Find Academic Supervisors

Fatemeh DavoudiView profile

Assistant Professor

• Machine Learning
• Safety Analytics
• Predictive Modeling
• +7 more

Fatemeh Davoudi is an Assistant Professor in the Department of Aviation and Technology at San José State University (SJSU), specializing in Manufacturing Systems. She directs the Machine Learning & Safety Analytics Lab and serves as the Graduate Advisor for the Master of Science in Engineering Technology (MSET) program. Her research focuses on applied machine learning in industrial systems, safety analytics, predictive modeling, quality management, and lean manufacturing. She holds a Ph.D. in Industrial Technology from Iowa State University with a minor in Statistics. Dr. Davoudi’s work includes projects funded by grants totaling over $500,000, such as Deep Learning for Process Monitoring in Semiconductor Manufacturing (Co-PI, $163,000) and Machine Learning in Autonomous Systems (Co-PI, $100,000). Her research spans safety analytics in occupational settings, geometric machine learning for reliability assessment, and theory-guided data science for industrial optimization. Education: Ph.D. Industrial Technology, Iowa State University (2018) Awards: AHFE 2020 Best Paper Award (Safety Management and Human Factors Track) Service: Guest Editor for International Journal of Environmental Research and Public Health , Board Member of ATMAE Her teaching includes courses on Six Sigma, Design of Experiments, and Lean Manufacturing. She advises students pursuing thesis and project work in machine learning applications for industrial systems optimization.

Hossam GaberView profile

Professor

• Resilient Smart Energy Grids
• Advanced Plasma Generation for Fusion Energy
• Nuclear Power Plant Safety Systems
• +3 more

Dr. Hossam Gaber is a Professor in the Department of Energy and Nuclear Engineering at Ontario Tech University, within the Faculty of Engineering and Applied Science. He holds a PhD in Safety Engineering from Okayama University, Japan, and is a Professional Engineer (PEng) and Fellow of the Institution of Engineering and Technology (IET). His research focuses on resilient energy systems, nuclear safety, and advanced plasma applications. Education: PhD (Safety Engineering), Okayama University, Japan MSc (Computer & Automatic Control), Alexandria University, Egypt BSc (Computer & Automatic Control, First-class Honours), Alexandria University, Egypt Dr. Gaber’s research interests span resilient smart energy grids, fusion energy plasma generation, nuclear power plant safety systems, fault diagnosis, risk-based energy conservation, and process systems engineering. He has authored over 30 peer-reviewed publications and holds several awards, including the Ontario Tech Achievement Award (2017-2018) and the IEEE Best Paper Award (2007). He teaches advanced courses such as Advanced Energy Process Control , Hybrid Energy System Design , and Reactor Control . His work emphasizes interdisciplinary solutions for energy sustainability and industrial safety.

Lixuan LuView profile

Professor

• Nuclear Power Plant Instrumentation
• Control Systems
• Reliability Engineering
• +4 more

Dr. Lixuan Lu is a Professor in the Department of Energy and Nuclear Engineering at Ontario Tech University, affiliated with the Energy Systems and Nuclear Science Research Centre (ERC). Their research focuses on nuclear power plant instrumentation, control systems reliability, and risk-informed maintenance strategies. Dr. Lu holds a PhD in Electrical and Computer Engineering from the University of Western Ontario (2005), and prior degrees from Beijing Institute of Technology (MES 2001, BES 1998). Education: PhD (2005), MES (2001), BES (1998) in Automatic Control/Electrical Engineering Research Interests Dr. Lu investigates advanced control methodologies for nuclear facilities, including networked control systems reliability, safety-critical instrumentation, and risk assessment for non-coherent systems. Key applications include CANDU reactor control, hydrogen production via thermochemical cycles, and FPGA-based instrumentation. Their work bridges theoretical reliability analysis with practical implementation in nuclear energy systems. Publications Recent work emphasizes risk-informed maintenance strategies, FPGA systems for nuclear instrumentation, and hydrogen production plant modeling. Key contributions address safety-critical control systems, probabilistic safety assessment using Petri nets, and reliability evaluation of standby systems. Dr. Lu collaborates on projects integrating supercritical water-cooled reactors (SCWR) with copper-chlorine thermochemical cycles for hydrogen co-generation. Awards & Grants No specific awards or grants listed in the provided materials. Dr. Lu’s research is supported through institutional and collaborative initiatives. Labs & Teams Affiliated with the Energy Systems and Nuclear Science Research Centre (ERC), focusing on interdisciplinary energy solutions.

• Biodiversity Theory
• Ecology
• Evolutionary Biology
• +4 more

James Rosindell is a Professor of Biodiversity Theory at Imperial College London's Department of Life Sciences (Silwood Park), part of the Faculty of Natural Sciences. He leads the Computational Methods in Ecology and Evolution (CMEE) program and co-founded the OneZoom charity to visualize the tree of life. His research focuses on biodiversity theory, conservation prioritization, and computational ecology. Research interests include: Neutral theory applications in biodiversity Phylogenetic diversity metrics Conservation biology and prioritization Ecological modeling His publications highlight innovations like the OneZoom tree visualization tool and frameworks for quantifying extinction risks. Key contributions address reptilian phylogenetic diversity conservation and microbial community dynamics under pollution.

Daniel KatzView profile

Assistant Professor

• Plant Ecology
• Ecosystem Services and Disservices
• Aerobiology
• +4 more

Daniel Katz is an Assistant Professor in the School of Integrative Plant Science at Cornell University, specializing in plant ecology and aerobiology. His work focuses on linking ecological processes to public health outcomes, particularly through modeling airborne pollen concentrations and urban tree impacts. He holds a Ph.D. from the University of Michigan (2015) and a B.A. from Bard College (2007). His research integrates field studies, remote sensing, and Bayesian statistics to address ecosystem services and disservices. Key projects include assessing allergenic pollen in Detroit, modeling Ashe juniper pollen in Texas, and developing national-scale airborne pollen frameworks. Recent work explores urban greening’s role in heat mitigation and health equity. Publications span interdisciplinary topics like pollen-asthma correlations, urban tree classification, and climate change effects on plant phenology. Media highlights include 2024 findings on pollen-driven asthma spikes and 2023 profiles of his faculty role at Cornell. Based in Bradfield Hall, his lab (Plants, Pollen and People) emphasizes collaboration with communities and stakeholders to translate ecological insights into actionable health strategies.

Brian Stone, Jr.View profile

Professor

• Urban Climate
• Environmental Planning
• Public Health
• +3 more

Brian Stone, Jr. is a Professor in the School of City & Regional Planning at Georgia Institute of Technology's College of Design. He directs the Urban Climate Lab, focusing on urban environmental planning, climate change adaptation, and heat island mitigation. His work integrates environmental science, urban design, and public health to develop strategies for climate-resilient cities. Stone's research is supported by the NSF, CDC, and EPA, with recent studies emphasizing extreme heat risk assessments, urban infrastructure resilience during compound climate events, and the health impacts of heat exposure. Education: Ph.D. and degrees in environmental management/planning from Duke University and Georgia Tech. Specialization includes urban form-climate interactions and climate justice. His book Radical Adaptation (2024) proposes transformative urban strategies for climate changed worlds, building on his earlier work honored with the 2012 Choice Award. Media coverage includes features in New York Times , Washington Post , and NPR. Key contributions include defining 'urban heat management,' modeling heat-wave/blackout compounding risks, and evaluating tree planting/cool roofing strategies. Current projects address climate viability thresholds in cities, spatial equity in heat exposure, and municipal adaptation frameworks. Grants support work on heat tolerance indices, indoor thermal resilience, and regional climate modeling. Awards include the 2012 Choice Award for The City and the Coming Climate . His lab's collaborations span academic, governmental, and NGO sectors. Stone advises on local and national climate policy, emphasizing actionable science for urban planners.

• Applied Mathematics
• Mathematical Modeling in Life Sciences
• Urban Resilience
• +3 more

Elena De Angelis is a Tenured Associate Professor at the Polytechnic University of Turin, holding a position in the Interuniversity Department of Territorial Sciences, Project and Policies (DIST). She serves as Deputy Coordinator of the Planning and Design College and is a member of the Interdepartmental Centre R3C (Responsible Risk Resilience Centre). Additionally, she acts as Scientific Advisor to the European Association EPIC (European Photonics Industry Consortium). Her research focuses on applied mathematics, mathematical modeling in life sciences, and urban resilience. Key projects include the TReE initiative (2023-2025) for ecological economy transitions in Italian cities and prior EU-funded research such as SAFECITI (2014-2016) and EVACUATE (2013-2017). She teaches courses in mathematical analysis and territorial planning, contributing to doctoral programs in Civil and Environmental Engineering. Her publications emphasize system dynamics models, resilience assessment frameworks, and agent-based modeling for urban regeneration and environmental systems. Notable works include applications to winemaking regions (Douro Valley) and green gentrification dynamics. She advises PhD students on urban development models and collaborates with institutions like the R3C Centre and EPIC.

Anthony OnojaView profile

Research Fellow

• Artificial Intelligence
• Data Science
• Statistics
• +5 more

Dr. Anthony Onoja is a Research Fellow at the University of Surrey's School of Health Sciences, affiliated with the Centre of Excellence on Ageing (CEA). He holds a PhD in Data Science from Scuola Normale Superiore (Italy), an MSc in Mathematical Statistics from Pan African University/Kenyatta University (Kenya), and a First Class BSc in Statistics from the University of Jos (Nigeria). His work focuses on applying AI, data science, and statistical methods to health challenges, particularly in biomarker identification, patient stratification, and interpretable machine learning for chronic diseases. He currently contributes to the CEA's transdisciplinary research on healthy ageing, collaborating with national and global networks. Research interests include: Interpretable/explainable AI for medical decision-making Multimorbidity analysis using multi-omics data Biomarker validation reproducibility Genetic interactions in disease severity (e.g., COVID-19) Notable contributions include developing explainable models for myocardial infarction patient profiling, lipidomics biomarker reproducibility frameworks, and genetic severity prediction systems for infectious diseases. His work emphasizes translational research with clinical and public health relevance. Current research projects include bioinformatics analysis of the NURTuRE-CKD cohort and applications of domain knowledge integration in biomedical AI systems.

• Social Forestry
• Forest Management
• Conservation Biology
• +3 more

Georgia Peterson is an Adjunct Assistant Professor in the Department of Forestry at Michigan State University , affiliated with the College of Agriculture & Natural Resources and MSU Extension . Her work focuses on social forestry, community engagement, and applied forest management. She provides expertise in invasive species control, forest health, and citizen science initiatives. Education background not explicitly stated in provided texts. Active in developing educational resources like the Identifying Trees of Michigan guide and facilitating workshops on leadership and forest stewardship. Collaborates with conservation districts and leads innovative projects adapting citizen science to pandemic challenges. Key areas of engagement include: Invasive species management strategies Urban and community forestry practices Public education through workshops and digital tools Forest health diagnostics and long-term planning Her recent work emphasizes practical solutions for landowners and educators, combining scientific rigor with actionable advice for sustainable forest management.

Thijs van OmmenView profile

Assistant Professor

• Causal Inference
• Machine Learning
• Statistical Learning
• +1 more

Thijs van Ommen is an Assistant Professor in the Department of Information and Computing Sciences at Utrecht University. His research centers on causal inference, machine learning, and statistical methodologies for data science applications. He teaches courses in Advanced Machine Learning and core Machine Learning principles, emphasizing algorithmic foundations and real-world implementations. Research explores causal entropy, graphical models, and robust decision-making under uncertainty. Recent publications address causal bandits, information bottlenecks, and efficient algorithms for structural equation models. Van Ommen actively presents at conferences like SIAM Applied Algebraic Geometry and co-chairs sessions at INFORMS. His work bridges theoretical machine learning with practical challenges in causal discovery and adaptive systems.

AJ (Ad) FeeldersView profile

Associate Professor

• Data Mining
• Machine Learning
• Applied Data Science
• +5 more

Dr. AJ (Ad) Feelders is an Associate Professor at Utrecht University, affiliated with the Department of Information and Computing Sciences within the Faculty of Science. His primary research focuses on Data Mining, Machine Learning, and Applied Data Science, with a particular emphasis on algorithmic data analysis and fraud detection. He has organized major conferences like the Symposium on Intelligent Data Analysis (IDA 2020) and contributed to editorial roles for journals such as Intelligent Systems in Accounting, Finance & Management . Roles: Associate Professor, Department of Information and Computing Sciences Affiliations: Utrecht University, Faculty of Science His research spans diverse applications, including renewable energy analysis, Bayesian networks, and time series forecasting. Notable projects include developing methods for detecting critical events in energy production and creating graph embeddings for historical data analysis. He has also worked on fraud detection in international shipping and real-time outlier detection in water sensor data. Feelders has authored or co-authored over 80 publications, including influential works on exceptional model mining, isotonic regression, and monotonic classification. His contributions bridge theoretical advancements with practical applications in domains like environmental science, healthcare, and digital humanities.

Max Mahdi RoozbahaniView profile

Lecturer

• Machine Learning
• Data Analysis
• Network Analysis
• +3 more

Mahdi Roozbahani is a Lecturer at Georgia Tech's School of Computational Science and Engineering and School of Computing Instruction. He earned his Ph.D. in Computational Science and Engineering from Georgia Tech (2019), along with three master's degrees in Civil and Environmental Engineering (Georgia Tech), Geotechnical Engineering (University Putra Malaysia), and a bachelor's from Iran University of Science and Technology. His research focuses on modeling/simulation, network analysis, and machine learning. Roozbahani founded Filio, a cloud-based photo management platform through Create-X incubator. He has published over 20 peer-reviewed papers and teaches courses like Machine Learning and Data Analytics. Awards: Jean-Lou Chameau Research Excellence Award (twice) NSF IRES Fellowship (Ecole des Ponts, Paris) Top Five Featured Paper (Materials Journal, 2017) 2021 Class of 1934 CIOS Honor Roll for Teaching Excellence He advises multiple students in OMSCS/OMSA programs and leads research in computational methods for disaster assessment, educational technology, and granular material analysis. His work bridges academia and industry via Filio's tech innovations.

Gabriela Nunez-MirView profile

Assistant Professor

• Biological Invasions
• Macroecology
• Computational Ecology
• +1 more

Gabriela Nunez-Mir is an Assistant Professor in Biological Sciences at the University of Illinois Chicago's College of Liberal Arts and Sciences. Her research leverages large-scale datasets to investigate patterns of biological invasions and ecosystem change. A 2024 Walder Foundation Biota Award recipient, she develops computational methods for ecological literature synthesis and invasion forecasting. Research Focus: Macroscale analysis of biological invasions using machine learning, spatial modeling, and meta-research approaches to address knowledge gaps in invasion ecology and conservation. Education: PhD Forestry and Natural Resources, Purdue University (2018) BS Biology/Biotechnology & BA Environmental Studies, Worcester Polytechnic Institute (2013) Methodologies: Combines machine learning, Bayesian statistics, and geospatial analysis to study invasive species dynamics and ecosystem impacts across spatial scales.

• Climate Change and Human Health
• Environmental Health
• Public Health
• +3 more

Dr. Christie Godsmark is a Lecturer in the School of Public Health at University College Cork (UCC) and Academic Director of the MSc in Occupational Health (online) program. She is affiliated with UCC's Environmental Research Institute. Her research focuses on climate change impacts on human health, particularly in vulnerable populations such as informal settlement residents in Dar es Salaam and temperate climate regions like Ireland. She coordinates the CATCH project (Communication and Action through Tree-planting for Climate-Health), funded by the Irish Research Council. Her teaching includes developing a 5-credit Environmental Health module for the MSc program. Education: Doctorate in Human Thermoregulation (University of Portsmouth, 2016) MSc in Medicine (Cardiovascular Physiology) – University of Cape Town (2012) BSc Honours in Human Kinetics/Ergonomics – Rhodes University (2009) Bachelor of Arts in Psychology – Rhodes University (2008) Research Interests: Climate change and health co-benefits, heat-health vulnerability, environmental health advocacy, and Sustainable Development Goals integration. Her work emphasizes actionable solutions that align climate action with health equity and environmental sustainability. Grants & Projects: CATCH project: €4,808 from Irish Research Council (2020–2021) Development of climate adaptation frameworks for South African provinces and Irish temperate regions Awards: Honorary Lecturer at University of Cape Town (2018–2021). Advising & Grants: Leads UCC's MSc Occupational Health program and contributes to policy briefs for governments in Tanzania and South Africa. Active in the Irish Climate and Health Alliance, UCC's Athena SWAN committee, and Green Campus Forum. Labs/Teams: Collaborates with the Environmental Research Institute and international teams on climate health projects.

• Automotive Cybersecurity
• Formal Verification
• Autonomous Systems
• +2 more

Hoang Nguyen is an Associate Professor in Cyber Security at Swansea University with research focus on automotive and autonomous systems security. Research Focus: Specializes in model-based verification methods and simulation techniques for security validation of cyber-physical systems. Current projects include VRBMAS, ACID, Ditto, QRNG for CAV, Secure CAV, and AutoCHERI funded by EPSRC, RSSB, InnovateUK, and Digital Catapult. Publication Trends: Recent work centers on automotive cybersecurity frameworks, threat modeling for connected vehicles, and formal verification techniques. Contributions include simulation-based risk assessment, attack-defense tree generation, and secure communication protocols for vehicular platoons.