory. The trend shows increasing attention to methodological rigor while maintaining core interests in emotion and morality, with growing emphasis on practical applications in conflict resolution and intergroup relations. Fellow of the Association for Psychological Science Member of Rising Stars selection committee (2023-2024) Promising Scholars Award (University of Kent, 2006) Vacation Research Scholarship (Wellcome Trust, 2005) Multiple ESRC grants totaling over £400,000 European Science Foundation Workshop Award (2004) Professor Giner-Sorolla has supervised an impressive number of PhD students, with 17 doctoral candidates listed in the documentation including both current and past students. His grant portfolio demonstrates significant research impact with funding from major organizations including ESRC, Wellcome Trust, and Leverhulme Foundation. His supervision style appears to encourage students to pursue research that aligns with his core interests in moral emotions while allowing exploration of novel applications and contexts. While the documentation doesn't specify laboratory or research team structures, his extensive collaborative work suggests leadership of research groups focused on moral psychology and emotion research. His numerous international collaborations and invited workshops indicate an active research program with global reach, likely involving multiple research teams working on interconnected projects related to his core interests in moral psychology and scientific methodology.
Asaf Cidon is an Associate Professor at Columbia University, jointly affiliated with the Department of Electrical Engineering and Computer Science, and a member of the Data Science Institute. His research focuses on software systems , storage , large-scale machine learning , and cybersecurity . Stanford University - PhD in Electrical Engineering Stanford University - MS in Electrical Engineering Technion - BS in Computer and Software Engineering His work in distributed storage systems has been commercialized by companies such as Facebook, Tibco, and Rubrik. He has led projects like Sentinel and Forensics during his industry career. Recent publications highlight advancements in software-based radiation protection (ASPLOS'26), PCIe pooling with CXL (HotOS'25), and AI phishing detection (IMC'25). These reflect his expertise in system architecture , security , and networking . Scientific recognitions include best paper awards at OSDI, Usenix Security, CIDR, and ATC, along with NSF CAREER and ARO Young Investigator Awards . His papers Cookie Monster (SOSP'24) and Chablis (CIDR'24) received notable accolades. He has mentored numerous PhD and Master's students , including Edward Guo, Harry Wang, and Teng Jiang, many of whom now hold roles at Google, Meta, Amazon, and academic institutions. His lab at Columbia is actively recruiting CS and EE PhD students. Prior to Columbia, he founded and led the startup Sookasa to acquisition and served as Senior Vice President of Email Protection at Barracuda Networks , managing a $200M business with 100 engineers.
Professor Timothy J. Power is Head of the Social Sciences Division and Professor of Latin American Politics at the University of Oxford, affiliated with the Oxford School of Global and Area Studies (OSGA) and the Department of Politics. He previously directed the Latin American Centre from 2008 to 2012 and has been a leading scholar in comparative politics since 2005. Research Interests: Democratization, political institutions (parties, legislatures, elections), coalitional presidentialism, Brazil, Latin America, new democracies. Awards: None listed in provided text. Advising: No specific students mentioned. Grants: No explicit grants listed, but research involves long-term projects like the Brazilian Legislative Surveys. Labs/Teams: Co-directs the Brazilian Legislative Surveys with Fundação Getúlio Vargas and contributes to cross-regional comparative studies at OSGA. His work analyzes democratization in Latin America, particularly Brazil, focusing on legislative dynamics, coalition governments, and political institutions. Recent articles explore cabinet proportionality, portfolio allocation, and ideological shifts in post-authoritarian settings.
Daniel W. Bliss is a Professor in the School of Electrical, Computer and Energy Engineering at Arizona State University and Director of ASU's Center for Wireless Information Systems and Computational Architectures (WISCA). With over $50 million in research funding as principal investigator from organizations including DARPA, ONR, Google, and Airbus, his work bridges theoretical foundations with practical implementations across multiple domains of wireless systems. Dr. Bliss received his educational foundation with a B.S.E.E. from Arizona State University (1989), followed by M.S. and Ph.D. degrees in Physics from the University of California-San Diego (1995, 1997). His academic journey includes significant industry experience at General Dynamics (1989-1993) and MIT Lincoln Laboratory (1997-2012) before joining ASU. His research program focuses on advanced wireless systems spanning radar, communications, precision positioning, computational architectures, and medical monitoring applications. Bliss employs information theory, estimation theory, and signal processing to develop novel system concepts with disruptive capabilities. Current research emphasizes RF convergence, integrated sensing and communications, and anticipatory medical analytics using wireless technologies, with particular focus on extracting physiological data from radar signals. Analysis of recent publications reveals a strong trend toward integrated sensing and communications systems, particularly utilizing mmWave and radar technologies for medical monitoring applications. His work increasingly bridges traditional communications and radar domains while expanding into physiological monitoring, demonstrating a clear trajectory toward convergence of wireless technologies for healthcare applications and remote vital sign detection. Dr. Bliss has received significant recognition for his contributions: Fellow of the IEEE (2015) 2021 IEEE Warren D. White Award for Excellence in Radar Engineering 2016-2017 Top 5% Teaching Award at ASU 2017 ASU Fulton Engineering Exemplar Faculty As a dedicated mentor, Dr. Bliss has supervised numerous graduate students through successful dissertation and thesis defenses across both PhD and Master's programs. His research portfolio includes substantial funding from diverse sources with over $50 million secured as principal investigator. Current projects include the $17M DARPA DASH project focused on advanced software-reconfigurable heterogeneous SoCs for next-generation RF systems, and multiple initiatives in contactless vital sign monitoring using radar technologies. Dr. Bliss leads the BLISS Lab and serves as director of WISCA, fostering interdisciplinary research in wireless systems. His team includes researchers working on distributed coherent systems, MIMO radar, RF convergence, and medical monitoring applications, with recent successes including the Making Waves team that tied for first place in the Air Force Spark Tank challenge. He has founded two startup companies: DASH Tech Integrated Circuits Company and the Big Little Sensor Company, focusing on high-performance embedded processing and small-scale radar physiological monitoring, respectively.
Minseok Ryu is an Assistant Professor at the School of Computing and Augmented Intelligence, Arizona State University (ASU). He holds a Ph.D. in Industrial & Operations Engineering from the University of Michigan (2020). Prior to ASU, he was a postdoctoral appointee at Argonne National Laboratory’s Mathematics and Computer Science Division. His research focuses on optimization methodologies for decentralized and stochastic decision-making distributed algorithms for machine learning and operations research applications in healthcare systems and energy grids Teaching responsibilities include courses on applied deterministic operations research (IEE 574), optimization (IEE 622), and research practicums (IEE 792). His work emphasizes computational challenges in decision-making under uncertainty, with recent projects addressing nurse staffing optimization, federated learning frameworks (e.g., APPFL/APPFLX), and resilient power grid systems. He has no recorded academic awards but actively contributes to open-source software and cross-disciplinary research collaborations. Research interests bridge theory and practice, targeting social goods through optimization techniques like distributionally robust optimization, federated learning, and heuristic algorithms for energy and healthcare systems.
Osman Yağan is a Research Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University (CMU), with affiliate faculty status in the School of Computer Science. He is also a core member of CyLab Security and Privacy Institute. Prior to joining CMU in 2013, he was a Postdoctoral Research Fellow at CyLab. He holds a Ph.D. in Electrical and Computer Engineering from the University of Maryland (2011) and a B.S. from Middle East Technical University (2007). His research focuses on modeling, analysis, and optimization of computing systems, leveraging applied probability, network science, data science, and machine learning. Key areas include multi-armed bandits, resilient machine learning, contagion processes in networks, and cybersecurity. Research Interests include Machine Learning, Data Science, Network Science, Cybersecurity, and Robustness in Cyber-Physical Systems. He has advised numerous students, including current PhD candidates Yurun Tian, Orkun İrsoy, and Ishank Juneja, as well as notable alumni such as Mansi Sood (now at MIT) and Jun Zhao (Assistant Professor at Nanyang Technological University). Key Awards include the CIT Dean's Early Career Fellowship, IBM Academic Award, and Best Paper Awards at ICC 2021, IPSN 2022, and ASONAM 2023. His work spans theoretical contributions (e.g., contagion models in multi-layer networks) and applied research (e.g., mitigating cascading failures in power systems). He leads or co-leads grants from ONR, NSF, and ARO, focusing on resilient machine learning, network robustness, and pandemic modeling.
Celestine Mendler-Dünner is a Principal Investigator at the ELLIS Institute in Tübingen, co-affiliated with the Max Planck Institute for Intelligent Systems and the Tübingen AI Center. She leads the Algorithms and Society research group, focusing on machine learning in social contexts and the role of prediction in digital economies. Her work bridges theoretical machine learning with practical societal impact, developing tools for safe, reliable, and equitable AI ecosystems. Her educational background includes a PhD from ETH Zurich in collaboration with IBM Research, followed by an SNSF postdoctoral fellowship at UC Berkeley hosted by Moritz Hardt. She was previously a group leader at the Max Planck Institute for Intelligent Systems before joining the ELLIS Institute. Mendler-Dünner's research spans several interconnected themes including performative prediction (where predictions change the behavior they aim to predict), algorithmic collective action (how participants can steer AI systems toward common goals), and the role of LLMs in social science research. Her work combines theoretical foundations with practical implementations, addressing challenges in interactive machine learning, optimization in dynamic environments, and context-specific evaluation of AI systems. She particularly examines how algorithmic predictions mediate services and platforms at societal scale, exploring concepts of economic power in digital markets. Her publication record shows a clear evolution from system-aware machine learning algorithms (including foundational work on IBM Snap ML) toward increasingly sociotechnical questions at the intersection of machine learning, economics, and policy. Recent work focuses on measuring performative power in digital economies, evaluating LLMs as risk scores, and developing frameworks for algorithmic collective action in recommender systems and labor markets. Among her notable recognitions are the ETH Medal for her dissertation, the IBM Research Division Award, the Fritz Kutter Award, and the IBM Eminence and Excellence Award. She is an ELLIS Scholar, a fellow of the Elisabeth-Schiemann-Kolleg, and affiliated with several prestigious research programs including the International Max Planck Research School for Intelligent Systems and the Max Planck ETH Center for Learning Systems. ETH Medal (dissertation award) IBM Research Division Award Fritz Kutter Award IBM Eminence and Excellence Award SNSF Early Postdoc Mobility Fellowship Mendler-Dünner actively mentors the next generation of researchers, advising PhD student Patrik Wolf and supervising research interns including Joachim Baumann, Haiqing Zhu, and Anna Badalyan, as well as Master's student Dorothee Sigg. She serves as core faculty for the International Max Planck Research School and associated faculty for the Max Planck ETH Center for Learning Systems. Her group has secured significant research funding through fellowships and institutional support, enabling work on projects like Powermeter (measuring search engine influence) and Snap ML (resource-efficient machine learning library with over 1 million PyPI downloads). She leads the Algorithms and Society research group, which examines machine learning as part of broader sociotechnical ecosystems. The group explores human-population interactions with algorithmic systems and incorporates these insights into learning system fundamentals. Current projects include investigating economic incentives in digital platforms, developing tools for systematic LLM evaluation in social science contexts, and creating frameworks for collective action in algorithmic systems. Mendler-Dünner also co-organizes the Algorithmic Collective Action workshop at NeurIPS 2025, demonstrating her leadership in emerging research directions at the AI-society interface.
Bahar Asgari is an Assistant Professor in the Department of Computer Science at the University of Maryland, College Park. She holds appointments in CS, UMIACS, and ECE, and directs the Computer Architecture and Systems Lab (CASL). Her research focuses on domain-specific architecture design, near memory processing, and reconfigurable computing. Before joining UMD, she worked at Google, contributing to system optimization and memory utilization strategies. Education: Ph.D., Georgia Institute of Technology, 2021. Research Interests: Developing energy-efficient architectures for sparse problems, scientific computing acceleration, FPGA optimizations, and reconfigurable hardware systems. Her work addresses challenges in memory efficiency, parallelization, and hardware-software co-design across domains like machine learning and IoT. Key Awards: 2024 UMD Excellence in Teaching Award 2023 DOE Early Career Award Advising & Grants: Supervises 9 graduate students and leads projects sponsored by NSF, DOE, and industry partnerships. Her lab explores systolic arrays, near-data processing, and fault-tolerant computing. Labs/Teams: Directs CASL, which builds next-generation computing systems through hardware innovation and algorithm-architecture co-design.
Dr. Anwar Haque is an Associate Professor in the Department of Computer Science at Western University, Canada, and a Faculty of Science Distinguished Research Professor. He holds a Ph.D. in Electrical and Computer Engineering and an M.Sc. in Computer Science from the University of Waterloo. Prior to academia, he was Associate Director at Bell Canada. His research focuses on 5G networks, IoT, cybersecurity, AI, and autonomous systems, with over 100 peer-reviewed publications and $15M in collaborative grants. Dr. Haque leads the Western Information & Networking Group (WING) Lab and is the founder/CEO of Bamboo Innovations Inc., a tech startup developing socially responsible smart technologies. Leadership roles include industry expert-in-residence in the Faculty of Science, Undergraduate Chair of the Computer Science Department, and member of Western’s Senate. He has delivered over 30 keynote talks and media features include BBC Earth and The Globe and Mail. Awards include the IEEE CCECE Leadership Award and multiple grants from NSERC, MITACS, and Bell Canada. His work spans network reliability, smart grids, and cybersecurity, with industry partnerships like the Bell-Western 5G Research Centre.
Albrecht Fuess is a Professor of Islamic Studies at Philipps University of Marburg since 2010, specializing in Middle Eastern History (13th–17th centuries), Mamluk socio-cultural dynamics, and contemporary European Islamic discourses. His research spans historical continuity in Ottoman-Mamluk-Safavid interactions, Islamic youth cultures, and Mediterranean geopolitics. Research Focus: Medieval Islamic history, Transottomanica mobility studies, Islam in Europe, and cultural integration of Muslim migrants. Awards: Le Studium Fellowship (2007–2009) at Université de Tours. His publications emphasize military-economy interplay, legitimacy through religious narratives, and resource management in empires, with a focus on Mamluk and Ottoman transformations. He has advised on doctoral projects covering topics like Islamic welfare, Arabic ʾAmālī literature, and Cypriot-Ottoman relations. Leadership: Co-coordinator of Transottomanica (DFG-SPP 1981), member of ANR and DAAD committees, and liaison professor for the German National Academic Foundation. Editorial Roles: Co-editor of 'Transottomanica' and 'Muslim Worlds' series, and advisory board member for journals in Cairo, Paris, and Leuven.
John Lygeros is a Full Professor and Head of the Institute for Automatic Control at ETH Zurich's Department of Information Technology and Electrical Engineering. He received his B.Eng. (1990) and M.Sc. (1991) from Imperial College London, and Ph.D. (1996) from UC Berkeley. Before joining ETH Zurich in 2006, he held academic positions at the University of Cambridge and University of Patras. His research focuses on: Modeling and control of hierarchical hybrid systems Large-scale dynamical systems applied to biochemical networks Control of automated transportation systems via wireless networks Energy systems and advanced manufacturing control His research demonstrates strong emphasis on optimization methods, distributed control architectures, and machine learning applications in control systems, with significant contributions to real-time optimization algorithms and data-driven control methodologies. Major scientific awards include: HSCC Test of Time Award (2024) ERC Advanced Grant (2018) O. Hugo Schuck Best Paper Award (2018) IEEE George S. Axelby Paper Award (2016) Three Golden Owl teaching awards from ETH Zurich He leads the Automatic Control Laboratory at ETH Zurich and serves as Director of the National Centre of Competence in Research 'Dependable Ubiquitous Automation'. He has advised over 60 doctoral candidates since 2017, with research spanning optimization algorithms, power systems, autonomous systems, and machine learning applications.
