Find Academic Supervisors

• Autonomous Systems
• Signal Processing
• Vehicle Health Management
• +7 more

Dr Ivan Petrunin is a Research Professor in Signal Processing for Autonomous Systems and a DARTeC Fellow at Cranfield University's School of Aerospace, Transport and Manufacturing. His work focuses on advancing sensor technologies, data fusion, and decision-making systems for Cyber-Physical Systems, with applications in aerospace, ground-based autonomous systems, and urban air mobility. Key areas include Position, Navigation and Timing (PNT), vehicle health management, and AI-driven fault detection. He leads research at facilities like the Muti-User Environment for Autonomous Vehicle Innovation (MUEAVI) and collaborates with industry partners like Airbus, Rolls-Royce, and Thales. Education: BSc and MSc in Design of Electronic Equipment from National Technical University of Ukraine (1996–1998), followed by a PhD in Signal Processing for Condition Monitoring from Cranfield University (2013). Prior to Cranfield, he was a Lecturer in Digital Signal Processing at NTU Ukraine (2001–2005). Research Interests: Autonomous Systems & Sensor Fusion Machine Learning in Navigation and Safety GNSS Integrity & Urban Air Mobility Condition Monitoring & Structural Health Multi-Agent Reinforcement Learning Publications: Over 100 journal/conference articles and book chapters, with recent works emphasizing hybrid sensor fusion, resilient navigation architectures, and AI-driven solutions for GNSS-denied environments. Notable contributions include multi-sensor fusion frameworks for UAVs and Bayesian filter innovations. Awards: FRIN Fellowship, SMAIAA Membership, IEEE and ION Fellowships, and FHEA recognition. His work is supported by ESA, Innovate UK, and EPSRC. Advising & Labs: Supervises PhD students in UAV navigation and machine learning. Leads Cranfield's facilities for autonomous systems experimentation and advanced timing node infrastructure.

• Health Services Research
• Narrative Interventions
• Hypertension Control
• +3 more

Dr. Jeroan Allison is Chair and Professor at UMass Chan Medical School's Department of Population and Quantitative Health Sciences. Trained as a primary care physician and epidemiologist (Harvard SPH), he leads research in narrative interventions for health behavior change, with continuous funding from NIH, AHRQ, and RWJF. His work spans hypertension control in Vietnam, AI-driven health communication, and implementation science for non-communicable diseases. Harvard School of Public Health: Master of Science in Epidemiology University of Alabama at Birmingham: MD Samford University: BS in Chemistry Research interests include narrative medicine , health disparities , mHealth , and health services research . He has published extensively on hypertension interventions in Vietnam, digital health tools, and tobacco cessation strategies using peer engagement. Recent publications focus on AI applications , global implementation science , and social determinants of health . His team has developed culturally adapted interventions for HPV vaccination and hypertension management using community storytelling methods. Scientific contributions include: Co-Editor-in-Chief of Medical Care Developing simulation-based training for research assistants Designing peer recruitment models for smoking cessation Dr. Allison holds multiple grants and leads the UMMS-Vietnam research collaboration , focusing on late-stage translation research in low-resource settings.

• Digital Marketing
• Entrepreneurship Education
• Sustainable Urban Development
• +5 more

George N. Papageorgiou is a Professor of Management & Information Systems at the Gregoriou School of Business Administration, European University Cyprus. He serves in leadership roles including Deputy Dean (2012–2017) and PhD Programme Coordinator (2015–2017). He holds a PhD in Systems Modelling and Simulation from City University, London (1997), along with an MBA (1994) and First Class Honours in Engineering (1992). His research focuses on digital marketing competencies, smart urban mobility systems, entrepreneurship education, and system dynamics modeling for healthcare and sustainability. Notable projects include the SPN (Smart Pedestrian Network) system, funded by Horizon 2020, and the DIMAS project addressing digital marketing frameworks. Awarded the IEEE Best Paper Award (2017) and Innovation Distinction (SPARKS 2019), his work spans over 50 publications in journals like IEEE and Emerald. He actively reviews for IEEE, Emerald, and the System Dynamics Society. His consulting roles include EU research proposal evaluation and editorial work for Emerald. Key achievements include developing frameworks for sustainable urban mobility and green entrepreneurship education. He has led EU-funded projects totaling millions in grants, emphasizing interdisciplinary approaches to innovation and education.

Debbie PalmerView profile

Senior Lecturer

• Sport Injury Epidemiology
• Athlete Health
• Concussion Prevention
• +3 more

Dr. Debbie Palmer is a Senior Lecturer in Research Methods and Epidemiology at the Moray House School of Education and Sport, University of Edinburgh. She holds adjunct roles including Adjunct Associate Professor at the University of Calgary and Honorary Assistant Professor at the University of Nottingham. Her research focuses on injury epidemiology, athlete health, and long-term consequences of sports injuries, particularly among Olympians and elite athletes. She co-founded the Versus Arthritis Significant Ankle Ligament Injury (SALI) Cohort and co-directs the Edinburgh-Bath UK Collaborating Centre on Injury and Illness Prevention in Sport, an IOC Research Centre of Excellence. Education: PhD in Injury Epidemiology, University of Bath (2009) MSc Exercise Physiology, Loughborough University (2003) BSc (Hons) Sport Science, University of Greenwich (1998) Research Interests: Dr. Palmer’s work spans injury prevention in elite and recreational cohorts, long-term health outcomes for athletes, and sport-related concussion. Key areas include Olympian health surveillance, rugby injury prevention, and cycling safety. Her projects involve collaborations with organizations like World Rugby, the IOC, and the Scottish FA. Recent Projects: IOC Olympian Health Cohort (2022–present) World Rugby Activate Program Evaluation (2022–present) Edinburgh Sports Medicine Research Network (ESMRN) Tackle Height Law Change Evaluation in Scottish Rugby Awards & Grants: IOC Research Centre of Excellence (2022) $218k UK Sport/English Institute of Sport grant (2011–2014) $120k World Olympians Association grant (ROMHS Study) Advising & Grants: Supervises 6 current PhD students and has graduated 5 students. Active in securing funding for injury prevention initiatives and athlete health programs. Labs & Teams: Leads the Edinburgh Sports Medicine Research Network and co-directs the UKCCIIS, fostering international collaboration in athlete health research.

• Evolutionary Computation
• Genetic Programming
• Robotics
• +5 more

Eric Medvet is a professor specializing in evolutionary computation, genetic programming, and robotics. He is actively involved in research areas such as neuroevolution, soft robotics, and modular robotics. His work bridges theoretical advancements in evolutionary algorithms with practical applications in robotics and AI. Roles: Conference chair for EuroGP (2020-2022), co-chair of multiple workshops and sessions. Key Research: Focus on genetic programming, embodied intelligence, and the design of adaptive robotic systems. Research Interests: His work emphasizes the development of scalable and interpretable AI systems, particularly through evolutionary methods applied to robotics. He explores topics like neuroevolution for soft robots, quality diversity algorithms, and the integration of machine learning with evolutionary computation. Publications: His recent work highlights trends in interpretable AI, modular robotics control, and evolutionary algorithms for complex systems. Notable contributions include studies on MAP-Elites, graph-based genetic programming, and the application of LLMs in automated testing. Grants & Labs: Developed frameworks like JGEA for evolutionary computation experiments. Collaborates on projects integrating evolutionary methods with real-world robotics applications.

Atreyee BanerjeeView profile

Researcher

• Polymer Physics
• Condensed Matter Physics
• Materials Science
• +3 more

Atreyee Banerjee is a Researcher and Early Career Fellow at Albert-Ludwigs-Universität (Oct 2024–Jun 2025) and a Postdoctoral Researcher at the Max Planck Institute for Polymer Research (MPIP), Mainz, Germany, under Prof. Kurt Kremer. She completed her PhD in Chemical Science at CSIR-National Chemical Laboratory (2017) and postdocs at Cambridge University (2017–2019) and MPIP (2019–present). Education PhD (2017): CSIR-NCL, Pune, India (Supervisor: Dr. Sarika Maitra Bhattacharyya) MSc (2011): Visva Bharati, Santiniketan (Physical Chemistry) BSc (2009): Visva Bharati, Santiniketan Research Interests Focused on data-driven analysis of complex systems, including supercooled liquids, polymers, and organic crystals. Specializes in combining theory, simulations, and machine learning to study structural/dynamical properties. Key areas include glass transition, free energy landscapes, and polymer dynamics. Publications Overview Recent work includes machine learning approaches to glass transition in acrylic polymers (J. Chem. Phys., 2023), data-driven analysis of polymer dynamics (ACS Macro. Lett., 2023), and thermodynamic studies of supercooled liquids (Soft Matter, 2022). Research emphasizes methodological innovations like PCA clustering and basin-hopping optimization. Awards Recipient of DST-India Travel Award (2017), Best Research Scholar Award (CSIR-NCL, 2017), Shell-India Computational Talent Prize Bronze (2015), and multiple best poster awards (2014–2015). Grants & Labs Collaborates with Dr. Oleksandra Kukharenko in the Polymer Theory Group at MPIP. Active in computational initiatives like the ENGAGE Summer School (2023). Research involves datasets from GROMACS trajectories and open-source tools (e.g., scikit-learn).

J. Ian MunroView profile

Professor

• Data Structures
• Space Efficient Data Structures
• Algorithm Design and Analysis
• +7 more

J. Ian Munro is a University Professor and Canada Research Chair in Algorithm Design at the Cheriton School of Computer Science, University of Waterloo. He has been a faculty member at Waterloo since completing his PhD at the University of Toronto in 1971 and was appointed University Professor in 2006, one of the highest honors the university bestows on its faculty. Dr. Munro's research focuses on the design, analysis, and implementation of efficient algorithms and data structures, with particular emphasis on space-efficient solutions. His work spans several key areas including succinct data structures, tree algorithms, text search methods, priority queues, and memory management for data structures. His research has had significant impact on how we understand the theoretical limits of data representation while maintaining efficient query performance. The trajectory of his recent publications (2020-2024) reveals a continued focus on pushing the boundaries of space efficiency in data structures, particularly for graphs and trees. His work increasingly addresses dynamic scenarios where data structures must be updated efficiently while maintaining query performance. The research shows strong connections between information theory, combinatorics, and practical algorithm design, with applications spanning database systems, computational geometry, and text processing. Fellow of the Association for Computing Machinery (FACM) Elected Fellow of the Royal Society of Canada (FRSC) in 2003 Canada Research Chair in Algorithm Design Dr. Munro has supervised over 24 PhD students throughout his career and has been actively involved in teaching advanced courses on data structures and algorithms. His research has been consistently funded through competitive grants, including his Canada Research Chair position. He maintains active collaborations with researchers worldwide, as evidenced by his extensive co-authorship network across numerous publications. As a member of both the Algorithms and Complexity Group and the Data Systems Group at Waterloo, Dr. Munro contributes to interdisciplinary research that bridges theoretical computer science with practical systems challenges. His work continues to influence both theoretical understanding and practical implementations of efficient data management solutions.

Kursat KaraView profile

Assistant Professor

• Fluid Dynamics
• Aerodynamics
• Computational Fluid Dynamics (CFD)
• +9 more

Kursat Kara is an Assistant Professor in the Department of Mechanical and Aerospace Engineering at Oklahoma State University (OSU), leading the Kara Aerodynamics Research Laboratory. He holds a Ph.D. in Aerospace Engineering from Old Dominion University (2008), and has held academic positions including Assistant Professor at Khalifa University (2010–2018), where he received the President’s Faculty Excellence Award for Teaching (2015). His research focuses on fluid dynamics, computational aerodynamics, hypersonic flows, quantum computing, and flow separation control using techniques like CFD and miniPIV. He has advised numerous graduate and undergraduate students, and collaborates on projects such as hypersonic boundary-layer stability, quantum computing for fluid dynamics, and urban wind field modeling for UAS navigation. Dr. Kara’s expertise spans experimental and numerical fluid dynamics, including work on sweeping jet actuators, boundary-layer transition, and aerodynamic design optimization. He is a member of AIAA (Senior), APS, and ASME, and has contributed to facilities like the $3.5M Khalifa University Low-Speed Wind Tunnel. His teaching includes courses on computational fluid dynamics, quantum computing, and unsteady aerodynamics. Recent research highlights include applications of machine learning in wind field prediction and interdisciplinary projects like interface learning for multiphysics systems. Scientific achievements include publications on hypersonic flow stabilization, quantum solvers for Burgers’ equation, and reduced-order models for urban wind simulation. His lab engages students from high school to PhD levels, emphasizing project-based learning and computational tools. Key collaborations involve NASA, the DOD, and industry partners like Sikorsky Aircraft Corp.

Thomas Le BarbanchonView profile

Professor

• Labor Economics
• Public Finance
• Econometrics
• +5 more

Thomas Le Barbanchon is a Full Professor of Economics at Bocconi University since 2025 and holds the Rodolfo Debenedetti Chair in Labor Economics. He received his PhD from Ecole Polytechnique (CREST-ENSAE) in 2012 and has been affiliated with institutions like CEPR, CREST, J-PAL, LEAP, BIDSA, IGIER, IZA, and IFS. His research focuses on labor economics, particularly job search mechanisms, unemployment insurance effects, gender disparities, and labor market policy evaluation. Educational background: PhD in Economics (Ecole Polytechnique), MSc in Economics (Universitat Pompeu Fabra), Diplôme d'ingénieur statisticien-économiste (ENSAE), and Diplôme d'ingénieur (Ecole Polytechnique) Research highlights include: Quantifying the impact of unemployment insurance reforms in France Analyzing gender differences in job search behavior Studying the effectiveness of hiring credits during economic crises Investigating how traditional AI improves job matching Examining migrant-native job search segregation patterns Scientific contributions appear in top journals like American Economic Journal: Applied Economics , Quarterly Journal of Economics , and Review of Economic Studies . Awards include two ERC grants (2017 & 2024) and the Bocconi Impact Award (2022). He mentors PhD students in economics and labor policy, currently serves as Director of IGIER research center, and maintains active editorial roles at Review of Economic Studies and Journal of the European Economic Association .

Arturo OrellanaView profile

Professor

• Natural Products Synthesis
• Synthetic Methods
• Organic Chemistry
• +3 more

Arturo Orellana is a Full Professor in the Department of Chemistry at York University, specializing in organic synthesis, catalysis, and medicinal chemistry. His research focuses on natural products synthesis, development of new synthetic methods, and heterocyclic compounds with therapeutic potential. He leads the Orellana Lab, actively mentoring graduate and undergraduate students. Key affiliations include the Faculty of Science and collaborations with institutions like Roche. Education details are not explicitly provided, but his professional trajectory includes extensive academic and industrial engagement. His research aligns with UN goals for health and sustainable consumption. Recent work includes publications in Organic Letters , Organic Process Research and Development , and Science Signalling . Students supervised include PhD candidates like Jiaqi Shi and Faizan, along with M.Sc. students such as Abel, Matthew, and Bill. His lab hosts postdoctoral researchers like Dr. Andrei Nikolaev and undergraduates like Natasha. No scientific awards are listed, but his work emphasizes impactful contributions to organic chemistry and drug discovery. Research grants and funding sources are not detailed, but his group's activities include sabbatical work, international presentations (e.g., at Roche, University of Zurich, and University of Paris), and active participation in conferences like the International Congress for Heterocyclic Chemistry. The Orellana Lab collaborates widely, with projects involving reaction development, natural product synthesis, and applications in medicinal chemistry. Future work likely focuses on expanding synthetic methodologies and translating discoveries into therapeutic applications.

• Belt Conveyor Systems
• Bulk Solids Handling
• Energy Efficiency in Material Transportation
• +5 more

Professor Craig Wheeler is a distinguished academic in the School of Engineering at the University of Newcastle, specializing in Mechanical Engineering with a focus on bulk solids handling and belt conveyor technology. As Associate Director of the Centre for Bulk Solids and Particulate Technologies and Deputy Chairman for the Australian Society for Bulk Solid Handling, he has established the university as a global leader in fundamental and applied research within this field. Wheeler's research interests primarily center on reducing the energy intensity and environmental impact of ore and mineral transportation globally. His work develops novel theoretical approaches to model and optimize belt conveyor and bulk handling systems, with significant contributions in energy-efficient transportation, dust emission control, and innovative conveying technologies like the Rail Conveyor system. His research bridges fundamental computational techniques with practical industrial applications, addressing real-world challenges in bulk material handling. His extensive publication record demonstrates trends toward increasingly sophisticated modeling techniques, combining continuum mechanics, discrete element methods, and computational fluid dynamics to solve complex problems in bulk material flow and energy consumption. Recent work shows particular emphasis on large-diameter idler rollers for energy savings, rail-running conveyor systems, and advanced dust control methodologies. 2023 Engineers Australia - Australian Society for Bulk Solids Handling 2017 Significant Contributions to Engineers Australia's Warman Design and Build Competition (Weir Minerals) 2017 Australian Council of Engineering Deans National Award for Engineering Education Excellence 2016 Innovative Technology Award (Australian Bulk Handling) 2010 Rising Star Award (Newcastle Innovation, The University of Newcastle) 2009 Pro-Vice Chancellor's Award for Research Excellence 2006 Best Research and Development Project (Australian Bulk Handling Review) 2000 A.W. Roberts Award (Australian Society for Bulk Solids Handling) Professor Wheeler has successfully led numerous Linkage Projects with major companies including Rio Tinto, Veyance Technologies, and Laing O'Rourke, securing significant cash and in-kind contributions for research projects. His industrial consulting experience, built on a 10-year engineering career with BHP, provides valuable insights that bridge fundamental research with practical applications. He actively supervises research students and contributes to professional development courses both within Australia and internationally. As a key member of the Centre for Bulk Solids and Particulate Technologies in association with TUNRA Bulk Solids, Wheeler leads research teams focused on developing eco-friendly conveying solutions. His work has resulted in new licensed technologies, internationally recognized testing methods, design guidelines, and Australian Standards that have transformed industry practices worldwide.

• Rock Mechanics
• Civil Engineering
• Mining Geotechnics
• +4 more

Professor Anna Giacomini is a leading academic in Rock Mechanics and Civil Engineering at the University of Newcastle. She holds a PhD from the University of Parma, Italy, and has been at the University of Newcastle since 2005. Her roles include Director of the Priority Research Centre for Geotechnical Science and Engineering and Deputy President of the Academic Senate (Research). She specializes in rockfall hazard analysis, mine geotechnics, and numerical modeling of geomechanical systems. Her research focuses on improving safety in mining and civil environments, with over $7.5M in funding and 140+ publications. Key areas include rockfall trajectory analysis, energy absorption in safety barriers, and drapery systems. She has led 20 major projects through ACARP and pioneered low-cost photogrammetric monitoring systems for rock slopes. Professor Giacomini is also a co-founder of HunterWiSE, promoting women in STEM. She has received prestigious awards such as the 2022 NSW Premier’s Engineering Prize and the 2019 John Booker Medal. Her administrative roles include membership in the ARC College of Experts and leadership in gender equity initiatives. Her technical contributions span experimental and numerical rock mechanics, including advancements in discrete element modeling (DEM) and stochastic approaches for discontinuity shear strength prediction. She collaborates internationally with institutions like the Colorado School of Mines and the University of Bologna.

Efthymios N. KaratzasView profile

Assistant Professor

• Numerical Analysis
• Computational Mathematics
• Optimal Control
• +5 more

Efthymios N. Karatzas serves as an Assistant Professor in the Department of Mathematics at Aristotle University of Thessaloniki, Faculty of Sciences, within the Computer Science and Numerical Analysis Section. He maintains an active research profile in computational mathematics with strong institutional affiliations including collaborations with SISSA mathLab and FORTH Institute of Applied and Computational Mathematics. His academic credentials include: PhD in Mathematics, National Technical University of Athens (2015) Master's in Applied Mathematical Sciences – Computational Mathematics, NTUA (2009) Master's in Applied Mathematics, University of Patras (2001) Bachelor's in Mathematics (Computational Mathematics), University of Patras (1999) Dr. Karatzas' research program centers on advanced numerical techniques for partial differential equations , with pioneering work in reduced order modeling , embedded boundary methods , and optimal control systems . His expertise spans computational fluid dynamics, uncertainty quantification, and biomechanical applications, characterized by methodological innovation in handling geometrically complex domains through cut finite element approaches and shifted boundary formulations. Analysis of his 15 most recent publications reveals a cohesive research trajectory focused on developing efficient numerical frameworks for parametrized PDE systems. His work consistently bridges theoretical rigor with practical implementation, particularly in advancing reduced basis methods for fluid-structure interaction and biological modeling, demonstrating significant contributions to computational mathematics through high-impact journal publications. No major scientific awards are documented in the available sources. Dr. Karatzas demonstrates research leadership through project management roles including Scientific Manager for the ELIDEK project at NTUA (2019-2021) and Project Manager for the European Social Fund HEaD initiative at SISSA (2017-2019). His grant administration experience encompasses coordinating interdisciplinary teams and securing external funding for computational mathematics research. He maintains active collaborations with the SISSA mathLab in Trieste (particularly with Prof. Gianluigi Rozza's group) and the FORTH Institute in Crete, participating in international workshops including the Reduced Order Methods in CFD Summer School (2019) and SIAM UQ conferences. His research network spans computational mathematics groups across Europe with emphasis on advancing numerical methodologies for real-world engineering and biological applications.

• Algorithms for Big Data Analytics
• Computational Geometry
• Machine Learning
• +4 more

Jeff M Phillips is a Professor in the Kahlert School of Computing at the University of Utah, specializing in algorithms for big data analytics, computational geometry, and machine learning. He holds a BS in Computer Science and Mathematics from Rice University (2003) and a PhD in Computer Science from Duke University (2009). He serves as Director of the Utah Center for Data Science, Director of the Data Science Program in the Kahlert School of Computing, and Faculty Co-Director of the One U Data Science Hub. His research focuses on geometric data analysis, coresets, sketches, and handling uncertainty in data. Education: BS/BA (Rice University, 2003), PhD (Duke University, 2009) CI Postdoctoral Fellow at University of Utah (2009–2011) His research interests include algorithms for big data analytics, computational geometry, machine learning, spatial statistics, and AI. He has led NSF-funded projects on spatial data analysis, cosmic origins via AI, and reactive flow data modeling. Phillips has advised numerous PhD and master’s students, contributing to topics like trajectory classification and bias mitigation in word embeddings. His publications span computational geometry, data science, and machine learning. Notable work includes coresets for kernel density estimates, bias mitigation in language models, and scalable spatial scan statistics. Phillips is also active in academic service, serving as co-PC chair for SoCG 2024 and on program committees for major conferences like NeurIPS and ICML.

D.S. Fahmeed HyderView profile

Professor

• Magnetic Resonance Imaging
• Neuroimaging
• Molecular Imaging
• +3 more

D.S. Fahmeed Hyder is a Professor of Biomedical Engineering at Yale University, with additional appointments in Radiology & Biomedical Imaging. He holds a Ph.D. from Yale University and leads the Hyder Lab, which focuses on advancing quantitative and translational imaging technologies using magnetic resonance methods to study brain function and dysfunction at the laminar level. His research integrates multidisciplinary approaches, including molecular imaging, neurophysiology, and material science. Research Interests: Neurovascular and neurometabolic coupling mechanisms Molecular imaging probes for disease diagnostics Functional MRI (fMRI) and metabolic imaging in health and disease Imaging applications for Alzheimer’s, stroke, and cancer Publications: Dr. Hyder’s recent work emphasizes cutting-edge imaging techniques, such as pH-sensitive biosensors, high-resolution fMRI, and multimodal optical imaging. His research highlights include studies on neurovascular dysfunction in Alzheimer’s models, therapeutic interventions for brain injury, and molecular imaging of tumor microenvironments. Awards: Niels Lassen Award (2003), for cerebral blood flow research Early Career Faculty Award (1998), NSF & NIH Pilot Awards from JDRF & Yale-UCL Collaborative (2008, 2013) Labs/Teams: The Hyder Lab collaborates with institutions like UCL and the James S. McDonnell Foundation, advancing translational imaging solutions for clinical applications.