Elisa Baniassad is a Teaching Professor in the Department of Computer Science at the University of British Columbia (UBC), within the Faculty of Science. She specializes in software engineering education and has received numerous teaching accolades including the UBC Killam Teaching Prize and CS-Can/INFO-CAN Excellence in Teaching Award. Her courses focus on software construction, engineering principles, and advanced software design. Dr. Baniassad has taught CPSC 310 (Introduction to Software Engineering), CPSC 210 (Software Construction), and CPSC 410 (Advanced Software Engineering) across multiple terms since 2000. Her research interests span educational methodologies in software engineering, aspect-oriented programming, and the design of effective learning tools. Notable contributions include studies on team dynamics in software development, automated assessment techniques, and pedagogical frameworks for large-scale programming courses. She has authored over 50 peer-reviewed articles on topics ranging from mutation analysis in student tests to the efficacy of online learning environments. Awards include recognition for teaching excellence at UBC and contributions to computer science education. Her work emphasizes practical applications of software engineering principles in academic settings, with a focus on fostering student mastery through innovative assessment strategies and feedback mechanisms.
Prof. Giovanni Sansavini is an Associate Professor in the Department of Mechanical and Process Engineering at ETH Zürich. His research focuses on energy systems resilience, renewable energy integration, and sustainable infrastructure design. He leads projects related to grid optimization, energy policy, and risk engineering, with a particular emphasis on decarbonization strategies for Switzerland and Europe. His work bridges theoretical modeling and practical implementation, addressing challenges such as power transmission equity, distributed energy resource management, and hydrogen storage integration. Recent projects include developing data-driven frameworks for grid reliability assessment and analyzing the socio-technical impacts of energy transitions. Prof. Sansavini collaborates with industry and policymakers to ensure research informs actionable solutions. His publications highlight interdisciplinary approaches to energy system design, emphasizing the trilemma of affordability, sustainability, and security.
Christopher Vogel is a Research Fellow at New College and a Senior Research Associate in the Department of Engineering Science at the University of Oxford. He holds a first-class BE(Hons) in Engineering Science from the University of Auckland and completed his DPhil at Oxford under the Oxford Martin School’s Programme on Globalising Tidal Power Generation. His work focuses on advancing renewable energy technologies, particularly in tidal and wind energy systems. His research interests include fluid dynamics of tidal turbines, aerodynamic performance optimization, blade design under erosion, and large-scale renewable energy array modeling. He has contributed to projects like the Tidal Energy Research Group and the FastBlade facility for full-scale tidal blade testing. Vogel’s work integrates computational fluid dynamics (CFD), experimental testing, and multi-scale analytical models to address challenges in energy extraction efficiency, structural durability, and system reliability. Recent publications highlight advancements in actuator line methods for turbine wake prediction, uncertainty quantification in blade-element momentum theory, and dynamic loading analysis of tidal arrays. His studies often bridge theory and application, emphasizing practical solutions for marine and wind energy deployments. Collaborations include the Tidal Benchmarking Project and investigations into hybrid systems combining wave energy converters with breakwaters. Vogel’s interdisciplinary approach addresses both technical and environmental dimensions of sustainable energy systems.
Traci J. Hess is the Douglas & Diana Berthiaume Endowed Professor of Information Systems and Senior Associate Dean at the Isenberg School of Management, University of Massachusetts Amherst. She holds a PhD (1999), MA (1997) in Information Systems from Virginia Tech, and a BS in Accounting from the University of Virginia (1988). Her academic career includes roles at Washington State University and industry experience as Senior Vice President in banking and auditing roles at Ernst & Young. Her research focuses on Human-Computer Interaction , Decision Support Systems , and Trust in Digital Technologies . She explores topics like online review dynamics, privacy mechanisms in health communities, and algorithmic labor platforms. Hess has published extensively in journals like Journal of the Association for Information Systems and MIS Quarterly , and her work bridges cognitive psychology with technology design. Hess has received prestigious awards including the Isenberg Outstanding Research Award (2012) and Transactions on Human-Computer Interaction Best Paper Award (2011). Her teaching spans Business Intelligence , Database Management , and Research Methods . She has advised numerous graduate students (not listed explicitly in texts) and contributes to digital strategy research. Her recent work (2023–2024) examines reviewer badges’ impact on consumer trust and human agency in algorithmic labor systems. She emphasizes user-centric design principles to mitigate negative emotional responses to technology (e.g., technostress).
Samuel N. Meisel is an Assistant Professor at Boston University, directing the SUMMIT Lab. Holding a PhD in Clinical Psychology from SUNY Buffalo (2020), he completed pre-doctoral training at Brown University and NIAAA-funded postdoctoral fellowships at E.P. Bradley Hospital and Brown’s Center for Alcohol and Addiction Studies. His work investigates how social relationships (peer/caregiver interactions) intersect with developmental factors to shape adolescent substance use etiology and treatment efficacy, emphasizing mechanisms of behavior change and scalable intervention design. Education PhD in Clinical Psychology, University at Buffalo (2020) Research Interests : Focuses on developmental pathways to substance use, treatment mediators, and the role of social contexts (e.g., family dynamics, school environments) in influencing adolescent behavior. His studies leverage tools like ecological momentary assessment and examine topics such as sleep-quality effects on substance use, caregiver practices in outpatient treatment, and validation of parenting assessment tools. Key Trends in Publications : Recent work emphasizes real-time behavioral dynamics, sleep-substance use links, and validation of clinical instruments. His 2025 studies highlight social recovery capital’s role in treatment outcomes and self-efficacy mechanisms in addiction science. Grants & Funding : Supported by NIAAA grants (F32, K99 postdoctoral fellowships). Current projects include family-based treatment protocols and interventions addressing disparities in youth substance use care. Labs/Teams : Directs the SUMMIT Lab, focused on translational research to improve adolescent health outcomes through evidence-based practices and community partnerships.
Ludovic Renou is a Professor of Economics at Queen Mary University of London, affiliated with the School of Economics and Finance. He serves as a CEPR Fellow and Associate Editor at Games and Economic Behavior . His research focuses on economic theory, particularly game theory, information design, and strategic interactions. He has contributed to topics including repeated games, persuasion mechanisms, and networked economic systems. Recent work explores themes like human-machine interaction in decision-making, cross-verification in communication networks, and contracting under persistent information. His 2020 paper in the American Economic Review advanced revealed preference analysis under risk and uncertainty. Awards: CEPR Fellowship Renou advises on research projects but no formal advisees are listed. His professional activities include serving on the REF2021 Economics sub-panel. Outside academia, he is an avid runner with personal bests in multiple distances, emphasizing training regimens and collaborative running ethics outlined in his 'Four Axioms for Collaboration.'
Professor Ian Brunton-Smith is a leading academic in Criminology and Advanced Quantitative Methods at the University of Surrey, Department of Sociology. He holds the role of Professor of Criminology and Research Methods, with affiliations including the Surrey Centre for Criminology and editorial positions at journals such as Sociology and the Journal of the Royal Statistical Society Series A . His research focuses on improving crime measurement, multilevel modeling, Bayesian statistics, and the public understanding of science. He has led projects like the ADR UK Data First Evaluation Fellowship and Re-counting Crime, addressing issues like police under-counting and crime data reliability. He currently supervises PhD student Megan Georgiou and teaches on the MSc Social Research Methods program. His work bridges criminological theory and methodological innovation, with notable contributions to topics like hate crime impacts, prisoner reentry outcomes, and interviewer effects in surveys. He has served on the 2021 REF panel for Sociology and advisory groups for police funding formulas. Education: Holds a PhD in Sociology, with prior academic roles at the University of Warwick (Director of the Warwick Q-Step Centre). His research integrates quantitative rigor with real-world policy applications, particularly in crime prevention and data accuracy. Grants and Projects: Principal Investigator for projects such as 'Re-counting Crime: New Methods to Improve the Accuracy of Estimates of Crime' (ESRC, £299,261) and 'ADR UK Data First Evaluation Fellowship' (£177,202). Collaborations include work on synthetic crime data and carbon footprint analysis of crime prevention measures. Awards and Recognition: While no explicit awards are listed, his extensive editorial roles and leadership in high-impact research initiatives reflect his scholarly influence. Labs and Teams: Co-director of the Surrey Centre for Criminology and involved in cross-disciplinary teams analyzing crime data, survey methodology, and environmental criminology.
Dr. Ciarán Hanley is a Lecturer in Structural Engineering at University College Cork (UCC), specialized in bridge and infrastructure systems. He holds a PhD in Civil Engineering from UCC (2017), following a BEng (Ord) and BE (Hons) in Civil Engineering (2010–2012). His research focuses on performance-based design, structural safety, and sustainable infrastructure, with contributions to bridge management systems and life-cycle assessment. He serves as a technical reviewer for journals like Structure and Infrastructure Engineering and ICE - Bridge Engineering , and is a board member of the Civil Engineering Research Association of Ireland. Education: BEng (Ord) Civil Engineering, UCC, 2010 BE (Hons) Civil Engineering, UCC, 2012 PhD Civil Engineering, UCC, 2017 Professional Memberships: Institution of Structural Engineers (IStructE) International Association of Bridge and Structural Engineering (IABSE) Fédération Internationale du Béton (FIB) International Association of Shell and Spatial Structures (IASS) His research interests emphasize probabilistic design, structural reliability, and resilience of infrastructure. Key themes include multivariate analysis of bridge networks and the integration of sustainability into infrastructure management. He has contributed to EU projects like TU1406 and serves as Rapporteur for EuroStruct. His publications span over a dozen peer-reviewed articles in journals like Journal of Structural Integrity and Maintenance and Proceedings of the ICE . Dr. Hanley’s teaching includes courses on structural mechanics, prestressed concrete, and design studios. He was a finalist for Engineers Ireland Chartered Engineer of the Year (2019) and actively engages in consultancy for bridge and marine structure design.
YuAnn Li is an Assistant Professor in the Department of Electrical Engineering at the University of Pittsburgh, affiliated with the Swanson School of Engineering. Previously, she held academic positions at FAMU–FSU College of Engineering (2019–2024) and Sichuan University (2009–2018). She earned her B.S., M.S., and Ph.D. in Electrical Engineering from Wuhan University in 2003, 2006, and 2009, respectively. Her research focuses on power systems, renewable energy integration, power electronics, and grid modernization. Notable contributions include advancements in inverter technology, hybrid circuit breakers, and grid stability solutions. Her work bridges theoretical power analysis (e.g., spacetime pq theory) with practical applications like solar forecasting and fault current management. Publications span key journals such as IEEE Transactions on Power Electronics and IEEE Journal of Emerging Topics in Power Electronics. Her research emphasizes grid resilience through energy storage systems and smart grid innovations. No scientific awards are explicitly mentioned. Her advising and grants sections remain unspecified in available texts. She is active in lab and team collaborations within power systems and energy electronics domains.
Katia Jaffres-Runser is a full Professor at Institut National Polytechnique de Toulouse (Toulouse INP) , affiliated with the ENSEEIHT engineering school and the IRIT laboratory , where she leads the RMESS team. She holds a PhD from INSA Lyon and completed a prestigious Marie Curie postdoctoral fellowship at Stevens Institute of Technology and INSA Lyon. PhD : Institut des Sciences Appliquées de Lyon (INSA Lyon), 2005 M.Sc. : INSA Lyon, 2002 Diplôme d’Ingénieur en Télécommunications : INSA Lyon, 2002 Her research centers on performance evaluation and optimization of networks , particularly in wireless sensor networks, IoT, embedded systems, and complex networks. She applies advanced techniques like Google Matrix analysis, game theory, and deep reinforcement learning to improve network reliability, synchronization, and efficiency. Her work spans theoretical modeling and practical implementations in avionics, automotive, and industrial systems. Her recent publications highlight a strong trend in time-sensitive networking (TSN) , network synchronization , AI-driven optimization , and complex network analysis using Wikipedia and trade data. She has led major projects like MACACO, GOIA, and the Maison du Quantique Occitanie, focusing on real-time, reliable, and intelligent networking solutions. Scientific Awards: Best Paper Award on Propagation, IEE International Conference on Antennas and Propagation, 2003 STIC Innovation Prize, 2005 Marie Curie Outgoing International Fellowship, 2007–2010 Prime d'Excellence Scientifique (2013–2016) PEDR (2017–2021) RIPEC C3 (2022–2025) She has advised PhD students and contributed to national and international scientific service, including committee memberships in CoNRS , HCERES , and ACM N²Women . She has served on award juries and grant review panels. Her leadership extends to being Vice-President for Education at Toulouse INP (2021–2024) and Team Leader of RMESS at IRIT (since 2024) . She is actively involved in research labs and collaborative teams such as: RMESS Team , IRIT Laboratory – leading research on network modeling and embedded systems MACACO Project – international collaboration on adaptive communication networks GOIA and APPLIGOOGLE Projects – applying Google Matrix to AI and complex networks IRT EDEN – evaluating determinism in embedded networking
Asta Halkjær From is a postdoctoral researcher in the Department of Computer Science at the University of Copenhagen, affiliated with the Software, Data, People & Society (SDPS) section under Dmitriy Traytel. She previously completed her PhD at DTU Compute from 2020 to 2023, focusing on formalized deduction methods in computational logic. She holds a Master’s and Bachelor’s degree from DTU in Computer Science and Software Technology, respectively, with a specialization in Artificial Intelligence and Algorithms. Her research lies at the intersection of formal logic and computer science, particularly in automated reasoning, proof assistants (Isabelle/HOL and Lean), and mechanized metatheory. She has contributed extensively to synthetic completeness proofs, tableau systems, and verified theorem provers. Her work emphasizes formal verification of logical systems, including epistemic logic, hybrid logic, and first-order logic, with a focus on soundness and completeness. The recent publications highlight a consistent trend: the mechanization of logical foundations in proof assistants. Her work bridges theoretical logic with practical verification tools, enabling reliable automation in theorem proving. She has developed and verified provers, explored axiomatic systems, and advanced the methodology of synthetic completeness, often leveraging Isabelle/HOL’s framework. Distinguished Paper Award, CPP 2023 DTU Young Researcher Award DTU Travel Grant (Executive Board Recognition) Otto Mønsted Fonden Travel Grant She has supervised BSc and MSc theses, special courses, and research projects at DTU, and currently teaches Software Development for Digital Health . She has served on program committees for CPP, ITP, and Dalí workshops and has reviewed for journals including Journal of Automated Reasoning and Journal of Logic and Computation . She has also participated in international research visits, including at VU Amsterdam. She is actively involved in building tools for formal reasoning and maintains a personal website with resources, including an Isabelle snippets generator and bibliography tools. Her work continues to advance the foundations of formal logic through mechanized proofs and practical automation.
John Hughes, PhD, is an Associate Professor and Chair of the Department of Biostatistics and Health Data Science at Lehigh University's College of Health. With nearly 30 years of experience in higher education, he has held positions at institutions including Frostburg State University, the University of Minnesota, and Pennsylvania State University. His methodological research focuses on statistical models for dependent data, Bayesian methods, and spatial and spatiotemporal analysis. He has developed numerous software packages for R and Perl, including copCAR , ngspatial , and krippendorffsalpha . Dr. Hughes' interdisciplinary work spans environmental health, bioimaging, vaccine hesitancy, and spatial epidemiology of HPV-related cancers. He has consulted for organizations such as the Courage Kenny Research Center and Temple University. His education includes a PhD in Statistics from Penn State University and an MS in Applied Computer Science from Frostburg State University. His research emphasizes statistical computing and the application of advanced models to health data. Recent work includes methodologies for agreement coefficients, environmental noise measurement, and spatial analysis of vaccination refusal patterns. Dr. Hughes teaches courses in biostatistics, data science, and programming, reflecting his dual role as a teacher-scholar. Professional contributions include software development, collaborative research projects, and academic leadership. His work bridges computational innovation and real-world health challenges, positioning him as a key figure in modern biostatistical research.
Haihua Chen is an Assistant Professor of Data Science in the Department of Information Science at the University of North Texas (UNT), with a co-affiliation in Health Informatics. They lead the Intelligent Data Engineering and Analytics (IDEA) Lab, focusing on interdisciplinary research in artificial intelligence, data science, and informatics. Chen earned a Ph.D. in Information Science (concentrating in Data Science) from UNT in 2022, an M.S. in Information Science from Wuhan University, and dual B.S. degrees in Information Science and English Literature from Central China Normal University. Research interests span applied machine learning, data quality evaluation, NLP, and informatics applications in legal and healthcare domains. Notable work includes developing frameworks for measuring scientific novelty, constructing high-quality legal and biomedical datasets, and leveraging AI for precision medicine and disaster response. Chen has secured over $499K in external grants, including NSF REU and HSI projects, and $20K+ in internal grants. Their work has been published in top journals like Journal of Informetrics , IEEE Transactions on Reliability , and Scientometrics , with a strong focus on innovation measurement and data-centric AI. Teaching includes courses on computational methods, data analysis, and AI in healthcare. Professional leadership roles include chairing ASIS&T SIG-STI and editorial roles for Journal of the Association for Information Science and Technology , Knowledge and Information Systems , and others. Awards include UNT’s Great Grads Award and the Linda Schamber Writing Award.
Ramya Korlakai Vinayak is the Dugald C. Jackson Assistant Professor in the Department of Electrical and Computer Engineering at the University of Wisconsin-Madison. She also holds affiliations with the Department of Computer Science and the Department of Statistics at UW-Madison. Her research program bridges theoretical machine learning with practical applications in data science and crowdsourcing. Education: PhD in Electrical Engineering from California Institute of Technology (Caltech), advised by Prof. Babak Hassibi B.Tech in Electrical Engineering with minor in Physics from Indian Institute of Technology Madras (IIT Madras) Dr. Vinayak's research focuses on developing theoretically grounded machine learning tools for reliable inference using data from human sources. Her work spans machine learning theory, statistical inference, and crowdsourcing systems, with particular emphasis on preference learning, metric learning, and robust dataset construction. She has pioneered methods for learning from limited pairwise comparisons, auto-labeling systems, and human-in-the-loop out-of-distribution detection. Her recent publications reveal a consistent trajectory toward building practical machine learning systems that incorporate human feedback while maintaining theoretical guarantees. The pattern shows increasing focus on ethical considerations in AI, particularly regarding bias in generative models and reliable human-AI collaboration frameworks. Scientific Awards: Faculty for the Future fellowship (2013-2015) from Schlumberger Foundation NSF CAREER Award American Family Funding Initiative Award with Fred Sala Dr. Vinayak leads an active research group with multiple PhD students across ECE and CS departments. She has secured significant research funding including an NSF grant for "Uncovering the cognitive and neural fingerprints that make each of us unique" in collaboration with Tim Rogers, Rob Nowak and Brad Postle. She is also co-organizing the MidWest Machine Learning Symposium and NeurIPS tutorials on dataset construction. Her research group operates at the intersection of theory and practice, developing mathematically grounded frameworks that address real-world challenges in dataset construction, human-AI collaboration, and reliable machine learning systems.
S. Alexander Haslam is a Professor of Social and Organizational Psychology and Laureate Fellow at the University of Queensland's School of Psychology, where he maintains an active research program with over 300 peer-reviewed articles and 15 authored or edited books. He currently serves as Associate Editor of The Leadership Quarterly and previously held the Chief Editor role for the European Journal of Social Psychology . His work bridges academia and real-world application through interventions like Groups 4 Health and More Than Sport, targeting mental health via social identity principles. Haslam's research centers on social identity theory and group processes across organizational, health, and social contexts. He examines how shared identities influence leadership, mental health outcomes, and collective resilience, with key applications in workplace stress, athletic performance, retirement transitions, and emergency response interoperability. His social identity model of leadership challenges traditional views by emphasizing group-based influence, while interventions such as social identity mapping directly address loneliness through community identification. The 2025 articles reveal three dominant trends: (1) mental health applications in high-stress occupations (construction, emergency services), (2) identity leadership in sports across cultures, and (3) organizational identity in crisis scenarios. Methodologically, they feature randomized controlled trials, longitudinal designs, and cross-national collaborations—particularly in Japan and Europe—validating the social identity approach for loneliness reduction, team performance, and ethical behavior. Common threads include psychological safety, group membership multiplicity, and intervention scalability. Scientific awards include Distinguished Contribution to Psychological Science from both the Australian Psychological Society and British Psychological Society, plus his 2022 appointment as a Member of the Order of Australia for 'significant service to higher education, particularly psychology, through research and mentoring.' While specific grant details are absent, his work is embedded in major collaborative projects like the Global Identity Leadership Development Project and pandemic response studies. He mentors researchers globally, with his leadership evident in large-scale cross-cultural teams (e.g., 25+ co-authors on Capitol attack analysis). Policy impact is demonstrated through advisory roles in social prescribing and mental health frameworks. Haslam co-leads the Groups 4 Health intervention team and develops tools including the Identity Leadership Inventory–Youth (ILI-Y) and Visual Identity Leadership Scale (VILS). His research group collaborates across sports, clinical, and emergency domains, with ongoing projects on psychedelic therapy, retirement transitions, and AI-human interaction. The BBC Prison Study remains a foundational reference for his organizational identity work.
