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Elie HajjView profile

Professor

• Sustainable Paving Materials
• Asphalt Pavement Engineering
• Transportation Infrastructure Analysis
• +4 more

Elie Hajj is a Professor in the Department of Civil & Environmental Engineering at the University of Nevada, Reno (UNR), serving as Associate Director of the Western Regional Superpave Center. His research focuses on asphalt pavement engineering, sustainable materials, and infrastructure resilience. He specializes in pavement rehabilitation, numerical modeling of dynamic load impacts, and economic analysis of pavement preservation strategies. Dr. Hajj has received recognition for his 2016 ASTM award for outstanding work on pavement rehabilitation economics. He actively engages in professional service, including TRB webinars and academic seminars on topics like pavement damage assessment and vehicle operating costs. His teaching spans graduate and undergraduate courses in pavement design, materials engineering, and advanced pavement analysis. His research integrates experimental and computational methods to address challenges in pavement performance under superheavy loads, recycled material utilization, and energy-efficient construction practices. Collaborations with industry and government agencies enhance the practical applicability of his findings.

Devansh SaxenaView profile

Assistant Professor

• Responsible AI
• Human-AI Interaction
• Public Interest Technology
• +3 more

Devansh Saxena is an Assistant Professor at the University of Wisconsin-Madison, holding dual affiliations in the Information School and the School of Computer, Data & Information Sciences. His research focuses on sociotechnical practices of decision-making in high-stakes domains, particularly examining the social impacts of AI in government agencies, community-based organizations, and public health. Saxena employs mixed-methods approaches, blending computational and design methods to develop human-centered AI systems that prioritize equity and collective decision-making. He holds a Ph.D. in Computer Science from Marquette University, advised by Dr. Shion Guha and Dr. Michael Zimmer. His work intersects Human-Computer Interaction (HCI), Machine Learning, and FAccT (Fairness, Accountability, and Transparency in Sociotechnical Systems). Key areas of research include responsible AI, participatory algorithm design, and rethinking risk assessment in public sector systems such as child welfare. Saxena has received prestigious recognition, including the Best Paper Award at CHI 2023 and the Presidential Postdoctoral Fellowship at Carnegie Mellon University. Recent projects include analyzing algorithmic harms in child welfare through casenote computational analysis, advocating for participatory AI frameworks in government, and exploring ethical AI innovation in early-stage concept selection. His work emphasizes bridging technical and sociocultural dimensions to ensure technologies serve public interest.

Inna FishmanView profile

Associate Professor

• Autism Spectrum Disorders
• Developmental Neuroscience
• Brain Imaging
• +3 more

Inna Fishman, Ph.D., is a Research Associate Professor at San Diego State University's Department of Psychology within the College of Sciences. Her research investigates brain network organization in autism spectrum disorder (ASD) using multimodal MRI techniques, focusing on developmental trajectories from toddlerhood to adulthood. She directs studies on sensory processing, socioeconomic influences, and neural connectivity patterns in ASD. Research Focus: Dr. Fishman's work bridges social neuroscience and clinical neuropsychology, examining: Early biomarkers of ASD via functional/diffusion MRI Impact of bilingualism and socioeconomic factors on neurodevelopment Sleep disorders and sensory sensitivities in autistic children Aging-related neural changes in adults with ASD Publication Trends: Her recent articles (2021-2025) emphasize: 1) Advanced neuroimaging of ASD across lifespan stages, 2) Machine learning applications for diagnostics, 3) Socioeconomic and environmental modulators of brain development, and 4) Sleep/auditory processing comorbidities. Student Advising & Grants: She mentors doctoral candidates (Lindsay Olson, Jiwandeep Kohli, Bosi Chen) and leads NIH-funded projects including a clinical psychology fellowship for autism evaluation across ages. Laboratory Affiliation: Dr. Fishman co-directs the Brain Development Imaging Laboratories (BDIL), which investigates ASD manifestations through behavioral and neuroimaging approaches.

Ravi AronView profile

Professor

• Healthcare IT
• Emergent Technologies
• Healthcare Startups Valuation
• +6 more

Ravi Aron is a Professor of Healthcare Strategy & Technology at the C. T. Bauer College of Business, University of Houston, and Research Director of the Healthcare Business Institute. He holds a joint appointment in the Department of Health Systems & Population Health Sciences at the Tilman J. Fertitta Family College of Medicine. He earned his Ph.D. in Management Information Systems from New York University's Stern School of Business. His research focuses on healthcare IT, emergent technologies in healthcare operations, valuation of healthcare startups, and AI applications in healthcare. He has published widely in top journals like Management Science and Information Systems Research, and his work bridges information systems, operations management, and technology strategy. Dr. Aron has extensive teaching experience at The Wharton School, Johns Hopkins Carey Business School, and NYU Stern, winning multiple teaching awards. He advises Fortune 500 firms, startups, and policymakers on technology strategy, digital transformation, and risk assessment. His executive education programs address AI, machine learning, and digital business models for global executives. Key awards include the Dean's Faculty Excellence Award (2016), multiple teaching accolades from Wharton and Johns Hopkins, and the Herman E. Kross Best Dissertation Award (1999). His current projects explore healthcare supply chains, predictive models using machine learning, and valuing technology-enabled startups. He regularly participates in global forums like the World Economic Forum, advising on healthcare innovation and technology policy.

Nilanjan BanerjeeView profile

Professor

• Mobile Computing
• Pervasive Computing
• Sensor Systems
• +6 more

Dr. Nilanjan Banerjee is a Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC). He leads the Mobile, Pervasive, and Sensor System Lab, focusing on embedded and distributed systems for mobile, pervasive, and sustainability-based computing. His research spans renewable energy-driven systems, health diagnostics, mobile usability, and experimental testbed design. He holds a Ph.D. in Computer Science from the University of Massachusetts (2009), an M.S. from the same institution (2007), and a B.Tech. (Hons) from the Indian Institute of Technology (2004). Dr. Banerjee's work emphasizes interdisciplinary innovation, including low-power wearable devices for health monitoring (e.g., RestEaZe), cybersecurity frameworks for embedded systems (e.g., CARE), and sensor-based solutions for environmental sustainability. His contributions address challenges in mobility, energy efficiency, and accessibility, such as the Presight sidewalk localization system for visually impaired riders and the Inviz gesture-recognition textile sensors. His recent publications (2018–2021) reflect a focus on health technology, cybersecurity, and sustainable systems. Notable trends include: Integration of machine learning with sensor data for medical applications (e.g., sleep analysis, infection detection) Development of lightweight security protocols for embedded devices Exploration of renewable energy solutions for mobile and sensor networks No scientific awards are explicitly listed in the provided text. His academic advising and grant activities are not detailed here, but his lab's active research suggests significant collaborative projects. The lab also pioneers educational strategies in mobile app development and inclusive faculty recruitment through peer education programs like STRIDE.

• Artificial Intelligence
• Machine Learning
• Pattern Recognition
• +11 more

Jianhua Zhang is a Professor of Computer Science and founding deputy head of the AI Lab at the Department of Computer Science, OsloMet - Oslo Metropolitan University, Norway. He holds affiliations with the Faculty of Technology, Art and Design. His career includes roles as Scientific Director at Vekia (France), Head of Machine Learning Lab, and Professorships at East China University of Science and Technology and Beijing University of Technology. He has held visiting positions at TU Berlin, TU Dresden, and the University of Catania. Educations: PhD in Electrical Engineering and Information Sciences (Ruhr University Bochum, 2005), Postdoctoral Research at the University of Sheffield (2005-2006). Research focuses on artificial intelligence, computational intelligence, cognitive human-machine systems, neuroergonomics, affective computing, and AI-driven neuroergonomics. Applications span engineering, biomedicine, finance, and business. He has led over 20 large-scale projects and published extensively (4 books, 13 chapters, ~200 papers). Leadership roles include Chair of IFAC Technical Committee on Human-Machine Systems (2017-2023), Vice Chair of IEEE Norway Section, and editorial roles at journals like Frontiers in Neuroscience and Cognitive Neurodynamics . He organized major conferences like IFAC HMS2025 (Beijing) and ICMLT 2024 (Oslo). Awards: Stanford/Elsevier Top 2% Scientists (2023/2024), Senior Research Fellowship (CSC, 2012), Max Planck Fellowship (2011), Shanghai Pujiang Talent (2007), DAAD Scholarship (2002-2004). Grants and advising: PI for 20+ projects, advising PhD students in AI, machine learning, and control systems. Teaching includes courses on computational intelligence, IoT, and fuzzy systems at both undergraduate and graduate levels. Labs/Teams: AI Lab at OsloMet, Machine Learning Lab (Vekia), and collaborations with institutions globally. Current work emphasizes AI ethics, neuroergonomics in smart cities, and adaptive human-machine systems.

Niall WintersView profile

Research Fellow

• Educational Technology
• Global Health
• Healthcare Informatics
• +3 more

Niall Winters is a Visiting Fellow at the University of Oxford's Department of Education, previously serving as Professor of Education and Technology and an Official Fellow. His research focuses on socially-just technology innovations, particularly in healthcare and education, supported by over €7 million in funding. He holds a PhD in Computer Science from Trinity College Dublin. Key roles include co-convenor of the Critical Digital Education Research Group, director of the MSc Education (Digital and Social Change), and mentor to Kellogg students. Prior to Oxford, he was a Reader in Learning Technologies at UCL Institute of Education and Deputy Head of the Department of Culture, Communication and Media. His research integrates global health challenges with digital solutions, emphasizing community health workers' training in low-resource settings. Collaborations include the Global Centre on Healthcare and Urbanisation at Kellogg and projects with UNESCO, WHO, and the NHS. He has held fellowships at institutions like Sciences Po and MIT Media Lab Europe. Publications span mobile health technologies, gamification in medical education, and policy frameworks for digital equity. His work bridges theory and practice, advocating for ethical technology design that addresses systemic inequalities in education and healthcare systems.

Gauthier GidelView profile

Associate Professor

• Deep Learning
• Adversarial Machine Learning
• Generative Modeling
• +5 more

Gauthier Gidel is an Associate Professor at the Department of Computer Science and Operations Research (DIRO) within the Faculty of Arts and Science at Université de Montréal, where he also holds the prestigious Canada CIFAR AI Chair position. He is a core faculty member of Mila, Quebec's AI research institute, and maintains active research collaborations with leading institutions. His academic journey includes a PhD in Computer Science under the supervision of Simon Lacoste-Julien, with internships at Sierra, ElementAI, and DeepMind during his doctoral studies. Dr. Gidel's research spans multiple critical areas in machine learning, with particular emphasis on generative modeling , adversarial machine learning , and variational inequalities for machine learning. His work explores the intersection of optimization theory and practical AI systems, focusing on challenges like LLM safety alignment, multi-agent cooperation, and robustness against adversarial attacks. He is particularly known for his contributions to understanding the theoretical foundations of generative adversarial networks through variational inequality frameworks. His recent publications reveal a strong trend toward addressing critical challenges in large language model safety and alignment, with numerous 2024-2025 papers focusing on adversarial robustness, safety evaluation methodologies, and alignment techniques for LLMs. Simultaneously, his foundational work continues in optimization theory, particularly in variational inequalities and performative prediction, demonstrating his dual focus on practical AI safety concerns and theoretical machine learning foundations. Canada CIFAR AI Chair Core member of Mila Organizer of popular NeurIPS workshops on smooth games Co-founder of the ICLR blog post track Dr. Gidel actively supervises an extensive research group with approximately 10 current graduate students and numerous alumni who have secured positions at leading institutions including Inria Lyon, Oxford, and industry research labs. His research is supported by multiple substantial grants from CRSNG, MITACS, and IVADO, including the prestigious CRSNG Discovery Grant program and MITACS Acceleration Québec projects focused on fraud detection in music streaming and conditional generation. His laboratory maintains strong connections with both academic and industry partners, fostering a collaborative environment focused on advancing AI safety and theoretical understanding.

Eric MorganView profile

Professor

• Parasitology
• Epidemiology
• Climate Change Impact on Disease Dynamics
• +6 more

Professor Eric Morgan at Queen's University Belfast leads parasitology research in the School of Biological Sciences , focusing on climate-driven epidemiology of parasitic infections in animals. His work integrates predictive modeling, parasite transmission dynamics at the wild-domestic interface, and sustainable livestock health solutions. Veterinary parasitology and climate change impact Anthelmintic resistance mitigation strategies AI-enhanced diagnostic systems for animal health Current research students include Anthony George, who investigates Combining alternative approaches for helminth control in grazing livestock . Public engagement initiatives like the BUG Consortium and Poo Patrol translate findings into practical parasite management. His recent publications in 2025 address topics like flood reactors, zoonotic toxocariasis, and precision agriculture tools for parasite risk assessment.

Loris D'AntoniView profile

Associate Professor

• Programming Languages
• Software Verification
• Program Synthesis
• +4 more

Loris D'Antoni is an Associate Professor in the Department of Computer Science and Engineering at the University of California at San Diego (UCSD) . He is also a Visiting Academic at Amazon Web Services (AWS) . His research focuses on helping people write trustworthy software through techniques in program synthesis, formal verification, and machine learning robustness. Bachelor and Master in Computer Science from University of Torino (2008, 2010) PhD in Computer Science from University of Pennsylvania (2015) His research integrates programming languages , automata theory , and formal methods to ensure software reliability. Recent work explores semantics-guided synthesis and specification-aligned LLMs , with applications in network security, machine learning fairness, and automated code repair. Key trends in his publications include program synthesis , formal verification , and trustworthy AI systems . He has contributed to tools like AutomataTutor and SemGuS , a framework for customizable synthesis problems using constrained Horn clauses. Phillip R. Certain-Gary D. Sandefur Distinguished Faculty Award NSF CAREER Award Microsoft Research Faculty Fellowship Google and Facebook Faculty Awards Best Paper Award at ICDCN 2023 Distinguished Paper Award at SBES 2021 D'Antoni actively contributes to academic community service as a committee member in PLDI , OOPSLA , POPL , and CAV . He leads the Programming Systems Group at UCSD and collaborates with SemGuS research team on synthesis frameworks.

Julian BergerView profile

Research Fellow

• Human-AI Interaction
• Collective Intelligence
• Machine Learning
• +3 more

Julian Berger is a postdoctoral researcher at the Max Planck Institute for Human Development in the Center for Adaptive Rationality , where he explores how to enhance decision-making through hybrid human-AI systems. He is also a fellow of the Joachim Herz Foundation and has received funding from the Foundation of German Business and the Danish Data Science Academy. Education: M.A. Psychology in Business and Economics, Universidade Catolica Portuguesa (2021) B.A. Politics, Administration and International Relations, Zeppelin Universität (2018) His research spans human-AI collaboration , collective intelligence , and interpretable machine learning . A recurring theme in his work is developing methods to combine human expertise with AI capabilities for accuracy in domains like medical diagnostics , credit scoring , and football analytics . He has authored publications in high-impact venues such as PNAS , Nature Human Behavior , and Science and Medicine in Football . Scientific awards and funding include: Fellowship for interdisciplinary economics, Joachim Herz Foundation (2024) PhD funding from the Foundation of German Business (Stiftung der deutschen Wirtschaft) Research grant from the Danish Data Science Academy His recent article trends emphasize ensembling techniques that leverage complementary human and AI errors, algorithmic fairness, and practical heuristics like Hybrid Confirmation Trees. These works demonstrate significant improvements in diagnostic accuracy and decision cost-efficiency. Beyond academia, Berger works as a consultant and ML engineer with Simply Rational , focusing on interpretable models for financial and sports analytics. His work bridges theoretical research with real-world applications, prioritizing fairness, transparency, and human accountability in AI systems.

Kate FarrahiView profile

Associate Professor

• Machine Learning
• Digital Health
• Human Sensing
• +3 more

Dr. Kate Farrahi is an Associate Professor in the ECS department at the University of Southampton, where she leads research in the Vision, Learning and Control (VLC) Group. Previously, she was a Research Assistant at the Idiap Research Institute and earned her PhD in Computer Science from the Swiss Federal Institute of Technology in Lausanne (EPFL). Her work focuses on the intersection of machine learning and digital health, particularly in developing human sensing methods using vision and wearable technologies. She currently supervises four PhD students in Computer Science and actively accepts new PhD applications. Her research interests span machine learning applications in healthcare, including wearable device analytics, epidemiological modeling via AI, and drug discovery through generative methods. She has been recognized with a Best Paper Award (2022) and contributes to interdisciplinary research groups such as the Institute for Life Sciences and Centre for Machine Intelligence. Her work bridges computational methods with real-world health challenges, emphasizing practical deployment of AI solutions in clinical and public health contexts. Research Groups: Vision, Learning and Control; Institute for Life Sciences; Centre for Health Technologies; Centre for Machine Intelligence Key Collaborations: Cross-disciplinary projects combining computer science with biomedical engineering and public health

• Motivation
• Time Management
• Goal Setting
• +3 more

Jordan Etkin is an Associate Professor of Marketing at Duke University’s Fuqua School of Business, specializing in studies of goal pursuit, motivation, and time management. She explores how goal structures, variety in activities, and personal quantification impact behavior and well-being. Her research bridges consumer behavior, psychology, and decision science, with frequent publications in top-tier journals like the Journal of Consumer Research and Journal of Marketing Research. Education: PhD (Year not specified, but teaches since 2013) Her research interests focus on the interplay between goals and personal resources (e.g., time), including unintended consequences of tracking behaviors like step-counting. Key themes include motivation dynamics, goal conflict resolution, and temporal resource allocation. She frequently engages with popular media, appearing in outlets like the New York Times and BBC. Recent work (2020–2024) highlights topics such as time limits paradoxically increasing consumption, variety’s role in goal conflict, and machine learning’s applications in behavioral research. Her 2019 JCR Award underscores scholarly impact. Awards: 2019 JCR Awards Announcements (Recipient) Teaching responsibilities include the Marketing Core class for Fuqua’s MBA program. While no lab teams are explicitly mentioned, her research themes suggest collaborative work in behavioral science and consumer studies.

• Maritime Risk Analysis
• Autonomous Ship Systems
• Safety Verification
• +3 more

Børge Rokseth is an Associate Professor at the Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU). His work focuses on maritime systems, autonomous vessel control, and safety verification. He actively supervises Master's students and contributes to research on risk-informed control systems, hybrid power systems, and systems-theoretic process analysis (STPA). Research Interests: Rokseth's research spans autonomous ship systems, dynamic risk assessment, and safety verification. He explores risk-based decision-making for maritime autonomy, hazard identification in hybrid propulsion systems, and control function allocation in dynamic positioning. His work integrates systems theory, machine learning, and regulatory compliance (e.g., COLREGS) to enhance safety and environmental performance in marine operations. Publications: His recent work includes probabilistic trajectory prediction frameworks for autonomous ships, STPA-based safety analyses, and studies on decarbonization barriers in the maritime industry. These publications emphasize risk modeling, systems-theoretic approaches, and simulation-based verification. Teaching: Rokseth teaches courses such as TTK4130 - Modelling and Simulation, contributing to the education of future engineers and researchers in cybernetics and maritime systems.

Jean Van Den ElsenView profile

Professor

• Structural Biochemistry
• Protein Homeostasis
• Immune Evasion Mechanisms
• +5 more

Prof Jean Van Den Elsen is a Professor of Biochemistry at the University of Bath , affiliated with the Department of Life Sciences and several research centers including the Centre for Sustainable Chemical Technologies (CSCT) , Centre for Therapeutic Innovation , and Milner Centre for Evolution . They are actively accepting doctoral students and leading multidisciplinary projects at the intersection of structural biology and immunology. Education: Not explicitly mentioned Appointments: University of Bath (current), with collaborations across Chemistry, Biology & Biochemistry departments Research Focus: The laboratory investigates protein structural biology in two major areas: Complement System Interactions: Studying how pathogenic microbes like Staphylococcus aureus evade host immunity through complement system manipulation , with structural analysis of proteins such as C3d and C5 complexes. This work directly informs vaccine design and autoimmune disease treatment . Glycation Mechanisms: Developing diagnostic tools for detecting non-enzymatic sugar modifications linked to diabetes , Alzheimer's , and aging, with commercial partnerships like Abcam . Article Trends: Recent publications demonstrate: Structural analysis of complement evasion proteins (2022-2025) Engineering knob domains as miniature antibodies (2023) Evolutionary studies on cooperative behavior (2021-2025) Advancements in peptide synthesis platforms (2022-2023) Applications of AI protein folding (2020) Scientific Contributions: ORCID: 0000-0002-0367-1956 BBSRC Funding recipient (2023) 100+ citations across 76 research outputs Student Mentorship: Directly supervising 4 current PhD students and 1 postdoc, with a track record of mentoring 11 previous students including Daphne Jackson Fellows and MSCA researchers. Collaborations: Maintains active partnerships with Dr. Tony James (Chemistry), Dr. Rob Williams (Biochemistry), and industry partners UCB Celltech and Porton Biopharma Ltd. Their work contributes to UN Sustainable Development Goals 3 (Good Health), 12 (Responsible Consumption), and 13 (Climate Action).