Find Academic Supervisors

Anthony WachsView profile

Researcher

• Computational Fluid Dynamics
• Particulate Flow
• Numerical Simulation
• +5 more

Anthony Wachs is an Associate Member of the Department of Mathematics at the University of British Columbia (UBC), affiliated with the Faculty of Science. His research focuses on computational fluid dynamics (CFD), particulate flows, and multiphase systems, with emphasis on numerical methods like DEM-CFD coupling and high-fidelity simulations of complex fluid-particle interactions. He develops scalable solvers for non-spherical rigid bodies and fluid-structure interactions, contributing to fields such as granular media, viscoplastic fluids, and biological capsule dynamics. His work bridges computational approaches with real-world applications in energy, biomedical engineering, and environmental systems. Research interests include particle-resolved direct numerical simulations (DNS), fluidized beds, and the development of tools like Grains3D and PeliGRIFF for particle dynamics. His studies address challenges in flow past irregular geometries, hydrodynamic force modeling, and machine learning-enhanced fluid dynamics. Wachs collaborates across disciplines, integrating advanced numerical techniques with experimental validation to advance understanding of multiphase flow phenomena.

Dominique MartinView profile

Professor

• Health Ethics
• Organ Transplantation Ethics
• Organ Trafficking
• +4 more

Professor Dominique Martin holds the position of Professor in Health Ethics and Professionalism at Deakin University's School of Medicine, Faculty of Health. Her academic journey includes a PhD in Applied Ethics (2011) from the University of Melbourne and a Graduate Certificate in University Teaching (2014). She has held roles including Senior Lecturer at Deakin (2016–present) and Lecturer at the University of Melbourne (2012–2016). Research Focus: Ethical issues in kidney care, organ trafficking, transplant tourism, and end-of-life research. Professional Memberships: Declaration of Istanbul Custodian Group, The Transplantation Society, and International Association of Bioethics. Her work emphasizes global health ethics, particularly combatting organ trafficking and improving equitable access to transplantation. She advises on organ donation policies and has contributed to international guidelines like the Declaration of Istanbul. Notable grants include a 2021 study on placental technologies and a 2017 project on donor-family communication. She has published extensively on transplantation ethics, with recent work focusing on global policy frameworks and clinical innovations.

Kathryn CowtanView profile

Professor

• Structural Biology
• Climate Science
• Scientific Computing
• +3 more

Professor Kathryn Cowtan is a Professor in the Department of Chemistry at the University of York, with dual expertise in Structural Biology and Climate Science. Her work spans software development for structural biology (e.g., cryo-EM and X-ray crystallography) and climate data analysis, focusing on improving public understanding of climate science. Research Interests: Structural Biology: Development of software tools (e.g., Buccaneer, Coot) for automated protein structure determination and cryo-EM image processing. Climate Science: Analysis of historical temperature records to address biases, particularly in sea surface temperature measurements, and extending climate data back to the 18th century via the GloSAT project. Key Contributions: Authored high-profile crystallographic software (dm, clipper, parrot) distributed via CCP4/CCP-EM. Co-developed methodologies to reconcile observed and modeled global temperature trends, addressing the early-21st-century warming slowdown. Awards: Recipient of the Friend of the Planet award (2016) for contributions to climate science communication. Teaching & Outreach: Leads programming courses for chemists and advocates for open research practices. Engages in public science communication through media collaborations and international training workshops. Funding & Projects: Principal investigator on grants from STFC and BBSRC, including projects on molecular graphics software development and cryo-EM refinement techniques.

Roseanne M. FordView profile

Professor

• Environmental Engineering
• Bioremediation
• Computational Systems Biology
• +3 more

Roseanne M. Ford is a Professor of Chemical Engineering at the University of Virginia, where she also served as Department Chair and Associate Vice President for Research and Graduate Studies. Her research focuses on microbial transport in porous media, particularly chemotactic bacteria's role in bioremediation. She holds degrees from the University of Delaware (B.S., 1984) and University of Pennsylvania (M.S. 1985, Ph.D. 1989). Education: B.S. Chemical Engineering, University of Delaware, 1984 M.S. Chemical Engineering, University of Pennsylvania, 1985 Ph.D. Chemical Engineering, University of Pennsylvania, 1989 Research Interests: Computational systems biology, environmental engineering, water resources, and microbial transport dynamics. Her work combines experimental, computational, and multi-scale modeling approaches to enhance bioremediation efficiency and understand bacterial behavior in complex environments. Awards: AIChE Fellow (2024) Cavaliers' Distinguished Teaching Professorship (highest UVa teaching award) AIChE WIC Excellence in Mentoring Award (2016) William R. Kenan Jr. Visiting Professorship (2017-2018) Grants & Projects: Leads Gulf of Mexico Research Initiative studies on microbial motility in oil degradation. Recent work integrates sonification and machine learning to analyze bacterial swimming dynamics and chemotaxis patterns. Current projects explore biofilm inhibition via nanocarriers and marine bacteria's response to hydrocarbons. Labs/Teams: Directs the Ford Group, collaborating with institutions like NIST and SLAC National Accelerator Laboratory. Active in interdisciplinary initiatives blending engineering, microbiology, and data science.

Theoni PhotopoulouView profile

Research Fellow

• Statistical Ecology
• Animal Movement Ecology
• Marine Biology
• +3 more

Dr. Theoni Photopoulou is a Research Fellow in the School of Mathematics and Statistics at the University of St Andrews, with a dual affiliation to the Centre for Research into Ecological & Environmental Modelling. Her work bridges statistical methodology and ecological research, focusing on animal movement patterns and conservation applications. She holds a former position as Research Associate at Nelson Mandela University (2018-2021). Her research employs advanced statistical techniques to study marine and terrestrial wildlife, particularly large animals like whales, dolphins, and sharks. Core themes include movement ecology, population dynamics, and the impacts of environmental stressors. She collaborates internationally on projects involving North Atlantic right whales, bottlenose dolphins, and white sharks, contributing to both ecological theory and conservation policy. Dr. Photopoulou has pioneered methods for analyzing tracking data, including hidden Markov models and epigenetic aging techniques. Her work frequently addresses conservation challenges such as habitat management, bycatch mitigation, and climate change adaptation. Notable contributions include studies on body size declines in endangered whales and spatial distribution patterns of apex predators. Publications span high-impact journals like Proceedings of the Royal Society B and Biological Conservation , with a focus on interdisciplinary solutions to ecological problems. She has developed open datasets for tracking studies and actively engages in policy-oriented research through collaborations with conservation agencies.

Rajat MittalView profile

Professor

• Computational Fluid Dynamics
• Biomedical Engineering
• Fluid-Structure Interaction
• +7 more

Rajat Mittal is a Professor of Mechanical Engineering at Johns Hopkins University (JHU), affiliated with the Whiting School of Engineering. He holds a secondary appointment in the JHU School of Medicine. His research focuses on computational fluid dynamics (CFD), biomedical flows, and bioinspired engineering, with applications to heart valve dynamics, digestive physiology, and drone rotor design. Education: B.S. in Aeronautical Engineering from IIT Kanpur (1989), M.S. in Aerospace Engineering from the University of Florida (1991), Ph.D. in Applied Mechanics from UIUC (1995). Postdoctoral research at Stanford University’s Center for Turbulence Research (1995-1996). Research emphasizes immersed boundary methods, fluid-structure interaction, and multiphase flow modeling. Key areas include gastric digestion mechanics, bioacoustics, and biomimetic propulsion systems. His lab (Flow Physics and Computation Lab) collaborates with zoology, cardiology, and robotics experts. Notable awards include the 2025 AIMBE Fellowship, 2022 Stanley Corrsin Award, and 2021 Freeman Scholar Award. He edits four journals and advises on projects funded by NIH, NSF, and DARPA. His work bridges engineering and medicine, with applications to surgical planning and medical device design. Recent projects model stomach biomechanics post-bariatric surgery, optimize drone rotor noise reduction, and study fish schooling hydrodynamics. He also explores transonic flutter in wings and porous media flow control.

• Robotics
• Algorithmic Automation
• Simulation
• +3 more

Prof. AF (Frank) van der Stappen is a Professor of Robotics and Automation at Utrecht University's Faculty of Science, Department of Information and Computing Sciences. He also holds a position at University College Roosevelt. His research focuses on robotics (grasping, manipulation, motion), algorithmic automation, simulation, computational geometry, and computer animation. He has been an IEEE Fellow since 2017. His work emphasizes geometric computing and its applications in automation, with contributions to form-closure grasping, path planning, and virtual character animation. Education: PhD in Motion Planning from Utrecht University (1994), MSc in Distributed Data Structures from Eindhoven University of Technology (1988). Research Interests: Robotics (manipulation/grasping), algorithmic automation, geometric algorithms, computer animation, and crowd simulation. His work bridges theoretical foundations with practical applications in manufacturing, virtual environments, and agricultural robotics. Awards: IEEE Fellow (2017). Advisees/Grants: No explicitly listed students, but extensive collaborative work with researchers like Elon Rimon, Ken Goldberg, and Mark Overmars. His research includes grants related to motion planning, caging, and automation. Labs/Teams: Involved in geometric computing and robotics teams at Utrecht University, contributing to Game Research themes and interdisciplinary projects.

David B. BlumenthalView profile

Professor

• Biomedical Engineering
• Network Science
• Artificial Intelligence in Medicine
• +6 more

David B. Blumenthal is an Assistant Professor and head of the Biomedical Network Science Lab at Friedrich-Alexander University Erlangen-Nürnberg (FAU). His work focuses on applying network science and AI to study molecular disease mechanisms and developing privacy-aware biomedical AI solutions. He holds a PhD in Computer Science from the Free University of Bozen-Bolzano and has held postdoctoral positions at TU Munich and the Free University of Bozen-Bolzano. His research spans federated learning, graph algorithms, and systems medicine, with a strong emphasis on translational applications in healthcare. Education: BSc/MSc Mathematics, Free University of Berlin & Technical University of Berlin BA/MA Philosophy, Free University of Berlin PhD in Computer Science, Free University of Bozen-Bolzano Visiting PhD student at GREYC Research Lab, France Research Interests: Blumenthal’s work integrates computational methods with biomedical data to uncover disease mechanisms. Key areas include federated learning for medical data privacy, network-based disease module discovery, and AI-driven drug repurposing. He develops tools like ROBUST-Web, NeDRex, and DataSAIL to address challenges in data leakage and heterogeneous data integration. Awards: Best Poster Award (2022), Best Paper Awards (2021, 2017), Best PhD Student Award (2021) Recipient of German Academic Scholarship Foundation support Grants: Leads projects funded by BMBF, DFG, and industry partners, including FLabNet (federated learning in paediatric oncology) and NetMap (dimensionality reduction in single-cell data). His work often bridges FAU’s engineering and medical faculties. Labs/Teams: Heads the Biomedical Network Science Lab, collaborating with institutions like TU Munich, Bitspark GmbH, and Erlangen University Hospital on translational AI projects.

• Signal Analysis
• Biomedical Engineering
• Power Systems
• +7 more

Marta Molinas is a Professor in the Department of Engineering Cybernetics at NTNU, affiliated with the Faculty of Information Technology and Electrical Engineering. She holds dual professorships in Industrial Electrotechnics and Power Electronics for Power Systems. She is also an affiliated scientist at the AMOS Center of Excellence. Her research focuses on non-linear/non-stationary signal analysis in both biological systems (EEG) and electrical grids, emphasizing synchronization mechanisms. Key projects include the 'David & Goliath' initiative and 'The Girl Effect' (2019-2020). Education: Dr. Eng. from Tokyo Institute of Technology (2000), Master of Engineering from University of the Ryukyus (1997). Teaching includes courses like TTK4240 Industrial Electrotechnics and TTK7 Adaptive Data Analysis. She supervises numerous PhD students and postdocs in areas like EEG signal analysis and grid stability. Research interests span EEG-based brain-computer interfaces, grid stability, and biomarker identification. Notable experiments include translating EEG signals into drone control and developing low-density EEG systems. Awards: Not explicitly listed, but recognized through prolific publications and grants.

Sarah FortuneView profile

Assistant Professor

• Marine Mammal Conservation
• Biological Oceanography
• Zooplankton Ecology
• +5 more

Sarah Fortune is an Assistant Professor in the Department of Oceanography at Dalhousie University, holding the Canadian Wildlife Federation Chair in Large Whale Conservation. She leads the Fortune Whale Lab, focusing on interdisciplinary research at the intersection of biological and physical oceanography, ecology, and physiology to address conservation challenges for large whales. Her work emphasizes understanding how environmental variability impacts whale behavior, prey availability, and ecosystem health, particularly in Arctic and temperate regions. Education: BAH from Queen’s University, MSc and PhD from the University of British Columbia, with additional research at the Woods Hole Oceanographic Institution. Her research explores whale movement ecology, foraging strategies, and responses to climate change, often collaborating with Indigenous communities, government agencies, and industry partners. She has conducted fieldwork in the Canadian Arctic, Cumberland Sound, and the Gulf of St. Lawrence. Research Interests: Marine mammal conservation, zooplankton ecology, Arctic ecosystem changes, whale behavior and energetics, and the impacts of human activities on marine life. Her lab employs advanced technologies like multi-scale tags and satellite telemetry to study whale behavior and habitat use. Awards: Recipient of multiple prestigious fellowships including the W. Garfield Weston Postdoctoral Fellowship and the Emily Gallagher Memorial Award. Her work has been recognized for bridging ecological theory with applied conservation outcomes. Advising & Grants: While no specific student names are listed, her lab supports graduate research on whale ecology. Funding sources include the W. Garfield Weston Foundation and NSERC grants. She contributes to conservation initiatives like the COSEWIC Status Report on North Atlantic right whales. Labs/Teams: Director of the Fortune Whale Lab, collaborating with universities, government bodies, and Indigenous groups to advance whale conservation through empirical and model-based research. Current projects include assessing vessel-whale interactions in Arctic shipping lanes and quantifying prey thresholds for bowhead whales.

Ricardo BetancurView profile

Associate Professor

• Ichthyology
• Evolutionary Biology
• Phylogenomics
• +6 more

Ricardo Betancur is an Associate Professor of Marine Biology at the Scripps Institution of Oceanography, UC San Diego. His research focuses on Ichthyology, Evolutionary Biology, and Phylogenomics, with a particular emphasis on understanding the evolutionary processes shaping fish diversity. His work integrates genomic, morphological, and ecological data to explore topics such as adaptive radiation, biogeography, and phylogenetic relationships in marine and freshwater fish species. Education: PhD Biological Sciences, Auburn University (2009) M.Sc. Marine Biology, Universidad Nacional de Colombia (2003) B.Sc. Marine Biology, Universidad Jorge Tadeo Lozano (2000) Research interests include phylogenetic comparative methods, population genetics, and the application of genomics to resolve evolutionary questions in fish lineages. His projects often involve genomic sequencing of diverse fish species, such as sea catfishes and anglerfishes, to uncover patterns of diversification and adaptation. He has contributed significantly to the classification and evolutionary understanding of ariid catfishes and other marine taxa. His research also addresses the impact of environmental factors, such as ancient climate changes, on fish evolution and distribution. He leads the Fish Phylogeny Research Group and maintains an active website ( fishphylogeny.org ) dedicated to advancing fish phylogenetics. Advising and grants: While no student advisees are listed here, Betancur’s lab focuses on training researchers in phylogenomics and evolutionary biology. His grants support large-scale genomic projects and collaborative initiatives in marine biodiversity. Labs/Teams: He directs the Fish Phylogeny Research Group at Scripps, emphasizing interdisciplinary approaches to fish systematics and evolutionary genomics.

Kirsten Mølgaard NielsenView profile

Associate Professor

• Control Systems
• Automation
• Renewable Energy
• +8 more

Kirsten Mølgaard Nielsen is an Associate Professor in the Department of Electronic Systems at Aalborg University, under The Technical Faculty of IT and Design. She is affiliated with the Automation & Control Green Lab, focusing on sustainable automation and control systems for energy and environmental applications. University: Aalborg University School: The Technical Faculty of IT and Design Department: Department of Electronic Systems Research Lab: Automation & Control Green Lab Email: kmn@es.aau.dk Phone: +4599408761 ORCID: https://orcid.org/0000-0002-2552-1764 Her research interests include control systems, automation, renewable energy (particularly wave and wind), digital hydraulics, smart grids, and wastewater treatment. She has contributed extensively to projects involving energy storage, process control, and sustainable engineering solutions. Her recent publications (2018–2022) demonstrate a strong trend in environmental and energy control systems, particularly in wastewater treatment plant optimization, sewer flow management, and refrigeration system control. These works highlight her expertise in applying advanced control strategies to real-world engineering challenges. She has participated in multiple research projects such as 'Digital Hydraulic Power Take Off for Wave Energy', 'IFIV: Intelligent Remote Control of Individual Heat Pumps', and 'Plug and Play Process Control (P³C)', showcasing her collaborative and interdisciplinary approach. Kirsten Mølgaard Nielsen has not received any explicitly mentioned scientific awards in the provided texts. There is no indication of student advising or grants, though her role in major research projects suggests leadership and mentorship within her team. She is actively involved in research and development within the Automation & Control Green Lab, contributing to advancements in sustainable energy and environmental control technologies.

• Computer Vision
• Machine Learning
• Probabilistic Graphical Models
• +7 more

Jacobus J Barnard is a Professor in the Department of Computer Science at the University of Arizona, College of Engineering. He is actively involved in teaching and research, with a focus on computer vision, machine learning, and interdisciplinary applications in emotion dynamics, biology, and planetary science. Department: Computer Science School: College of Engineering University: University of Arizona Academic Rank: Professor His research interests are centered on Computer Vision , Probabilistic Modeling , and Machine Learning , with applications in emotion regulation, biological structure analysis, and remote sensing. He develops statistical models for understanding indoor scenes, tracking biological motion, and analyzing social and emotional dynamics. His work integrates vision and language, with generative models linking image regions to semantic concepts. The recent publications reflect a strong trend in deep learning for image restoration (e.g., fiber bundle imaging), Bayesian modeling in planetary science (crater shape analysis), and interdisciplinary AI (emotion dynamics, gene expression). His work spans computer science, psychology, biology, and engineering, often combining statistical inference with real-world data from microscopy, aerial imaging, and human behavior studies. Scientific Awards: No explicit awards listed in the provided text. Barnard has advised numerous students, including PhD candidates and honors undergraduates, working on topics such as gesture authentication, pollen tube tracking, and emotion modeling. He has not received mention of major grants, but his sustained publication record and interdisciplinary collaborations suggest active funding. He teaches core courses like Intro to Computer Vision and Probabilistic Graphical Models , and supervises dissertation and independent study research. He is involved in developing computational models for understanding biological structures (e.g., Alternaria fungus, Drosophila neurons), emotion regulation in couples, and automated trail detection in aerial imagery. His lab appears to focus on statistical vision, with strong ties to cognitive science and bioinformatics.

• Machine Learning
• Bioengineering
• Medical Imaging
• +5 more

Wei Qu, M.D., Ph.D., M.S., is a Senior Biologist at the National Toxicology Program (NTP) within the National Institute of Environmental Health Sciences (NIEHS). His work focuses on integrating machine learning, bioengineering, and neuroimaging to advance toxicology and medical research. He leads projects in graph neural networks, functional connectivity modeling, and biomedical image analysis. Qu’s research bridges computational methods with biological systems, addressing challenges in neurodegenerative diseases, biosensing interfaces, and automated medical diagnostics. Key research areas include graph-based representation learning, dynamic functional connectivity analysis, and 3D microscopy image processing. His contributions span neuroimaging data interpretation, biosensor design, and cervical cancer screening algorithms. Qu collaborates across interdisciplinary teams to develop replicable machine learning frameworks for environmental health studies.

Kaie KubjasView profile

Associate Professor

• Algebraic Statistics
• Nonlinear Algebra
• Matrix and Tensor Decompositions
• +5 more

Kaie Kubjas is an Associate Professor at Aalto University in the Department of Mathematics and Systems Analysis, School of Science. Since 2024, she has held a tenured position, following a tenure-track role from 2017–2024. She earned her PhD in Mathematics at Freie Universität Berlin (2013) under Professors Christian Haase and Klaus Altmann, with postdoctoral research at institutions including the Max Planck Institute and MIT. Her research focuses on applied nonlinear algebra, algebraic statistics, and their applications in biology (e.g., phylogenetics and 3D genome reconstruction), as well as matrix/tensor decompositions. She has organized major events like the European Women in Mathematics General Meeting 2022 and the 2025 workshop on Algebraic Statistics and Multistate Models. Kubjas serves on editorial boards of journals like SIAM Journal on Applied Algebra and Geometry and Annales Fennici Mathematici . Recent work includes advances in log-concave maximum likelihood estimation, 3D genome reconstruction, and structured matrix decompositions. Her students, such as Olga Kuznetsova (Second Place MEGA 2021 Poster Award winner), have contributed to these areas. She regularly contributes to seminars like the Algebra and Discrete Mathematics at Aalto, fostering interdisciplinary collaboration.