Find Academic Supervisors

Vineet PandeyView profile

Assistant Professor

• Human-Computer Interaction
• Digital Health
• Citizen Science
• +3 more

Vineet Pandey is an Assistant Professor at the Kahlert School of Computing, University of Utah, and a Responsible AI Faculty Fellow starting Spring 2025. His research focuses on human-centered computing tools to bridge communities and institutional experts in science and medicine, emphasizing digital health and citizen science. He holds a Ph.D. in Computer Science from UC San Diego (2013-2019) and postdoctoral roles at MIT (2022-2023) and Harvard University (2020-2022). Education: Ph.D. in Computer Science, UC San Diego (2013-2019) Postdoctoral Researcher, MIT (2022-2023) Postdoctoral Fellow, Harvard University (2020-2022) Research Interests: Designing systems for community-led scientific work Remote health assessment tools for neurological disorders Social platforms for public participation in policymaking Collaborations with rare disease communities and healthcare institutions Articles Trends: Recent work spans motor impairment monitoring in ataxia-telangiectasia, digital phenotyping in ALS, and citizen science platforms like Galileo. Earlier contributions include key-value store systems and microbiome research via the American Gut Project. Scientific Awards: 2019 School of Engineering Henry Booker Award for Exemplary Ethical Engineering Advising/Grants: Supervises PhD/MS/BS students on HCI projects in digital health and citizen science. Alumni include Jenny Yijun Zhan (MSD) and Gunasekhar Athuluri (CS MS). Teaches courses like 'Designing Digital Health Systems' and 'Designing Human-Centered Systems'. Labs/Teams: Leads a multidisciplinary group collaborating with medical experts, rare disorder communities, and institutions. Current projects include fine-finger tracking for motor performance analysis and platform design for participatory science.

Hojjat AdeliView profile

Professor

• Structural engineering
• Computational neuroscience
• Civil engineering
• +7 more

Hojjat Adeli is an Academy Professor at The Ohio State University (OSU) with courtesy appointments in the Departments of Neurology, Neuroscience, and Biomedical Informatics. He has held the Abba G. Lichtenstein Professorship in Infrastructure Engineering (2003-2013) and served as Editor-in-Chief of Computer-Aided Civil and Infrastructure Engineering for 25 years. Academy Professor, OSU (2018–present) Professor of Neurology, Neuroscience, and Biomedical Informatics (by courtesy, since 2015-2002) His research interests span interdisciplinary domains at the intersection of engineering and neuroscience, focusing on: Computational neuroscience and neurocomputing Biomedical signal processing (particularly EEG-based diagnostics) Machine learning and computational intelligence applications Smart infrastructure systems and structural engineering Optimization algorithms in civil and biomedical contexts His research trends demonstrate a synergy between: Neural network development for medical diagnostics Wavelet and chaos theory in epilepsy detection Computational intelligence for structural engineering Hybrid models integrating fuzzy logic and genetic algorithms Scientific awards and honors include: Multiple IEEE Fellowships and AAAS Fellow Thomson Reuters Highly Cited Researcher in Engineering and Computer Science Hojjat Adeli Awards for Neural Systems and Innovation in Computing Elections to international academies in Poland, Lithuania, and Spain Scott Award for Engineering Education and Distinguished Member ASCE

• Biostatistics
• Clinical Trials
• Public Health
• +8 more

Professor Ian Marschner is a leading academic in biostatistics, currently holding the position of Professor of Biostatistics and Co-Director of Biostatistics at the NHMRC Clinical Trials Centre, University of Sydney. He has extensive experience spanning over 30 years, including roles as Professor and Head of the Department of Statistics at Macquarie University, Director of Biometrics at Pfizer, and Associate Professor at Harvard University. His research focuses on biostatistical applications in clinical trials, epidemiology, and public health, with a particular emphasis on adaptive trial designs, meta-analysis, and disease surveillance. Professor Marschner has contributed to major clinical trials in cardiovascular medicine, oncology, HIV/AIDS, neonatal/perinatal care, and COVID-19. He co-authored the book Inference Principles for Biostatisticians and is involved with the Biostatistics Collaboration of Australia (BCA) in developing and teaching the Masters of Biostatistics program. His grants include the NHMRC Centre of Research Excellence (AusTriM) and a National Critical Research Infrastructure Initiative grant totaling over $20 million. Research students under his supervision include Aydin HIBBERT, focusing on generalized joint regression models for longitudinal data. His work addresses methodological challenges such as bias in early-stopped trials, surrogate endpoints, and statistical frameworks for adaptive experiments. Recent contributions include risk modeling for diabetes, cardiovascular mortality prediction, and biomarker analysis in cancer therapies.

Mark KramerView profile

Professor

• Neuroscience
• Computational Neuroscience
• Mathematical Modeling of Neural Activity
• +5 more

Mark Kramer is a Professor in the Department of Mathematics & Statistics at Boston University. He belongs to the Applied Mathematics research group, focusing on mathematical, statistical, and machine learning approaches to characterize brain activity. His work bridges data-driven neuroscience with computational methods, exploring topics like biophysical models of neurons, field models of neural populations in epilepsy, and theoretical questions about brain rhythms. His research interests include: Biophysical modeling of single-neuron dynamics Neural population activity in pathological states Machine learning for detecting abnormal brain rhythms Analysis of cross-frequency coupling and coherence Kramer has developed educational resources like Case Studies in Neural Data Analysis using both MATLAB and Python. These materials teach practical data analysis techniques for spike trains and field data, emphasizing hands-on implementation over theoretical mathematics. He has received funding from NIH and NSF for computational neuroscience projects. His recent publications focus on epilepsy research, sleep spindle analysis, and neural signal processing. The work spans from developing statistical frameworks to understanding network dynamics in seizure termination and exploring phase consistency in neural data. Notably, his coherence studies revealed non-intuitive coupling patterns between brain regions, demonstrating that low-amplitude rhythms can be more informative than dominant ones.

Jeffrey DoserView profile

Assistant Professor

• Ecological Modeling
• Species Distribution Analysis
• Spatial Statistics
• +3 more

Jeffrey Doser is an Assistant Professor in the Department of Forestry and Environmental Resources at North Carolina State University (NC State), within the College of Natural Resources. His research focuses on ecological modeling, species distribution analysis, spatial statistics, and biodiversity monitoring. He specializes in developing R software tools for ecological data analysis, such as the spAbundance and spOccupancy packages. His work emphasizes improving statistical methods for occupancy models, integrating acoustic and survey data, and addressing environmental challenges like invasive species and climate change impacts on ecosystems. Key research themes include species-environment interactions, spatially varying coefficients in ecological models, and functional reproducibility in scientific coding. His recent studies address topics such as American chestnut restoration, wild bee community dynamics, and early detection of invasive aquatic species. Doser collaborates on interdisciplinary projects involving forest inventory, avian soundscapes, and long-term ecological monitoring. His publications (2020–2025) highlight methodological advancements in species distribution modeling, occupancy frameworks for multi-season data, and applications of Bayesian approaches. He advocates for rigorous statistical practices and reproducible research in ecology.

Can DincerView profile

Professor

• Bioanalytical Materials
• Sensors and Microsystems
• Data Science
• +4 more

Prof. Can Dincer is a Professor of Sensors and Wearables for Healthcare at the TUM School of Computation, Information and Technology, Technische Universität München (TUM). His research focuses on bioanalytical materials, wearable sensors, and AI-driven diagnostics for One-Health applications, integrating disposable sensor technology with data science. He holds a doctorate from the University of Freiburg (summa cum laude, 2016) and worked as a visiting scientist at Imperial College London before joining TUM in 2024. He is a member of the Munich Institute of Biomedical Engineering (MIBE). Key research interests include: Development of wearable biosensors for real-time health monitoring CRISPR-based diagnostics for nucleic acids and proteins AI integration for therapeutic drug monitoring in sepsis and other critical conditions Environmental health connections via point-of-need diagnostics Notable achievements include the 2021 Biosensors & Bioelectronics Best Paper Award and inclusion in Stanford's World's Top 2% Scientists since 2022. His work spans clinical applications, microfluidic platforms, and nanotechnology-based solutions for healthcare challenges. Publications highlight innovations like optogenetic bioassays (Science Advances, 2024), CRISPR-powered multiplexed biosensors, and wearable systems for continuous biomarker monitoring. His research bridges material science, electrical engineering, and biomedicine to create practical diagnostic tools. Prof. Dincer collaborates across disciplines, focusing on translating lab innovations into clinical and commercial applications through advanced sensor technologies.

Camilo MoraView profile

Professor

• Climate Change Impacts
• Biodiversity Conservation
• Environmental Science
• +5 more

Camilo Mora is a Professor in the Department of Geography at the University of Hawaii at Manoa, where he maintains an active research laboratory and teaches courses on environmental issues, biogeography, and data analysis. His academic journey began with a BSc in Marine Biology from Universidad del Valle in Colombia (1999), followed by a PhD in Biology from the University of Windsor, Canada (2005). He completed postdoctoral fellowships at the University of Auckland (2005), Scripps Institution of Oceanography (2006-2008), and Dalhousie University (2008-2010). BSc, Marine Biology, Universidad del Valle, Colombia (1999) PhD, Biology, University of Windsor, Canada (2005) Postdoctoral Fellow, University of Auckland (2005) Postdoctoral Fellow, Scripps Institution of Oceanography (2006-2008) Postdoctoral Fellow, Dalhousie University (2008-2010) Mora's research spans interconnected lines focused on understanding biodiversity patterns and their modification by human activities, with particular emphasis on climate change impacts. His lab specializes in big data analytics applied to diverse environmental challenges including heatwaves, disease transmission, marine ecosystems, and even unconventional topics like Bitcoin's environmental footprint. The Mora Lab operates on a 'divide and conquer' approach to tackle large research questions by breaking data gathering into individual parts that can be concatenated into central databases. Mora has received the CSS Excellence in Research award (2014) for his significant contributions to environmental science. His influential publications include groundbreaking work on the global risk of deadly heat (2017), the projected timing of climate departure from historical variability (2013), and the finding that over half of known human pathogenic diseases can be aggravated by climate change (2022). CSS Excellence in Research (2014) Highly cited publications in Nature and Nature Climate Change Research featured in major international media outlets Development of innovative research methodologies for large-scale analyses Mora leads an active research group that engages students in the full scientific process from idea generation to publication. His approach to mentoring involves creating yearly classes where graduate students, professors, and international advisors collaborate to tackle significant research questions, with papers typically completed within a single semester. His Carbon Neutrality Challenge project, spearheaded by his daughter Asryelle Mora, provides a practical mechanism for individuals to offset carbon emissions through tree planting. The Mora Lab maintains a distinctive approach to environmental research, working on seemingly diverse topics from reef fishes to Bitcoin, united by their reliance on big data analytics. This interdisciplinary methodology has produced impactful research across multiple domains of environmental science and climate change impacts, establishing Mora as a significant contributor to our understanding of humanity's environmental challenges.

• Malaria
• Implementation Science
• Epidemiology
• +2 more

Adam Bennett is an Associate Professor of Epidemiology & Biostatistics at the University of California, San Francisco School of Medicine. His primary research focuses on malaria epidemiology, global health equity, and implementation science, with extensive field work in Southeast Asia (Laos, Thailand, Vietnam) and Africa (Zambia, Namibia). He is affiliated with UCSF's Institute for Global Health Sciences. Dr. Bennett's research examines innovative malaria control strategies including: Targeted interventions for high-risk populations (forest-goers, miners, agricultural workers) Reactive drug administration strategies Genomic epidemiology of malaria transmission Cost-effectiveness of elimination approaches Implementation science in low-resource settings His recent publications demonstrate a strong focus on malaria elimination methodologies, spatial epidemiology, and intervention studies in endemic regions. Research consistently addresses diagnostic approaches, drug administration protocols, and vector control methods tailored to specific transmission contexts.

Christer MalmView profile

Professor

• Sports Medicine
• Exercise Physiology
• Proteomics
• +3 more

Christer Malm is a Professor at Umeå University's Department of Community Medicine and Rehabilitation, Section of Sports Medicine. His research spans molecular muscle adaptation, anti-doping technologies, and physical performance optimization for firefighters and athletes. Primary Affiliation: Umeå University, Sweden Key Focus Areas: Exercise physiology, proteomics, anti-doping, muscle disease mechanisms Research Interests: Muscle Adaptation: Revisiting the damage-repair hypothesis using proteomic screening to study cytoskeletal remodeling. Anti-Doping: Developing proteomic methods to detect autologous blood doping and investigate erythrocyte breakdown mechanisms. Work Capacity: Establishing physiological benchmarks for Swedish firefighters through extensive testing. Musculoskeletal Diseases: Comparative proteomic analysis of trapezius, vastus lateralis, and extraocular muscles to uncover disease resistance mechanisms. Exercise Impact: Exploring how physical activity modulates immunity in health and disease contexts. Scientific Contributions: Over 20 years of publications in Journal of Sports Sciences , PLOS ONE , and Scandinavian Journal of Medicine & Science in Sports , including studies on anabolic steroid effects and cold climate physiology. Ongoing Projects: PhD studies on blood doping detection, firefighter performance limits, and cross-country skiing physiology. Contact: christer.malm@umu.se

Ruben MartinsView profile

Assistant Professor

• Constraint Programming
• Program Synthesis
• Formal Verification
• +3 more

Ruben Martins is an Assistant Professor at Carnegie Mellon University's School of Computer Science and serves as the program director of the Master of Science in Computer Science (MSCS) . His research focuses on the intersection of constraint programming, program synthesis, analysis, and verification, with recent work aiming to make formal methods tools more accessible through automated reasoning. Ruben earned his Ph.D. with honors from the Technical University of Lisbon, Portugal (2013) , followed by postdoctoral research at the University of Oxford (2014-2015) and UT Austin (2015-2017) . Research Interests : Ruben's work bridges constraint programming and program synthesis , with applications in software verification , optimization , and automated reasoning . He has developed award-winning tools like Open-WBO , a modular MaxSAT solver that has won gold medals in international competitions. His publications span top-tier venues such as POPL , PLDI , FSE , SAT , and CP , often addressing real-world challenges from program analysis to network security. Scientific Awards include: Distinguished Paper Award at PLDI 2018 Distinguished Paper Award at FSE 2021 Distinguished Paper Award at SAT 2022 Gold medals for Open-WBO in MaxSAT competitions Teaching & Advising : Ruben mentors Ph.D., Master’s, and undergraduate students in research projects related to program synthesis, formal methods, and constraint solving. He teaches courses such as Bug Catching: Automated Program Verification and Advanced Topics in Logic: Automated Reasoning and Satisfiability , emphasizing hands-on experience with tools like Why3. His advising spans topics from AI-driven program repair to network protocol verification , fostering collaboration across disciplines.

Zhenzhou WangView profile

Research Fellow

• Composite Materials
• Cryogenic Material Testing
• Multi-objective Design Optimization
• +7 more

Dr. Zhenzhou Wang is a Research Fellow at the University of Southampton, affiliated with the CERN-STFC HL-LHC Project. His research focuses on lightweight materials for liquid hydrogen storage systems in aircraft and ships, composite material modeling, and AI-driven multi-objective optimization. He is a member of the Energy Technology Group and has held roles such as Guest Editor for Polymers (2021-2023). Notable achievements include receiving the Dean's Award (2024) twice. His work integrates analytical and numerical methods to address challenges in aerospace materials, cryogenic testing, and structural optimization. Recent studies include evaluating thermoplastic polymers for cryogenic sealing, thermal fatigue effects on composites, and deployable composite boom design frameworks. Collaborations involve researchers from institutions like CERN and industry partners. Affiliations: University of Southampton (CERN-STFC HL-LHC Project), Energy Technology Group Key Projects: Liquid hydrogen fuel storage systems, spacecraft lightweight materials, AI optimization algorithms Awards: Dean's Award (2024)

Niklas WahlbergView profile

Professor

• Lepidoptera Evolution
• Molecular Systematics
• Biogeography
• +5 more

Niklas Wahlberg is a Professor in Biological Systematics at Lund University, Sweden. He holds roles including Museum Director of the Biological Museum and Principal Investigator in the BECC biodiversity initiative. His primary affiliation is with the Department of Biology, focusing on evolutionary biology and systematics of Lepidoptera. Education & Career: PhD in Evolutionary Biology from University of Helsinki (2000) Postdoc at Stockholm University (2000–2002) Academy Research Fellowship at University of Turku (2006–2011) Professor in Genetics at Turku (2014) before moving to Lund in 2015 Research Interests: His work centers on the evolutionary history of Lepidoptera, particularly diversification patterns linked to angiosperm evolution and mass extinction events. He employs molecular systematic methods, next-gen sequencing, and museum specimens to study clade origins and biogeography. Key topics include Cretaceous diversification, post-mass extinction radiation, and genomic discordance in butterflies. Awards & Recognition: Web of Science Highly Cited Researcher (2017, 2018) Elected to Kungliga Fysiografiska Sällskapet (2016) Grants & Projects: Swedish Research Council: Testing gene-trait associations in genome modifications (2025–2029) Infrastructure leader for museum collections and holistic specimen projects Labs & Collaborations: Head of the Systematic Biology Group at Lund, managing the Biological Museum’s collections. Active in global entomology networks and co-organizes major conferences like the International Congress of Entomology.

• Medical Microbiology
• Malaria Molecular Surveillance
• Population Genetics
• +3 more

Dr. Robert Verity is an Assistant Professor in the School of Public Health at Imperial College London, affiliated with the Faculty of Medicine. His research focuses on malaria parasite genetics, particularly using molecular surveillance to understand transmission dynamics. He leads projects like the SIMPLEGEN pipeline funded by the Bill and Melinda Gates Foundation, aiming to optimize resource use in malaria research. His work integrates spatial data analysis, Bayesian methods, and population genetics to address global health challenges. During the pandemic, he contributed to early estimates of COVID-19 fatality rates as part of the Imperial College response team. Key affiliations: Imperial College Network of Excellence in Malaria, MRC Centre for Global Infectious Disease Analysis Current projects: Molecular inversion probes analysis in DRC, malaria drug resistance quantification Research interests include Plasmodium falciparum population structure, antimalarial resistance mechanisms, and spatial epidemiology. His work bridges field data collection with advanced computational methods to inform public health strategies.

• Genetic Algorithms
• Evolutionary Computation
• Complex Adaptive Systems
• +2 more

Annie S. Wu is an Associate Professor in the Department of Computer Science at the University of Central Florida (UCF). She directs the Evolutionary Computation Laboratory and holds joint appointments with the Department of Electrical and Computer Engineering and the Institute for Simulation and Training at UCF. Wu earned her Ph.D. in Computer Science and Engineering from the University of Michigan in 1995. Ph.D. in Computer Science and Engineering – University of Michigan Her research spans genetic algorithms , evolutionary computation , complex adaptive systems , multi-agent systems , and machine learning . She has served on editorial boards for Evolutionary Computation and Memetic Computing , and held leadership roles with ACM SIGEVO and the International Society for Genetic and Evolutionary Computation. Notable accolades include: UCF Teaching Incentive Program Award (2019) Excellence in Graduate Teaching Award, UCF College of Engineering and Computer Science (2017) National Research Council Research Associateship Award (1996–1999) Wu’s work bridges theoretical and applied computational methods, with a focus on adaptive systems and collaborative research across engineering disciplines.

• Animal Ecology
• Urban Ecology
• Biodiversity Research
• +5 more

Privatdozent Dr. Marcela Suarez-Rubio is a Senior Scientist at the Institute of Zoology, University of Natural Resources and Life Sciences Vienna (BOKU) , specializing in urban ecology, biodiversity research, and wildlife monitoring . Her work integrates landscape ecology, remote sensing, and conservation biology to study how land-use changes affect birds and bats in temperate and tropical regions. She has led projects in Austria, Myanmar, and Bhutan, focusing on habitat connectivity, urban green spaces, and endangered species conservation . Education: PhD in Ecology, University of Maryland, USA (2011) MSc in Biology, University of Puerto Rico (2005) BSc in Biology, Universidad del Valle, Colombia (2000) Research Themes: Urbanization gradients and their nonlinear effects on avian and bat communities Biodiversity assessment in remote areas like Hkakabo Razi National Park Telemetric and acoustic methods for wildlife monitoring Conservation strategies for critically endangered species (e.g., White-bellied Heron) Ecosystem management in agricultural and forested landscapes Scientific Awards: ERASMUS+ Teaching Mobility (2022, 2018, 2017) National Parks Austria Research Award (2022) BOKU Teaching Award (2016) NASA-MSU Professional Enhancement Award (2011) Golden Key International Honour Society (2008) Advising and Grants: Supervised 14 theses and secured funding from National Parks Austria, Austrian Academy of Sciences, and international organizations . Active in scientific peer-review (Philosophical Transactions of the Royal Society B, Journal of Urban Ecology) and conservation policy for UNESCO World Heritage nominations.