Find Academic Supervisors

• Experimental Turbulent Flow Measurement
• Gas-Liquid Interface Dynamics
• Wind-Assisted Propulsion
• +3 more

R. Jason Hearst is a Professor at the Department of Energy and Process Engineering , Norwegian University of Science and Technology (NTNU) , specializing in experimental turbulent flow analysis. His research focuses on high Reynolds number turbulence generation, air-sea interface dynamics, aerodynamic impacts of turbulence on structures, and wind-assisted propulsion systems. He employs advanced diagnostics like Particle Image Velocimetry (PIV) and Laser-Induced Fluorescence (LIF) to explore turbulence-structure interactions and gas transfer mechanisms. Academic Milestones: PhD (2009–2014), Institute for Aerospace Studies, University of Toronto Postdoctoral Fellowship (2015–2017), University of Southampton Professor (2023–Present), NTNU Research Themes: His work bridges fundamental turbulence studies with applied energy systems, including wind turbine aerodynamics, bridge deck wind loading, and UAV icing mitigation. Current projects like reSail (wind-assisted propulsion) and GLITR (gas-liquid interface turbulence) highlight his interdisciplinary approach. Publications: Recent studies analyze freestream turbulence effects on wall-bounded flows, air-water gas transfer mechanisms, and vortex dynamics in wind turbine wakes. Collaborative articles with postdoctoral fellows (e.g., Leon Li, Pim Bullee) emphasize experimental validation and cross-institutional partnerships. Laboratory Contributions: As coordinator of the Fluid Mechanics Lab , he oversees advanced equipment for turbulence measurement and wind tunnel testing. His team includes PhD candidates and postdoctoral researchers working on topics like oxygen transport at air-water interfaces and turbulent mixing in non-Newtonian systems.

Kamal NasrollahiView profile

Professor

• Computer Vision
• Artificial Intelligence
• Biometrics
• +7 more

Kamal Nasrollahi is a Professor at Aalborg University's Department of Architecture, Design and Media Technology, affiliated with The Technical Faculty of IT and Design. He leads research in Visual Analysis and Perception, AI for the People, Mobility and Urban Studies, and Tracking Technologies. His work focuses on computer vision, anomaly detection, biometrics, and AI ethics. Research Interests: Advancing AI-driven video surveillance and privacy-preserving techniques Developing anomaly detection systems for maritime, healthcare, and urban environments Exploring multimodal fusion and deep learning architectures Creating real-world super-resolution solutions for degraded imagery Key Projects: REPAI: Responsible AI for Value Creation (2023–2027) FDF: Fully Documented Fisheries (2024–2026) Patient@home: Long-term healthcare monitoring systems COST Action 2101: Biometrics for Identity Documents Notable Contributions: Over 150+ publications in top-tier journals/conferences, including landmark works on image anonymization, fall detection, and thermal-based person re-identification. Active in creating benchmark datasets like RELLISUR and SVSR. Awards & Recognition: No explicitly stated awards, though his work has received media attention for innovations in video analytics and ethical AI. Grants & Labs: Lead researcher in multiple EU and national grants Founded the AI for the People initiative to bridge societal impact Collaborates with industry partners for real-world deployment

Elizabeth M GoldbergView profile

Adjunct Associate Professor

• Aging and Geriatrics
• Emergency Medicine
• Geriatric Fall Prevention
• +4 more

Dr. Elizabeth M Goldberg is an Adjunct Associate Professor of Emergency Medicine and Associate Professor of Health Services, Policy and Practice at Brown University. She practices at Rhode Island and Miriam hospitals and leads initiatives in geriatric emergency care and digital health innovation. Her research focuses on fall prevention, telehealth for older adults, and improving care transitions. Dr. Goldberg completed her MD at Sackler School of Medicine, followed by residency and chief residency at Brown University. She holds a Master of Epidemiology from Brown's School of Public Health and completed a postdoctoral fellowship in gerontology. Her research interests intersect aging and emergency medicine, including the GAPcare fall prevention intervention and the MyCovidRisk.app. She has led NIH-funded studies and received awards for mentorship and innovation. Key scientific awards include the Paul B. Beeson Career Development Award (2019), Technology Innovation Award (2020), and recognition as one of Providence's 40 Under Forty (2017). She currently serves on the Providence School Board and co-leads the Brown Clinical MPH program. Dr. Goldberg's work bridges clinical practice and public health, emphasizing physician-scientist training and healthcare equity. Her grants include NIH funding for digital health tools and fall prevention, with a focus on leveraging technology to improve outcomes for older adults.

• Dementia
• Late-Life Psychiatry
• Geriatric Medicine
• +5 more

Professor Brian Lawlor is the Conolly Norman Professor of Old Age Psychiatry at Trinity College Dublin (TCD), Deputy Executive Director of the Global Brain Health Institute (GBHI), and Co-Director at the Trinity Institute of Neurosciences (TCIN). His work focuses on dementia, late-life mental health, and brain health interventions. He has led over 30 years of research on dementia services, treatments, and prevention strategies. Affiliations: Trinity College Dublin – Department of Psychiatry Global Brain Health Institute (GBHI) Trinity Institute of Neurosciences (TCIN) Research interests span early dementia detection, late-life depression, and the impact of social factors like loneliness on cognitive decline. His studies frequently address caregiver support, medication effects (e.g., statins, PPIs), and environmental adjustments for dementia patients. He has contributed to multinational trials like SENSE-Cog (hearing/vision interventions) and NILVAD (nilvadipine efficacy). Key themes in his work include neurodegenerative mechanisms, polypharmacy risks, and the interplay between cardiovascular health and cognitive aging. He advocates for equitable dementia care and public awareness.

Jing FengView profile

Professor

• Human Factors Engineering
• Cognitive Psychology
• Driving Safety
• +3 more

Jing Feng is a Professor of Psychology at North Carolina State University within the College of Humanities and Social Sciences, specializing in the Human Factors and Applied Cognition Program. Her research integrates cognitive theories of attention with practical applications in transportation safety and interface design. She holds a Ph.D. in Cognitive Psychology from the University of Toronto (2011), with postdoctoral training at Baycrest's Rotman Research Institute and the University of Toronto's Mechanical and Industrial Engineering department. Her multidisciplinary work focuses on aging drivers' visual attention, driver-automation interaction, and cognitive training. She directs the Applied Cognitive Psychology Lab, which develops tools like the SWAVF task to assess visuospatial attention during walking and evaluates robotic prosthesis user preferences. Her research also explores the impact of in-vehicle displays and non-safety messages on driver behavior. Key career milestones include the Earl Alluisi Award (2021) and APA Fellow designation (2023). She has mentored students in human factors engineering and cognitive science, with notable contributions to driver distraction mitigation and interface design for aging populations. Current projects investigate automated vehicle monitoring systems and virtual reality applications in spatial skill training. Notable Awards: 2023 APA Fellow, 2021 Earl Alluisi Award, 2023 Undergraduate Mentorship Award Labs: Applied Cognitive Psychology Lab (http://www.jfenglab.com/) Key Research Themes: Driver Safety, Human-Machine Interaction, Aging Cognition

Sheriza BakshView profile

Academic

• Clinical Trials
• Pharmacoepidemiology
• Regulatory Science
• +3 more

Sheriza Baksh, PhD, MPH, is an Assistant Research Professor in the Department of Epidemiology at the Johns Hopkins Bloomberg School of Public Health. She holds affiliations with the Clinical Trials and Evidence Synthesis Center and the Center of Excellence in Regulatory Science and Innovation (CERSI). Her research focuses on clinical trial design, pharmacoepidemiology, and regulatory science, with a particular emphasis on drug safety and evidence synthesis. Education: PhD in Public Health, Johns Hopkins Bloomberg School of Public Health (2018) MPH in Public Health, Boston University School of Public Health (2009) BA in Human Biology, University of Pennsylvania (2007) Her research interests center on optimizing clinical trial methodologies, evaluating drug safety signals (e.g., cardiovascular risks of dipeptidyl peptidase-4 inhibitors), and advancing regulatory science practices. Notably, she has contributed to studies on convalescent plasma use in COVID-19 treatment and the impact of sodium-glucose cotransporter-2 inhibitors on diabetic complications. Recent work includes meta-analyses of hydroxychloroquine efficacy in hospitalized patients and a multicenter trial comparing natural vs. programmed frozen embryo transfer protocols. Her publications span high-impact journals like JAMA Internal Medicine and the New England Journal of Medicine. Baksh collaborates widely, leading studies on vaccine development, post-COVID-19 condition risks, and transfusion safety. Her lab focuses on translating epidemiological insights into actionable clinical and regulatory policies.

• Biostatistics
• Public Health Research
• Collaborative Statistical Methods
• +3 more

Alex Dahlen is a Clinical Associate Professor of Biostatistics at the NYU School of Global Public Health, leading the Collaborative Statistical Core. He holds a PhD in physics from Princeton University (2011) and previously served as a senior statistician at Stanford University's Department of Medicine. His work focuses on collaborative statistical methods for public health research, study design, and training next-generation data scientists. Education: PhD in Physics (Princeton University, 2011). Professional experience includes statistical leadership roles in academic and clinical settings, emphasizing interdisciplinary collaboration and methodological rigor. Research interests span biostatistical applications in neonatal care, healthcare data analysis, and global public health challenges. His recent studies address falls prevention, neonatal hypothermia protocols, and healthcare worker mental health during pandemics. He actively mentors junior scientists in coding, analysis, and ethical research practices. Notable contributions include benchmarking healthcare claims data and developing telemedicine strategies for neonatal care. His work integrates cutting-edge statistical techniques with real-world clinical and public health problems.

Raphaël MonatView profile

Researcher

• Formal Methods
• Static Program Analysis
• Abstract Interpretation
• +5 more

Raphaël Monat is a Research Scientist in the SyCoMoRES team at Inria Lille, affiliated with University of Lille. He holds a Ph.D. in computer science from Sorbonne Université, advised by Antoine Miné, and has designed a modern compiler for the French tax code with Denis Merigoux. His educational background includes a Ph.D. in Static Type and Value Analysis by Abstract Interpretation of Python Programs (2018-2021) at Sorbonne Université, Formal verification of Static Analyses of Floating-point Programs (2017) at MPI-SWS, Black-box Variational Inference in Probabilistic Programming (2016) at University of Oxford, and Abstract Interpretation of Concurrent Programs (2015) at École Normale Supérieure. Raphaël's research focuses on improving software quality through formal methods, particularly automated program verification. He has a special interest in implementations of computational laws (taxes, benefits) and is currently developing formal methods tools for Catala, a domain-specific language for legislative texts. He is also one of the maintainers of the Mopsa static analyzer and explores ways to facilitate the adoption of static analysis tools. His recent publications demonstrate expertise across static analysis, computational law, and program verification, with articles published in top venues including ESOP, ECOOP, and TACAS. His work shows a consistent trend toward making formal methods applicable to real-world systems, particularly in public administration contexts. ETAPS 2025 distinguished artifact for 'CUTECat: Concolic Execution for Computational Law' SV-Comp 2025 Silver Medal in the 'Software Systems' category Amazon Research Award, Fall 2024 ETAPS 2024 best tool paper award SV-Comp 2024 Gold Medal in the 'Software Systems' category Raphaël actively mentors students including Milla Valnet and Pierre Goutagny, and has received funding from Amazon Research Awards and ANR-JCJC RAISIN project for his research on resource-aware conservative static analysis. He serves as Artifact Evaluation chair for PLDI 2026 and ECOOP 2025, and participates in the 'collège logiciel' of the French Committee for Open Science.

Jaydeb SarkerView profile

Assistant Professor

• Human Factors Software Engineering
• Empirical Software Engineering
• Natural Language Processing
• +3 more

Dr. Jaydeb Sarker (he/him/his) serves as a Tenure Track Assistant Professor in the Department of Computer Science at the University of Nebraska at Omaha since Fall 2024. He previously completed his Ph.D. (2024) and MSc (2022) in Computer Science at Wayne State University, with a BS (2016) from Rajshahi University of Engineering and Technology. Research Focus : Human Factors Software Engineering, Empirical Software Engineering, Natural Language Processing, Human-Computer Interaction Current Work : Antisocial behavior analysis in software engineering platforms His publications appear in top-tier venues including FSE, TOSEM, ASE, and ESEM. He has received multiple travel grants (SIGSOFT CAPS, ACM SIGSOFT, NSF) and fellowships (Thomas C. Rumble). As a reviewer for journals like TSE and TOSEM, and committee member for conferences like Mining Software Repositories, he actively contributes to the academic community.

Sandun Malpriya SilvaView profile

Research Fellow

• Biostatistics
• Data Science
• Health Informatics
• +3 more

Dr. Sandun Malpriya Silva is a Senior Research Fellow at the Australian Institute of Health Innovation (AIHI), Macquarie University, specializing in biostatistics and data science. He holds a PhD in Statistics from Swinburne University of Technology and a BSc in Statistics from the University of Colombo. His research focuses on statistical and machine learning models for health-related problems, including physical activity programs, falls prevention in aged care, and medication management. Previously, he worked as a biostatistician at the NHMRC Clinical Trials Centre, University of Sydney, and held teaching roles at Monash University, Melbourne Business School, and Swinburne University of Technology. Research interests include predictive analytics in healthcare, systematic reviews of intervention efficacy, and the application of statistical methods to real-world health challenges. Notable projects include developing predictive tools for fall risk in aged care, analyzing medication use patterns, and optimizing pharmacist-led medication reviews. His work has been published in journals such as Journal of Safety Research , Cancer Medicine , and Biometrical Journal . Dr. Silva has received awards including the Rising Star Award (2022) and the Swinburne University Postgraduate Research Award (2017). He collaborates with institutions like the Victorian Department of Transport and Peter MacCallum Cancer Research Centre, addressing complex health issues through data-driven approaches.

• Robotics
• Artificial Intelligence
• Sensor Systems
• +4 more

Francisco Javier Acevedo Rodríguez is an Associate Professor at the University of Alcalá's Department of Signal and Communications Theory. Specializing in Robotics, Artificial Intelligence, and Sensor Systems , his research focuses on bioanalysis, multisensory integration, assistive technologies, and embedded AI systems . He leads the BAB_Group (Bioanalysis and Biosensors Group) and GRAM (Multisensorial Recognition and Analysis Group). He holds a PhD in Signal Processing from the University of Alcalá (2009), with a thesis on signal processing techniques for gas/liquid sensor systems. His work bridges theoretical signal processing with practical robotics applications, emphasizing real-world deployments in healthcare and navigation domains. Key technical contributions include semantic navigation systems, action recognition algorithms, and low-cost assistive robots for neurodevelopmental disorder patients. His research has addressed challenges in indoor localization, fall detection, and real-time video processing using ROS and AI-driven perception frameworks. He has published extensively in robotics, computer vision, and sensor systems since 2000. Notable work includes the SEMNAV navigation framework (2025) and a validated assistive robotics platform for daily living support (2021-2022).

• Computer Vision
• Robotics
• Machine Learning
• +5 more

Sergio Lafuente Arroyo is a Professor at the Department of Signal Theory and Communications at the University of Alcalá. He leads the GRAM (Multisensorial Recognition and Analysis Group), focusing on computer vision, robotics, and assistive technologies. His work integrates multisensory data for applications like traffic sign recognition, indoor navigation, and wearable health monitoring. He holds a Ph.D. from the University of Alcalá (2014) with a thesis on traffic sign detection using AI and image processing. Research interests include real-time vision systems, autonomous robotics, continual learning, and low-cost healthcare technologies. His recent work explores semantic navigation, fall detection systems, and stress/activity recognition via wearables. Over 50 publications span topics from LIDAR-based localization to pediatric assistive robotics. No scientific awards explicitly mentioned. Active in grants related to multisensory integration and assistive platforms. Supervised research on road sign inventory systems and pediatric mobility aids. Collaborates with engineering and biomedical teams. Laboratory affiliations include the GRAM Group, specializing in multisensory data fusion and real-world robotics applications.

• Artificial Intelligence
• Robotics
• Machine Learning
• +3 more

Pablo Muñoz Martínez is a permanent professor at the Department of Automation, Universidad de Alcalá. His research focuses on autonomous systems, machine learning applications in healthcare and space weather, and robotics. He is affiliated with the Space Weather (SWE) group and the Intelligent Systems Group (ISG). He holds a PhD from Universidad de Alcalá (2016), supervised by Dr. María Dolores Rodríguez Moreno. His research interests span AI-driven teleassistance systems, autonomous controller frameworks, and path-planning algorithms for robotics. Notable projects include LARES (AI-based emergency teleassistance) and TERRA (cooperative UGV-UAV exploration). He has contributed to space weather forecasting using neural networks and developed frameworks like OGATE for autonomous system evaluation. His recent work emphasizes healthcare predictive analytics, such as emergency department patient forecasting, and energy-efficient hardware techniques. His publications reflect a blend of theoretical advancements and applied solutions in robotics, AI, and space science. Awards: None explicitly mentioned. Advising and Grants: No specific grants or advisee names listed, but his research projects imply collaborative grant-funded initiatives. His work on fall detection simulators and teleassistance systems suggests involvement in healthcare technology grants. Labs/Teams: Active in SWE (Space Weather) and ISG (Intelligent Systems Group), focusing on AI, robotics autonomy, and space environment modeling.

Christine DuvalView profile

Associate Professor

• Nuclear Engineering
• Materials Science
• Chemical Engineering
• +3 more

Christine Duval is an Associate Professor in the Department of Chemical and Biomolecular Engineering at Case Western Reserve University (CWRU), part of the Case School of Engineering. She is also a member of the Cancer Imaging Program at the Case Comprehensive Cancer Center. Her research focuses on developing advanced materials and processes for separating f-elements (lanthanides and actinides) with applications in nuclear fuel recycling, nuclear medicine, and rare earth element recovery from waste streams. Duval holds a PhD from Clemson University (2017) and a BS from the University of Connecticut (2011). Her research interests span membrane technology, materials science, and environmental engineering, with a particular emphasis on sustainable separations and nuclear waste management. Notably, her lab explores functionalized membranes and biomimetic materials for selective ion adsorption. Duval has received prestigious awards, including the Presidential Early Career Award for Scientists and Engineers (PECASE) in 2025, NSF CAREER Award in 2023, and the DOE Early Career Research Award in 2020. Her publications highlight innovations in membrane design, electrochemical sensing, and actinide/lanthanide separations. The Duval Lab actively recruits PhD and postdoctoral researchers for Fall 2025, focusing on wastewater treatment and critical mineral recovery. The lab emphasizes community outreach, including educational events and collaborations with national labs like Argonne National Lab. Awards and honors include recognition for mentoring, teaching, and contributions to the field of separations science. Duval’s work bridges fundamental research with practical applications, addressing global challenges in energy sustainability and environmental protection.

David HughesView profile

Professor

• Behavior
• Bioinformatics
• Cell Biology
• +7 more

David Hughes is a Professor of Entomology and Biology at Pennsylvania State University's Department of Biology. He holds affiliations with the Department of Entomology and the Huck Institutes of the Life Sciences. His research focuses on parasite manipulation of host behavior, biodiversity of insect parasites, disease transmission in social insect societies, and the intersection of human behavior with epidemics. He has pioneered studies on zombie ant fungi and the extended phenotypes of parasites, combining fieldwork, molecular biology, and computational modeling. Education: Ph.D. in Entomology from the University of Oxford (2003), B.S. in Zoology from the University of Glasgow (1999). Awards include Marie Curie International Outgoing Fellowship (2008–2011) and Varley-Gradwell Travelling Fellowship (2004). Key research themes include understanding how parasites like Ophiocordyceps fungi control ant behavior, exploring biodiversity in tropical ecosystems, and developing AI tools for disease surveillance in agriculture and public health. Hughes collaborates across disciplines, leveraging big data and machine learning for global challenges such as crop protection and epidemic response. Recent work includes AI-based dietary assessment tools for adolescents in Ghana, deep learning models for plant disease detection, and climate-driven forecasts for pest outbreaks. His lab also investigates the cultural evolution of cities and its impact on disease dynamics. Current projects emphasize global soil moisture modeling and sustainable agricultural practices for smallholder farmers.