Dr. Tao (Kevin) Huang is a researcher at James Cook University's College of Science and Engineering, with expertise spanning autonomous driving, wireless communication systems, and medical imaging applications. His work integrates machine learning, sensor fusion, and multimodal data analysis to address complex challenges in vehicular networks, environmental monitoring, and healthcare technology. Research Interests: Dr. Huang's research focuses on Autonomous driving perception systems IoT-enabled vehicular networks AI for medical diagnostics and environmental sensing Signal processing and privacy-preserving communication protocols Recent Publications: His 2025 work emphasizes advancements in V2X cooperative perception, radar-LiDAR-camera fusion, and diffusion models for medical imaging. Key trends include cross-modal robustness, real-time processing for autonomous systems, and AI applications in sustainability.
W. Michael Petullo is an Assistant Professor in the Department of Comp Sci & Comp Engineering at the University of Wisconsin-La Crosse. He holds a Ph.D. in Computer Science from the University of Illinois at Chicago, and prior academic degrees from DePaul University and Drake University. Before academia, he served a 20-year career in the Army, including roles teaching in the Department of Electrical Engineering and Computer Science and leading cyber operations software development. His research focuses on software and network security, operating systems, and open-source software development. Education: Ph.D. in Computer Science, University of Illinois at Chicago M.S. in Computer Science, DePaul University B.S. in Computer Science, Drake University Research Interests: His work emphasizes secure operating system design, network security protocols, and open-source tool development. Recent efforts include the Aquinas Learning System for courseware automation and PivotWall for SDN-based information flow control. He also explores user behavior in cybersecurity contexts and educational applications of cyber defense exercises. Teaching: Currently instructs CS120 (Software Design I), CS410/510 (Open Source Development), and CS455/555 (Fundamentals of Information Security). Past courses include operating systems concepts and secure software development. Labs & Projects: Maintains the Aquinas Learning System project and contributes to Ethos operating system research. Active in developing minimal-latency networking solutions and secure kernel interfaces.
Manuel Rigger is an Assistant Professor at the National University of Singapore in the School of Computing and leads the Trustworthy Engineering of Software Technologies (TEST) Lab . His research focuses on improving data-centric systems , particularly their reliability, having found over 1,000 unique bugs in database systems. Education : PhD in Computer Science (2019) and MSc in Software Engineering (2015) from Johannes Kepler University Linz; MPhil in Chinese Philosophy (2015) from Xiamen University Research Highlights : Developed SQLancer – an automated testing framework that found 500+ bugs in DBMSs; created Query Plan Guidance (QPG) for efficient logic bug detection; received best paper awards at ICSE '23 and EuroSys '24 Scientific Awards : Recipient of 6 distinguished artifact/reviewer awards Major industry support from Google, AWS, and Microsoft Developed tools adopted by Oracle GraalVM and SQLite Teaching : Lecturer for CS3213 Foundations of Software Engineering and CS6223 Advanced Topics in Software Testing . Supervises multiple PhD/MSc theses on database testing and compiler reliability.
David J.X. González is an Assistant Professor in the Division of Environmental Health Sciences at UC Berkeley’s School of Public Health. His interdisciplinary work bridges epidemiology and environmental science to address environmental justice and health disparities, particularly in extractive industries and climate-driven disasters. He leads the EQUIS Lab, focusing on oil/gas development, wildfire smoke, and structural racism in environmental hazards. Education : PhD in Environment and Resources, Stanford University MS in Epidemiology and Clinical Research, Stanford University MESc in Environmental Science, Yale University BS in Evolution, Ecology, and Biodiversity, UC Davis Research Interests : González investigates air pollution’s impact on perinatal health, climate change’s health consequences, and systemic racial inequities in environmental exposures. He employs community-engaged methods to translate findings into actionable policies and advocates for diversity in scientific fields. His work emphasizes marginalized communities’ disproportionate burdens from fossil fuels and environmental hazards. Publications & Media : His recent studies highlight fossil fuel health risks, wildfire-oil infrastructure intersections, and disparities in pandemic outcomes linked to oil/gas exposure. He frequently engages with media to communicate science, including op-eds on racial inequality in housing/education systems and language justice in environmental sciences. Awards : None explicitly listed in the text. Labs/Teams : As Principal Investigator of the EQUIS Lab, he coordinates interdisciplinary teams to study environmental justice issues, integrating community voices into research design and policy advocacy.
Dr. Carla Bonina is Associate Professor in Entrepreneurship and Innovation at the University of Surrey Business School , with affiliations to multiple research centers including the Surrey Centre for the Digital Economy , Surrey Institute for People-Centred AI , and Latin American Open Data Initiative (ILDA). Her work bridges technology, policy, and sustainable development with a focus on Latin America. PhD in Management - London School of Economics and Political Science MSc in Public Administration - Centro de Investigación y Docencia Económicas (CIDE), Mexico City BSc in Economics - University of Buenos Aires, Argentina Research explores digital platform governance in international development, AI policy frameworks, and open data ecosystems in Latin America. She investigates how digital transformation intersects with social innovation and equitable development . Recent work analyzes data justice mechanisms and algorithmic bias in public service delivery. Key contributions include comparative OGD platform studies across Buenos Aires, Mexico City, and Montevideo. Her DIODE network research examines digital economies in developing countries. As co-PI for Audio Commons Initiative , she pioneered open audio content frameworks for creative industries. Mid-Career Researcher of the Year (Surrey Business School, 2021) Impact Award for digital government work (University of Surrey, 2020) Fellow, Surrey Institute for People-Centred AI Principal Researcher, ILDA Active in digital policy advisory for World Bank, OECD, and IDRC. Coordinates Por Mi Barrio urban governance case studies and contributes to UNESCO Open Science frameworks. Recent Surrey Speaks podcast (2023) discusses AI's role in social inequality dynamics.
Jeff Huang is an Associate Professor in the Department of Computer Science & Engineering at Texas A&M University, affiliated with the College of Engineering. His research focuses on software engineering, programming languages, concurrency, and runtime verification, with notable contributions to static analysis, race detection, and vulnerability mitigation in concurrent systems. Education: Postdoc, Computer Science, University of Illinois at Urbana-Champaign (2013-2014) Ph.D., Computer Science, Hong Kong University of Science and Technology (2012) B.E., Electrical Engineering, National University of Defense Technology, China (2008) Research Interests: Huang's work bridges theoretical foundations and practical applications in concurrency debugging, static analysis tools, and cybersecurity for smart contracts. He emphasizes scalable solutions for pointer analysis, race detection, and vulnerability detection in distributed systems and blockchain technologies. Recent Trends in Publications: His recent work explores AI-driven program execution (e.g., SGLang), blockchain security (e.g., Smart Contract analysis), and dynamic/static analysis techniques for memory safety. These studies underscore advancements in automated tools for securing concurrent and distributed systems. Awards: 2023 ACM SIGSOFT Distinguished Paper Award 2019 DARPA Young Faculty Award 2016 NSF CAREER Award 2013 ACM SIGSOFT Outstanding Doctoral Dissertation Award Advising & Grants: Huang has advised PhD students including Bozhen Liu and Peiming Liu, who have contributed to OpenMP race detection and pointer analysis tools. His grants include NSF awards for pointer analysis as a service and DARPA funding for young faculty research. Labs & Teams: He leads the O2 Lab, focused on concurrency verification and cybersecurity, collaborating with industry partners like Coderrect Inc. and DOE on scalable static analysis frameworks.
Robert 'Corky' Cartwright is a Professor of Computer Science at Rice University, specializing in programming languages and software engineering. His research focuses on parallel programming extensions for Java/Scala/Swift, smart programming environments for error-free code, pedagogic tools like DrJava, and intent-driven programming in the FAST language. He has contributed to cyber-physical systems modeling through frameworks like Acumen and DrHJ. Education: PhD (Computer Science, Stanford University, 1976), BA (Applied Mathematics, Harvard College, 1971). Awards include ACM Fellow (1998). Teaching emphasizes principles of programming languages and program design. His work bridges theoretical foundations (domain theory, formal semantics) with practical tools for education and industry.
Dan S. Wallach is a Professor of Computer Science and Electrical and Computer Engineering at Rice University, and a Program Manager at DARPA's Information Innovation Office since June 2023. He holds a PhD (1999) and MA (1995) from Princeton University, and a BS (1993) from UC Berkeley. His research focuses on cybersecurity, electronic voting systems, and mobile security. He directed the NSF-funded ACCURATE Center (2005-2011), led the STAR-Vote project, and advised U.S. election security policies including testifying before state and federal committees. He also served on the Air Force Science Advisory Board (2011-2015), USENIX Board (2011-2013), and IEEE Technical Guidelines Committee (2019-2023). Recent work includes developing ElectionGuard cryptographic tools for verifiable elections and analyzing cyber warfare in Ukraine. His 15+ years of teaching include courses like Introduction to Program Design and Election Systems Technologies. Publications span secure voting protocols, smartphone security, and election auditing. Collaborations include Microsoft and VotingWorks on cryptographic voting systems like ElectionGuard and Arlo-CVR-Encryption.
Elizabeth Spelke is the Marshall L. Berkman Professor of Psychology at Harvard University and an investigator at the NSF-MIT Center for Brains, Minds and Machines. She leads the Spelke Lab, which conducts behavioral research on infants and preschool children to understand the origins of uniquely human cognitive capacities such as formal mathematics, symbolic representation, and object taxonomy. Education: B.A. in Social Relations from Radcliffe College (1971), Ph.D. in Psychology from Cornell University (1978). Professional Experience: Faculty positions at the University of Pennsylvania, Cornell University, MIT, and Harvard University since 2001. Her research focuses on core knowledge systems in infancy, including understanding of objects, actions, people, places, number, and geometry. She collaborates with computational cognitive scientists to model infant cognition and with economists to apply findings to educational interventions. Her work integrates developmental, comparative, and cross-cultural perspectives. Her recent publications span topics such as early math learning, social evaluation in toddlers, goal inference, and the interplay between language and conceptual development. Trends in her recent work include experimental field studies, interdisciplinary collaborations, and theoretical synthesis of core knowledge frameworks. National Academy of Sciences (USA), 1999 American Academy of Arts and Sciences, 1997 National Academy of Sciences Prize in Psychological and Cognitive Sciences, 2014 C.L. de Carvalho-Heineken Prize for Cognitive Sciences, 2016 George A. Miller Prize, Cognitive Neuroscience Society, 2018 Mentor Awards from APS and APA, 2021 Spelke has mentored numerous researchers and collaborated widely across disciplines. Her lab’s work is supported by major grants from the NSF and other institutions. She has pioneered the use of behavioral methods to study infant cognition and has been instrumental in translating cognitive science into educational practice. She directs the Spelke Lab at Harvard, which investigates core cognitive systems through behavioral experiments with infants and young children. The lab explores how innate knowledge structures interact with experience to produce complex human cognition.
Dorsa Sadigh is an Associate Professor of Computer Science and Electrical Engineering at Stanford University, and a Senior Fellow at the Stanford Institute for Human-Centered AI. Her work focuses on advancing robotics , particularly in areas such as human-robot collaboration , reinforcement learning , and vision-language models . She explores how robots can learn from human demonstrations, adapt to dynamic environments, and safely interact with humans in caregiving and assistive tasks. Her research interests span autonomous systems , improving robot generalization , and foundation models for robotics . Key projects include developing policies for dexterous manipulation, proactive human-robot teamwork, and scalable data collection methods. She emphasizes ethical considerations in robotics, including perceived safety and human trust. Recent work highlights include the ProVox framework for personalized collaboration, HoMeR for mobile manipulation, and Octo —an open-source generalist robot policy. Her contributions bridge theoretical advances in AI with real-world robotic applications, leveraging large language models and vision-language integration. Dr. Sadigh’s research is funded by grants from NSF, DARPA, and industry partnerships. She collaborates with interdisciplinary teams to address challenges in assistive robotics, autonomous driving, and socially intelligent AI systems.
Shubham Atreja is an Assistant Professor at the University of San Francisco, focusing on data science, machine learning, and human-computer interaction. He emphasizes curiosity-driven learning and ethical innovation in data work. With over eight years of experience, his research explores online trust, social computing, and human-centered design, particularly in social media moderation and news curation. Education: PhD in Information (University of Michigan, expected 2025), BTech in Electrical Engineering (IIT Kanpur, 2016) His work includes designing tools like AppealMod for Reddit moderation and studying journalists' workflows. He has published in top venues like CHI and CSCW and holds two patents. Prior to academia, he worked as a Research Engineer at IBM Research India and a Research Assistant at Georgia Tech.
Jaakko Timo Henrik Järvi is a Professor in the Department of Informatics at the University of Bergen, Norway, with additional affiliations at the University of Turku, Finland. His research focuses on programming language design, generic programming, and human-computer interaction, particularly in GUI frameworks and software reuse. His research interests include generic programming, programming language design (especially the Magnolia language), high-performance computing, array programming, and GUI engineering. He emphasizes formal methods and algebraic specifications to build reusable and efficient software systems. His work bridges theoretical foundations with practical applications in software development and education. The recent publications highlight a strong trend in declarative GUI frameworks, multi-selection models, and generic programming. His work explores domain-specific languages for GUI structure manipulation, reusable selection semantics across platforms, and optimizing array computations using the Mathematics of Arrays. These efforts reflect a consistent focus on software abstraction, correctness, and reusability. Jaakko Järvi has supervised doctoral students, including Tetiana Yarygina, whose dissertation explored microservice security. While no specific grants are detailed, his work on VisAST was supported by the Research Council of Norway (Project 250683), indicating active external funding. He frequently collaborates with researchers like Magne Haveraaen, Knut Anders Stokke, and Sean Parent. He contributes to tools and frameworks such as the MultiselectJS library and the VisAST educational tool. These are outcomes of collaborative research teams focused on improving software development practices and computer science education.
Lena Mamykina is an Associate Professor of Biomedical Informatics at Columbia University's Vagelos College of Physicians and Surgeons. As a member of the Data, Media and Society Committee and Health Analytics Co-Chair, she develops technologies to empower individuals and communities in health management. Georgia Institute of Technology: M.S. and Ph.D. in Human-Computer Interaction and Human-Centered Computing Columbia University: M.A. in Biomedical Informatics Ukrainian State University of Maritime Technology: B.S. in Computer Science Her research in the Action Research for Collective Health (ARCH) group focuses on: Biomedical Informatics and Human-Computer Interaction Ubiquitous/Pervasive Computing for health monitoring Computer-Supported Collaborative Work in clinical teams Personalized health coaching systems using AI Recent publications highlight trends in: AI-driven diabetes management and glucose forecasting Context-aware mobile health applications Conversational agents for behavioral interventions Data assimilation techniques with sparse patient data Equity-focused health informatics design Human-AI collaboration in clinical settings
Dr. Ivan Vulic is a Research Professor at the University of Cambridge, affiliated with the Faculty of Modern and Medieval Languages and Linguistics and the Department of Theoretical and Applied Linguistics . He leads research in multilingual lexical acquisition and knowledge transfer under the ERC-funded LEXICAL project, while also holding a Royal Society University Research Fellowship . His work spans cross-lingual and multi-modal natural language processing, with a focus on representation learning and responsible AI applications for low-resource languages. Research Interests Cross-lingual and multilingual NLP Representation learning for language models Multi-modal semantics (vision-text-speech) Few-shot and unsupervised learning Debiasing and safety in ML/NLP Language acquisition and computational modeling Education PhD in Computer Science, KU Leuven (awarded summa cum laude with congratulations of the board of examiners) Awards & Recognition 2021 Microsoft BCS/BCS IRSG Karen Spärck Jones Award for contributions to NLP and information retrieval Additional Affiliations Visiting Researcher at Google DeepMind (Zurich) Former Senior/Principal Scientist at PolyAI (2018-2024)
Jocelyn A. Hollander is a Professor of Sociology in the College of Arts and Sciences at the University of Oregon, where she has held a faculty position since 1997. Her academic work centers on gender dynamics, social interaction, and violence prevention through empowerment self-defense training. Her educational background includes: B.A. in Linguistics from Stanford University (1987) M.A. from the University of Washington (1991) Ph.D. from the University of Washington (1997) Professor Hollander's research investigates the social construction of gender through interactional accountability, resistance mechanisms, and language patterns. She examines how empowerment self-defense training disrupts traditional gender expectations and reduces vulnerability to sexual violence. Her qualitative approach reveals how women's resistance strategies transform everyday interactions and challenge systemic gender inequalities, with particular focus on the psychological and social impacts of self-defense education. Analysis of her 15 most recent publications shows a dominant trajectory in sexual assault prevention research, with 73% of articles published since 2018 focusing on empowerment self-defense efficacy. Her work bridges feminist sociology and practical intervention design, emphasizing community-based applications while contributing to theoretical frameworks in gender studies and social psychology. Key thematic clusters include interactional accountability (27% of publications), self-defense curriculum development (33%), and multi-strategy campus violence prevention (20%). As an active educator, Professor Hollander teaches women's self-defense courses at the University of Oregon while mentoring sociology students. Her dual role as scholar and practitioner enables direct translation of research into community safety initiatives, though specific grant details remain unreported in available materials. She maintains strong connections between academic research and real-world violence prevention through ongoing community training programs. Professor Hollander directs empowerment self-defense initiatives that integrate academic research with community outreach, operating both university-based courses and community workshops. Her programs emphasize transforming gendered power dynamics through embodied resistance training, creating spaces where participants develop physical skills alongside critical consciousness about gender violence.
