Professor Yan (Lindsay) Sun is a faculty member at the University of Rhode Island in the College of Engineering under the Department of Electrical, Computer and Biomedical Engineering . She is the founding director of the Center for Cyber-Physical Intelligence and Security (CYPHER) and an IEEE Fellow . Her research focuses on cyber-physical systems security , power grid security , network security , and trustworthy social computing , with a particular emphasis on trust modeling and management in complex systems. Her publications span smart grid security , microgrid control , machine learning applications in power systems, and blockchain-based security mechanisms . The work often explores adversarial threats , resilient control strategies , and data augmentation techniques for improved grid monitoring. NSF CAREER Award (2007) IET Wireless Sensor Systems Premium Award (2018) EURASIP Best Paper Award (2015) IEEE Fellow (2019) URI College of Engineering Outstanding Research Award (2022) She actively leads interdisciplinary CYPHER Lab initiatives involving cyber-physical system resilience , network security , and smart grid analysis , collaborating with government and industry partners.
Robert Dick is a Professor in the Department of Electrical Engineering and Computer Science at the University of Michigan, part of the College of Engineering. He previously held roles as Associate Professor at Northwestern University and Visiting Professor at Tsinghua University. He earned his Ph.D. from Princeton University and a Bachelor's degree from Clarkson University. His research focuses on Embedded Systems, Learning Dynamics, Efficient Machine Learning, Privacy, and Censorship Resistance. Key themes include defining problems with correct costs/constraints, broadening access to information technology, mitigating negative tech impacts, and solving inference problems with limited resources. He leads the Embedded Systems Graduate Program and is a member of the Michigan Integrated Circuits Laboratory (MICL). His work spans thermal management, energy-efficient computing, and low-power wireless networks. Notable contributions include innovations in embedded system design, machine vision frameworks, and sensor networks. Courses taught include EECS 507 (Embedded Systems Research), EECS 373 (Embedded System Design), and ENGR 100 (Autonomous Systems). His recent publications emphasize AI model analysis, energy-efficient networks, and environmental sensing. Projects include MemX (attention-aware wearable tech) and LoRa-based LPWAN protocols. Dick co-founded Stryd, a company commercializing embedded systems innovations.
Edouard Oyallon is a CNRS Researcher at Sorbonne University's MLIA team within the Institute of Intelligent Systems and Robotics (ISIR). His research focuses on machine learning foundations, particularly the symmetries of deep neural networks, and large-scale distributed/decentralized training algorithms. He has contributed to frameworks like Kymatio for wavelet scattering transforms and collaborates on projects such as SHARP (Frugal Learning) and ADONIS (ANR-funded). He advises multiple PhD and postdoctoral researchers and teaches advanced deep learning courses at Institut Polytechnique de Paris (IPP). Grants include the ADONIS project (ANR/Sorbonne) and participation in VHS and CoCa4AI initiatives. His work spans theoretical and applied aspects, with recent emphasis on optimizing LLM training at exascale. He maintains active roles in academic service, including organizing workshops on federated learning and graph machine learning.
Professor Marta Zofia Kwiatkowska is Professor of Computing Systems and Fellow of Trinity College at the University of Oxford, where she has held a faculty position since 2007. She previously served as Professor of Computer Science at the University of Birmingham (2001–2007), Reader and Lecturer at the University of Birmingham (1994–2001), and Lecturer at the University of Leicester (1986–1994). Her academic career began as Assistant Professor at the Jagiellonian University in Kraków, Poland (1980–1988). Education: BSc/MSc in Computer Science, Jagiellonian University, Kraków MA, University of Oxford PhD, University of Leicester Research Interests: Professor Kwiatkowska spearheaded the development of probabilistic and quantitative verification methods on the international stage. Her work bridges theory and practice through the PRISM model checker—the leading software tool in probabilistic model checking—used worldwide for research and teaching. Application domains include communication and security protocols , nanotechnology designs , power management , ubiquitous computing and systems biology . She investigates automated verification , temporal logics , semantic models for concurrency , real-time systems , and biological process modelling . Current grant funding exceeds £3.7 million from EPSRC, EU and ERC, including the prestigious ERC Advanced Grant VERIWARE. Scientific Awards & Honours: Fellow of the Royal Society Fellow of the ACM Fellow of the European Association for Theoretical Computer Science (EATCS) Fellow of the British Computer Society (BCS) Fellow of the Polish Society of Arts & Sciences Abroad ERC Advanced Grant VERIWARE (€2.046 M, 2010–2015) Top Cited Article Award, Theoretical Computer Science (2005–2010) Best Paper Award, QEST 2006 Doctoral Supervision & Grants: Professor Kwiatkowska actively supervises doctoral students (D.Phil. at Oxford) and post-doctoral researchers. She welcomes applications in areas aligned with her research interests, detailed here . Current students include Charlie Griffin, Daqian Shao, Matthew Yuan and Minghao Liu; past students and researchers number over twenty, many now in faculty or industry leadership roles. Laboratory & Teams: She leads the Oxford Quantitative Verification group within the Department of Computer Science. Ongoing projects include FUN2MODEL, ELSA, FAIR and the flagship PRISM probabilistic model checker. The group maintains strong collaborations with biological, robotics and engineering teams worldwide.
Hélène Morlon is a Professor at the Biology Department of École normale supérieure (ENS) - PSL Research University Paris. She leads the Biodiversity Modeling team within the Center for Computational Biology, focusing on integrating ecological and evolutionary processes to explain biodiversity patterns through mathematical and bioinformatics approaches. Specializes in molecular phylogenies, speciation, extinction, and dispersal mechanisms Collaborates with mathematicians, phylogeneticists, and field ecologists Her research reveals non-equilibrium dynamics in biodiversity, challenging classical models by demonstrating speciation rate declines and climate-driven phenotypic evolution. She has developed probabilistic models applied to amphibians, mammals, birds, plants, and microorganisms. Scientific Awards: ERC Consolidator Grant (2013) Chaire d'Excellence en biologie/santé (France Innovation Santé 2030) ERC Advanced Grant (2024) for project PlankDiv Her work bridges macroecology, macroevolution, and conservation biology, with notable contributions to understanding tropical biodiversity gradients and climate impacts on evolutionary rates.
Christina Chung is an Assistant Professor in the Department of Computational Media at the University of California, Santa Cruz (UCSC). Her research focuses on personal informatics, health & wellbeing in interpersonal contexts, and human-computer interaction (HCI). She has previously been affiliated with the University of Washington (UW) and Indiana University, evidenced by her emails at those institutions. Her work explores topics such as goal-setting behaviors in technology-mediated environments, dining-out challenges for individuals with food hypersensitivities, and collaborative health practices between patients and healthcare providers. Key research interests include behavioral design, user experience (UX) in healthcare systems, and the intersection of technology with social behavior. She has published in journals like the International Journal of Human-Computer Studies and the ACM CHI Conference proceedings. Her studies often involve participatory design approaches to address real-world challenges, such as improving restaurant safety protocols for allergy sufferers or enhancing patient-doctor data-sharing practices. Chung collaborates with interdisciplinary teams, including the Design Use Build group at UW and the Proactive Health Lab at Indiana University. Her research bridges academic and applied contexts, aiming to create technologies that support long-term health behaviors and interpersonal well-being.
Elena Simperl is a Professor of Computer Science and Deputy Head of Department for Enterprise and Engagement at King's College London's Department of Informatics. She co-directs the King's Institute for Artificial Intelligence and serves as Director of Research for the Open Data Institute. As a Hans Fischer Senior Fellow at the Technical University of Munich's Institute for Advanced Study, she leads the Trustworthy Knowledge Graphs focus group and contributes to advancing human-centric AI research across European institutions. Professor Simperl obtained her doctoral degree in Computer Science from the Free University of Berlin and her diploma from the Technical University of Munich. Prior to joining King's, she held academic positions in Germany, Austria, and at the University of Southampton, and was a Turing Fellow. Her career trajectory demonstrates consistent leadership in bridging academic research with practical applications in data ecosystems. Her research sits at the critical intersection of AI and social computing, focusing on human-centric approaches to building sociotechnical systems that integrate data, algorithms, and human capabilities. She investigates how to make knowledge engineering more accessible, how to leverage collective intelligence for data quality improvement, and how to design participatory AI systems that address societal challenges like misinformation. Her work spans knowledge graphs, semantic technologies, crowdsourcing, and open data, with particular emphasis on the social dimensions of data-intensive systems and the governance frameworks needed for trustworthy AI deployment. Analysis of her recent publications reveals a strong evolution toward integrating large language models with traditional knowledge engineering practices while maintaining human oversight. There's a clear trajectory from foundational work on knowledge representation toward increasingly applied research addressing real-world challenges in media ecosystems, citizen science, and data governance, with growing attention to policy implications of AI technologies. Fellow of the British Computer Society Fellow of the Royal Society of Arts Hans Fischer Senior Fellow at TUM-IAS (2023) Ranked among top 100 most influential scholars in knowledge engineering of the last decade Included in Women in AI 2000 ranking Professor Simperl has led 14 major European and national research projects totaling millions in funding, including MediaFutures (a Horizon 2020 program tackling online misinformation), QROWD, ODINE, Data Pitch, and ACTION. She currently co-chairs the Croissant working group in ML Commons developing data standards for AI, and serves as president of the Semantic Web Science Association. Her research has directly influenced the development of data ecosystems supporting startups and citizen science initiatives across Europe, demonstrating exceptional ability to translate theoretical advances into practical impact. As Director of Research at the Open Data Institute, she oversees initiatives connecting data entrepreneurs with artists and civic organizations. Her leadership in the MediaFutures project established a data-driven innovation hub that supported 51 startups/SMEs and 43 artists through three open calls, creating a sustainable model for arts-technology collaborations addressing media challenges. Her work with the ODINE project helped create a European ecosystem for data-driven startups, demonstrating her commitment to building practical applications of open data principles.
Ximian Xu (preferred name: Simeon) is a Senior Research Associate in the Faculty of Divinity at the University of Cambridge , with a PhD in Systematic Theology from the University of Edinburgh (2020). His research bridges theology with technology, focusing on artificial intelligence (AI) ethics, Dutch Neo-Calvinism, Karl Barth, and contextual theology in mainland China. Xu’s work explores the intersection of AI and Christian ethics, the role of Reformed theology in contemporary Chinese Christianity, and the ontological implications of technology on human sustainability. Research Interests Theology and Technology (AI, Surveillance) Dutch Neo-Calvinism (Herman Bavinck) Karl Barth Contextual Theology (Reformed in China) Grants and Organisational Roles He received the CAHSS KE Grant for the workshop "Artificial Intelligence and the Christian Churches" and the Alan Turing Institute Postdoctoral Enrichment Award for research on AI in pastoral care. Xu co-founded the Studies in Dutch Neo-Calvinism Series (Chinese) and is a co-editor for its publications. Publications and Awards His recent works include studies on AI’s moral agency, technomoral futures, and Reformed theological frameworks. Xu’s book The Digitalised Image of God: Artificial Intelligence, Liturgy, and Ethics (2024) addresses AI’s theological challenges. He has contributed to journals like Perspectives on Science and Christian Faith and Modern Theology .
Pontus Johnson is a Professor at the KTH Royal Institute of Technology in Stockholm, Sweden. He leads the Center for Cyber Defense and Information Security (collaborating with Swedish Armed Forces, FRA, MSB, FOI, FHS) and serves as vice director of Cybercampus Sweden since 2024. His research focuses on cybersecurity , enterprise architecture analysis , and probabilistic threat modeling , particularly through his development of the Meta Attack Language (MAL) for simulating cyber attacks on networked systems. Education: MSc in Computer Science, Lund Institute of Technology (1997) PhD in Computer Science, KTH (2002) Docent title, KTH (2007) Leadership Roles: Director, Center for Cyber Defense and Information Security (2013–present) Vice Director, Cybercampus Sweden (2024–present) Board Member, Swedish Research Council (2025–present) Deputy Chair, Swedish Royal Academy of Engineering Sciences (IVA) Board (2024–present) His work spans cybersecurity research , attack simulation methodologies , and enterprise architecture frameworks . He has developed tools like securiCAD (acquired by Google) and pwnPr3d for probabilistic threat modeling. His 15 most recent publications highlight advancements in graph-based attack simulations , automated security assessments , and AI applications in cyber defense . Scientific recognition includes: Listed among Tech Awards Sweden's 50 Most Influential People in Swedish Tech (2022, 2023) Discovery of vulnerability in the Universal Turing Machine (2021) He supervises 16 PhD students and alumni (2005–2024), including Simon Gökstorp , Jakob Nyberg , and Sotirios Katsikeas . His academic service includes over 50 program committee roles and leadership positions in international conferences. He contributes to both academic and public domains through media appearances (SVT, Aftonbladet), courses in ethical hacking , and industry collaboration via his role at Google (20% of his time). His research group Software Systems Architecture and Security (SSAS) focuses on predictive security frameworks and system-of-systems analysis.
Dominique Chen is a Professor at Waseda University's School of Culture, Media and Society since 2022, previously serving as Associate Professor from 2017-2022. A French national born in 1981, he holds a Ph.D. in Interdisciplinary Informatics from the University of Tokyo (2013). His work bridges technology, art, and human experience with a focus on digital well-being and more-than-human relationships. Chen's research interests include human-microbe interaction, neo-cybernetics, and the design of systems that foster mutual care between humans and non-human entities. His work with the Nukabot project exemplifies this interdisciplinary approach, exploring how fermentation processes can serve as metaphors for communication and relationship building. He leads the Ferment Media Research group, investigating how fermentation principles apply to digital cultures and communication systems. His recent publications reveal a consistent focus on designing for well-being in digital societies, with particular attention to translation processes, human-microbe relationships, and the creation of systems that support co-adaptive interaction. The Nukabot research series demonstrates how traditional fermentation practices can inform novel interaction paradigms that acknowledge and incorporate more-than-human perspectives. Best Paper Honorable Mention (2024) - ACM Synlogue with Aizuchi-bot ACM SIGGRAPH Special Prize (2023) - Nukabot Best of AppStore 2015/2016 - Picsee/Syncle applications Good Design Award (2008) - Creative Commons Japan Super Creator certification (2009) - IPA Exploratory IT Program Chen has advised numerous projects through his leadership of Ferment Media Research and has served on various committees including the Good Design Award jury (2016-), Yomiuri Shimbun Reading Committee, and advisory boards for art and design institutions. His work extends beyond academia through his founding of Divideal Inc. (acquired by Smart News in 2018) and Creative Commons Japan (now Commonsphere). His laboratory, Ferment Media Research, explores interdisciplinary connections between fermentation processes, digital systems, and human relationships, creating installations like Nukabot that facilitate human-microbe interaction and Last Words/TypeTrace that examines writing processes and communication.
Dr. Yujie Tang is an Assistant Professor in the Faculty of Computer Science at Dalhousie University, Canada, where she has been serving since September 2022. Prior to this, she was an Assistant Professor at Algoma University (2019–2022) and a Post-Doctoral Fellow at the University of Waterloo (2017–2019). Her academic journey includes a PhD from the University of Waterloo and earlier degrees from Harbin Institute of Technology and Lanzhou Jiaotong University. PhD – University of Waterloo (2017) M.E. – Harbin Institute of Technology, Shenzhen, China B.E. – Lanzhou Jiaotong University, Lanzhou, China Her research focuses on intelligent networking and computing technologies for future IoT and 5G/6G systems. Key areas include Internet of Vehicles (IoV), AI-empowered edge computing, resource management in heterogeneous networks, software-defined networking, and UAV-assisted communications. She employs machine learning and optimization techniques to design energy-efficient and high-performance network protocols. The most recent publications reflect a strong trend in applying AI and machine learning to solve complex problems in vehicular networks, edge caching, and spectrum management. Her work spans top-tier IEEE journals such as IEEE Transactions on Vehicular Technology , IEEE Internet of Things Journal , and IEEE JSAC , with a clear emphasis on real-world deployable solutions for next-generation wireless systems. Faculty Research Startup Fund, Dalhousie University, 2022 NSERC Discovery Grant, 2021–2026 Algoma University Research Fund, 2021 Faculty Research Startup Fund, Algoma University, 2019 Best Speaker Award, University of Waterloo, 2017 Faculty of Engineering Award (4 times), University of Waterloo, 2013–2017 University of Waterloo Graduate Scholarship, 2013–2015 International Doctoral Student Award, 2012–2016 Graduate Research Studentship (twice), 2011–2012 Provost Doctoral Entrance Award for Women, 2011 Dr. Tang actively supervises graduate and undergraduate students and has secured competitive research grants, including the NSERC Discovery Grant. She serves on the technical program committees of major IEEE conferences such as INFOCOM, GLOBECOM, and ICC, and regularly reviews for top journals like IEEE JSAC , IEEE TWC , and IEEE TVT . She currently leads a research group focusing on B5G/6G networks, IoV, and edge computing, and she is actively recruiting new students and visiting scholars. Her research group operates within the Faculty of Computer Science at Dalhousie University, where she leads projects in intelligent resource management, AI-driven networking, and integration of space-air-ground networks. She is a member of IEEE, IEEE Communications Society, and IEEE Vehicular Technology Society.
Sotirios Liaskos is an Associate Professor in the School of Information Technology at the Faculty of Science, York University. He is a leading researcher in requirements engineering and conceptual modeling, with a focus on goal models, empirical evaluation, and model-driven engineering. Research Interests: Requirements Engineering Goal and Conceptual Modeling Empirical Software Engineering Model-Driven Design and Automation Uncertainty and Decision-Theoretic Reasoning in Models Applications in Blockchain and Reinforcement Learning His recent work emphasizes the empirical validation of modeling constructs, the integration of decision theory into goal models, and the automated generation of secure workflows and AI training environments. He has led and co-authored numerous experimental studies on model comprehensibility and semantic quality. Publication Trends: His publications consistently appear in top venues like ER, RE, and iStar. The last five years show a strong trend toward empirical evaluation of modeling languages, decision-theoretic goal models, and applications of goal modeling in emerging domains such as blockchain and reinforcement learning simulation design. Scientific Contributions: Developed frameworks for empirical evaluation of modeling language ontologies (Peira framework). Advanced decision-theoretic approaches to goal modeling under uncertainty. Pioneered model-driven methods for generating blockchain simulators and reinforcement learning environments. Conducted foundational empirical studies on the comprehensibility of contribution links and visualization alternatives in goal models. Advising and Collaboration: He has advised several researchers including Ibrahim Jaouhar, Wisal Tambosi, Mehrnaz Zhian, and Saba Zarbaf. He maintains a highly collaborative research profile with frequent co-authorship with John Mylopoulos, Shakil M. Khan, and other international researchers. He has served as a co-editor for multiple iStar workshop proceedings, indicating leadership in the goal-oriented requirements engineering community. Labs and Teams: While no specific lab name is mentioned, his work is closely associated with research groups focused on requirements engineering and conceptual modeling, likely within York University’s software engineering research cluster. His collaborations span institutions in Canada, Europe, and beyond.
Maiken Mikkelsen is the James N. and Elizabeth H. Barton Associate Professor of Electrical and Computer Engineering at Duke University, promoted to Professor in 2025. She holds a secondary appointment as Associate Professor of Physics (2023–present) within Trinity College of Arts & Sciences. Her research bridges Nanophotonics , Quantum Materials , and Ultrafast Spectroscopy , focusing on plasmonic nanostructures and nonlinear metasurfaces for quantum optics and optoelectronic applications. Education: Ph.D. in Physics (University of California, Santa Barbara, 2009), B.S. in Physics (University of Copenhagen, 2004), postdoctoral work at University of California, Berkeley. Her work explores Plasmonics and Quantum Optics to engineer nanoscale light-matter interactions, enabling transformative technologies in Single-Photon Sources , Ultrafast Photodetectors , and Active Metasurfaces . Recent projects include real-time tunable lasing and polarization-controlled nanocavity systems. Her 2016–2025 publications highlight breakthroughs in plasmonic fluorescence enhancement, hot electron dynamics, and room-temperature quantum devices. Grants include Nano Solutions On-Chip (Triad National Security, LLC, 2025–2029) and Meta-Imaging (Air Force Office of Scientific Research, 2021–2026). Her lab, jointly based in Electrical & Computer Engineering and Physics, has graduated PhD students Eunso Shin and Hengming Li, and actively engages in STEM outreach initiatives.
Jeffrey Andrews is a Professor at The University of Texas at Austin, holding the Truchard Family Chair in Engineering. He is Director of the 6G@UT research center and a member of the Wireless Networking and Communications Group (WNCG). He earned his B.S. in Engineering from Harvey Mudd College and M.S. and Ph.D. in Electrical Engineering from Stanford University. His career includes consulting for Samsung, Nokia, Qualcomm, Apple, Verizon, AT&T, Intel, Microsoft, Sprint, and NASA. B.S. Engineering with High Distinction, Harvey Mudd College M.S. Electrical Engineering, Stanford University Ph.D. Electrical Engineering, Stanford University His research focuses on Wireless Communication, Information Theory, Communication Theory, Stochastic Geometry, and Machine Learning for Communications. He has authored seminal books on WiMAX and LTE and led editorial roles at IEEE Transactions on Wireless Communications and IEEE Journal on Selected Areas in Information Theory. His work spans 5G/6G wireless systems, femtocells, and wireless network optimization. Jeffrey Andrews has received 16 best paper awards, including the IEEE Stephen O. Rice Prize, Leonard G. Abraham Prize, Heinrich Hertz Prize, and Kiyo Tomiyasu Award. Additional accolades include the Terman Award, NSF CAREER Award, Gordon Lepley Memorial Teaching Award, and IEEE ComSoc Joe LoCicero Service Award. As an ISI Highly Cited Researcher and IEEE Fellow, he has shaped global wireless standards and mentored students in high-impact research projects. His collaborations with Intel, Cisco, and Qualcomm have driven advancements in 5G/6G and video networking technologies.
Harish Ravichandar is an Assistant Professor at the School of Interactive Computing , Georgia Institute of Technology, and a core faculty member of the Institute for Robotics and Intelligent Machines (IRIM) . He leads the Structured Techniques for Algorithmic Robotics (STAR) Lab , focusing on structured computational frameworks and learning algorithms with inductive biases to enhance robot efficiency, reliability, and self-sufficiency in human-robot collaboration and complex applications like dexterous manipulation and multi-agent coordination. His research bridges robot learning , human-robot interaction , and multi-agent systems , emphasizing stable, frugal, and safe skill acquisition from human demonstrations. Key themes include intention inference , trajectory optimization , and heterogeneous team coordination , often leveraging Koopman operators , hypernetworks , and graph-based methods . Scientific recognition includes the NSF CAREER Award , IEEE MRS Best Paper Award , and Georgia Tech’s College of Computing Outstanding Post-Doctoral Research Award . His work also received the ASME DSCC Best Student Paper Award and P&W Institute Graduate Fellowship . Harish’s educational background includes a Ph.D. in Electrical and Computer Engineering from the University of Connecticut (2018) , an M.S. from the University of Florida (2014) , and a B.E. in Instrumentation and Control Engineering from Anna University (2012) . He previously held postdoctoral and research scientist roles at Georgia Tech before his current position.
