Find Academic Supervisors

Derek BeachView profile

Professor

• EU Integration Processes
• Process Tracing Methodology
• Voter Behavior
• +7 more

Derek Beach is a Professor at the Department of Political Science, Aarhus University. His expertise lies in advancing process tracing methodology for academic research and policy evaluation, with a focus on European integration processes, voter behavior, and case study methods. He is currently leading a four-year project on Mechanisms and Mechanistic Evidence in the Social Sciences. Research Interests: Beach specializes in methodological development of process tracing, applying it to both academic and policy contexts. His substantive research explores EU crisis negotiations, the role of analogical reasoning in policy analysis, and evidential pluralism in social science research. He has co-authored a textbook on foreign policy analysis and process tracing in Danish. Collaborations & Consultancy: Beach collaborates with the Wellbeing Investments in Schools and Enterprises (WISE) project at the University of Birmingham and has worked with the World Bank's Independent Evaluation Group and the Joint Data Center (World Bank/UNHCR) on policy evaluations. His consultancy work spans UN agencies and global institutions. Teaching: He teaches across all levels (BA to PhD), including courses on Methods, US Presidential Election Simulation Models, and Case-Based Methods. His pedagogical focus aligns with his methodological research, emphasizing process tracing and evaluation techniques. Publications & Contributions: His scholarly work includes foundational texts on process tracing and empirical studies on EU integration. He has contributed to journals like European Journal of Political Research , Synthese , and Sociological Methods & Research , though specific publication years are not listed in the provided data.

Carolyn Conner SeepersadView profile

Professor

• Design for Additive Manufacturing
• Engineering Design
• Additive Manufacturing
• +4 more

Carolyn Conner Seepersad serves as the J. Mike Walker Professor of Mechanical Engineering at the University of Texas at Austin and directs the Center for Additive Manufacturing and Design Innovation. She holds membership in the U.T. System Academy of Distinguished Teachers and maintains active leadership in the additive manufacturing community through roles such as co-organizer of the Solid Freeform Fabrication Symposium and ASME Design Engineering Division Executive Committee membership. Her academic credentials include: PhD in Mechanical Engineering from Georgia Tech (2004) MA/BA in Philosophy, Politics and Economics from Oxford University (1998, Rhodes Scholar) BS in Mechanical Engineering from West Virginia University (1996) Dr. Seepersad's research centers on computational design methodologies and additive manufacturing innovation , with particular expertise in simulation-based design of complex systems, environmentally conscious product development, and materials engineering. Her work bridges theoretical design frameworks with practical manufacturing applications, emphasizing sustainability and performance optimization across aerospace, automotive, and energy systems. Current projects explore reactive extrusion additive manufacturing, negative stiffness materials, and machine learning integration for process-aware design. Analysis of her 15 most recent publications reveals a dominant focus on process innovation in additive manufacturing (70%), particularly stereolithography and selective laser sintering, with growing emphasis on data-driven design approaches (20%) and sustainable engineering applications (10%). Her work demonstrates consistent progression from fundamental material design toward integrated system optimization and industrial scalability. Her scientific recognition includes: International Outstanding Young Researcher Award in Freeform and Additive Manufacturing (2009) UT System Regents’ Teaching Award (2010) ASME Design Automation Committee Outstanding Young Investigator Award (2010) ASEE Outstanding New Mechanical Engineering Educator Award (2013) Multiple ASME and ASEE best paper awards U.T. System Academy of Distinguished Teachers membership Dr. Seepersad maintains an extensive advising portfolio with 48 graduate students (16 PhD, 24 MS, and 8 current) plus 2 postdoctoral researchers, reflecting sustained research productivity and educational impact. Her Product, Process, and Materials Design Lab fosters interdisciplinary collaboration between mechanical engineering, materials science, and computational design teams.

• Software Engineering
• Model-Driven Engineering
• Automotive Embedded Systems
• +3 more

Vera Pantelic is an Adjunct Assistant Professor in the Department of Computing and Software at McMaster University. Her research focuses on software engineering practices for model-based development in automotive systems, particularly centralized Electrical/Electronic (E/E) architectures, Simulink modeling, and supervisory control of probabilistic discrete event systems. Education: Not explicitly mentioned in the text. Her scholarly activity includes extensive contributions to conferences and journals in automotive software engineering, model transformation, and real-time systems. Her work addresses challenges in modularity, documentation, and compliance within automotive embedded systems. Her recent publications emphasize advancements in centralized E/E architectures, model-driven testing, and assurance cases for automotive safety. She collaborates on topics integrating software engineering principles with automotive domain requirements. Scientific Awards: No specific awards mentioned in the text. She serves as an advisor in software engineering, though specific student names are not listed. Her projects involve simulation-based testing, model refactoring, and compliance frameworks, supported by industry partnerships and academic grants. Her work contributes to labs and teams focused on automotive software reliability and model-driven engineering. No explicit lab or team affiliations are detailed in the provided text.

• Semiconductor Physics
• Microwave Engineering
• Cryogenic Electronics
• +3 more

Niklas Rorsman is a Research Professor at the Microwave Electronics group, part of the Department of Microtechnology and Nanoscience at Chalmers University of Technology . His work focuses on advanced semiconductor devices, particularly gallium nitride (GaN) and silicon carbide (SiC) high-electron-mobility transistors (HEMTs) for microwave and cryogenic applications. Expertise : Semiconductor device physics, microwave electronics, cryogenic transistor characterization Key Technologies : GaN HEMTs, SiC MESFETs, graphene FETs Rorsman's research investigates trapping effects, thermal management, and material optimization in GaN/SiC devices. Recent studies explore field plates for cryogenic stability, recessed ohmic contacts, and high-κ dielectric interfaces. His publications demonstrate a focus on improving device linearity, noise performance, and reliability through structural and process innovations. Selected trends in his work include: Cryogenic GaN HEMTs with superconducting Nb gates Buffer-free AlGaN/GaN heterostructures for high breakdown voltage Graphene integration for millimeter-wave communication systems Advanced SiNx passivation and gate stack engineering Contact: niklas.rorsman@chalmers.se

Seyed Mojtaba HoseyniView profile

Lecturer

• Process Safety
• Hydrogen Safety
• Risk Assessment
• +6 more

Dr. Seyed Mojtaba Hoseyni is a Lecturer in Process Safety and Loss Prevention at the School of Chemical, Materials and Biological Engineering, University of Sheffield. Previously a Postdoctoral Research Associate at the same institution (2022-2024), he holds a PhD in Energy Engineering from Politecnico di Milano (2021). His research focuses on enhancing system resilience, risk assessment, and decision-making under uncertainty in engineering systems, particularly for decarbonization applications. Royal Academy of Engineering Global Talent (Exceptional Promise) in Chemical and Process Engineering His work spans hydrogen safety, climate change risk, nuclear engineering safety, and predictive maintenance. Recent publications emphasize integrating resilience metrics into HAZOP analysis and optimizing sensor placement for risk-informed decision-making. Teaching activities include the Hazards and Protections module (CPE61020). Specializes in RAMS (Reliability, Availability, Maintainability, and Safety) analysis Develops safety frameworks for hydrogen energy systems Applies advanced computational techniques to nuclear and industrial safety

Thomas Cheatham IIIView profile

Professor

• Computational Chemistry
• Molecular Dynamics
• Biomolecular Simulation
• +4 more

Thomas Cheatham III is a Professor of Medicinal Chemistry in the College of Pharmacy and Adjunct Professor of Biomedical Engineering at the University of Utah, specializing in computational biomolecular simulation methodologies. His work bridges theoretical chemistry and biological applications through advanced molecular dynamics techniques. Education: B.A., Middlebury College Ph.D., University of California, San Francisco Research Focus: Dr. Cheatham pioneers molecular dynamics and free energy simulation methods (AMBER/CHARMM) for proteins, nucleic acids, and lipids. His group addresses critical challenges in environmental dependence of nucleic acid structure (ion/hydration effects on DNA), conformational transition pathways (e.g., B-DNA/Z-DNA junctions), and macromolecular flexibility beyond static experimental structures. Recent innovations target force field refinement for modified nucleic acids and polarizable models. Publication Trends: Analysis of his 2023-2025 publications reveals three dominant themes: (1) Nucleic acid force field optimization (60% of recent work), particularly RNA/DNA parameterization; (2) Development of simulation infrastructure including FAIR data principles and AmberTools; (3) Application-driven studies of therapeutic targets like Bcr-Abl inhibitors. His work increasingly integrates polarizable force fields and high-performance computing. Research Infrastructure: He leads the AMBER biomolecular simulation software development effort and maintains an active laboratory focused on methodological innovation. His group collaborates extensively with experimentalists to validate computational predictions and provides open-source tools (PTRAJ/CPPTRAJ) used globally. Current initiatives emphasize reproducibility through standardized simulation protocols and data sharing frameworks.

Rajesh RanjanView profile

Assistant Professor

• Fluid Dynamics
• Turbulence
• Turbomachinery Flows
• +4 more

Rajesh Ranjan is an Assistant Professor in the Department of Aerospace Engineering at the Indian Institute of Technology Kanpur. His academic career spans multiple prestigious institutions including Ohio State University and Jawaharlal Nehru Centre for Advanced Scientific Research. Dr. Ranjan completed his PhD (2016) from Jawaharlal Nehru Centre for Advanced Scientific Research, Bengaluru, ME (2007) from Indian Institute of Science, Bengaluru, and BE (2005) from Bihar Institute of Technology, Sindri where he achieved First Rank with Roll of Honor. His educational background laid the foundation for his expertise in fluid dynamics and computational methods. His research focuses on fundamental and applied aspects of fluid dynamics with specialization in turbomachinery flows, applied aerodynamics, stability and flow control, transition and relaminarization phenomena, and high performance computing applications. Dr. Ranjan employs a multidisciplinary approach combining theoretical analysis, advanced computational techniques, and experimental validation to address complex fluid flow problems in aerospace engineering. His work has significant implications for improving efficiency in turbomachinery design and understanding fundamental flow physics in complex geometries. Dr. Ranjan's publication record reveals a strong trajectory in computational fluid dynamics with recent work spanning traditional aerospace applications like turbomachinery and aircraft aerodynamics while also demonstrating adaptability through interdisciplinary research such as his data-driven approach to modeling the COVID-19 pandemic. His publications consistently demonstrate rigorous methodology and innovative approaches to complex fluid flow problems. All India Rank-3, Graduate Aptitude Test in Engineering (GATE), India (2005) Roll of Honor (First Rank), B.E., BIT, Sindri, India (2001-2005) Outstanding Performance Award (thrice), TATA CRL, Pune, India (2008-10) ICAM International Travel Award, Institute for Complex Adaptive Matter (2013) International Travel Support Award, DST, Govt. of India (2014) Best Poster Award, JNCASR In-house Symposium, Bengaluru, India (2015) Dr. Ranjan has mentored multiple students through research projects at IIT Kanpur and previously at Ohio State University. His research has been supported by institutional funds and travel awards from national agencies including the Department of Science and Technology, Government of India. He maintains active collaborations with researchers in India and internationally to advance computational fluid dynamics methodologies and their application to real-world engineering problems.

William NewmanView profile

Professor

• Geophysics
• Planetary Science
• Astrophysics
• +5 more

William Newman is a Professor in the Department of Earth, Planetary, and Space Sciences at the University of California, Los Angeles (UCLA), currently on sabbatical at the Institute for Advanced Study in Princeton. His primary academic home resides within UCLA's geoscience and planetary science division. His educational credentials include: B.Sc. (Hon.) in Physics from the University of Alberta, Canada (1971) M.Sc. in Physics from the University of Alberta, Canada (1972) M.S. in Astronomy and Space Science from Cornell University (1975) Ph.D. in Astronomy and Space Science from Cornell University (1979) Professor Newman applies theoretical physics and applied mathematics to solve critical real-world problems across multiple disciplines. His research spans statistical techniques for climate change assessment, earthquake hazard modeling, solar system evolution (including collision risks from trans-Jovian bodies), astrophysical jet dynamics, and pattern emergence in complex systems. This interdisciplinary work bridges geophysics, planetary science, and astrophysics through rigorous mathematical frameworks. His publication record (2024-2016) reveals three dominant research thrusts: (1) Semiconductor electron emission physics (GaAs nanotips, photoemission sources), (2) Solar system dynamics and celestial mechanics (N-body simulations, impact hazards), and (3) Complex systems analysis (earthquake patterns, statistical record-breaking events). These intersect physics, earth sciences, and computational mathematics through shared methodologies in statistical modeling and nonlinear dynamics. At UCLA, Newman developed innovative courses including a natural disasters undergraduate GE course (satisfying diversity requirements) and graduate-level planetary atmospheres and continuum mechanics curricula. His academic contributions include over 100 refereed papers and graduate textbooks published by Princeton and Cambridge University Presses, focusing on mathematical methods for geophysics and space physics.

Farzin ZareianView profile

Professor

• Structural Engineering
• Earthquake Engineering
• Performance-Based Earthquake Engineering
• +2 more

Farzin Zareian is a Professor in Civil and Environmental Engineering at the Samueli School of Engineering, University of California, Irvine. His research focuses on performance-based earthquake engineering, collapse analysis, structural reliability, and structural control. Ph.D. in Structural Engineering, Stanford University (2006) M.S. and B.S. in Civil/Earthquake Engineering, Sharif University of Technology (1997, 1995) Zareian's research integrates analytical and experimental approaches to advance earthquake resilience in structural systems. Key areas include base plate connections, seismic response of asymmetric structures, and validation of simulated ground motions. His work with the Performance Based Earthquake Engineering Laboratory emphasizes practical applications in structural safety. Recent publications highlight innovations in column base modeling, seismic demand prediction, and infrastructure recovery frameworks. Notable trends in his 2021–2025 articles include machine learning for ground motion prediction, resettable structural systems, and probabilistic drift profile analysis for multistory buildings.

Reza SamaviView profile

Associate Professor

• Information Security
• Machine Learning
• Trustworthy AI
• +5 more

Dr. Reza Samavi is an Associate Professor at Toronto Metropolitan University's Department of Electrical, Computer, and Biomedical Engineering, Faculty of Engineering & Architectural Science. He is also a Faculty Affiliate with the Vector Institute for Artificial Intelligence and directs the Trustworthy AI Research Lab (TAILab). Previously, he served as Assistant Professor and eHealth Graduate Program Coordinator at McMaster University's Department of Computing and Software (2014-2020). Holding a PhD in Computer Science (University of Toronto, 2013), his academic journey bridges industry experience with rigorous scholarly contributions. His research lies at the critical intersection of Trustworthy AI , Machine Learning Security , and Medical Informatics . He investigates Safety & Security of ML Algorithms Privacy-Preserving AI Systems Transparency Frameworks for Medical AI Blockchain-enabled Privacy Auditing Game Theory for Model Robustness Optimization-based Anonymization Techniques The TAILab research group under his leadership has produced groundbreaking work in Uncertainty Quantification for Neural Networks Robustness Against Adversarial Attacks Medical Image Analysis Clinical Decision Support Systems Emergency Medicine Predictive Modeling His recent projects focus on enhancing migrant youth mental health through LLM-based conversation agents and developing certified robustness guarantees for ensemble networks. Dr. Samavi's scholarly excellence is recognized through Privacy Technologies Research Award (IBM) Privacy By Design Research Award (Ontario IPC) Bridging Divides Emerging Research Grant (TMU) NSERC PGS-D Recipient (Co-supervised student) SOSCIP Accelerator Grant He has secured major funding from NSERC , SOSCIP , MITACS , HHS , and IDEaS programs. As a dedicated educator, Dr. Samavi teaches graduate courses in Secure Machine Learning and Software Testing while mentoring 15+ graduate students across PhD , MASc , and MEng programs. His lab has presented at premier venues including AAAI , IJCAI , and IEEE Transactions while maintaining active collaborations with institutions like Harvard, ETH Zurich, and the University of Waterloo.

• Computer Supported Cooperative Work (CSCW)
• Human-Centered Computing
• Human-Computer Interaction
• +7 more

Pernille Bjørn is a Professor in Computer Supported Cooperative Work (CSCW) at the Department of Computer Science , University of Copenhagen (DIKU), where she has been since May 2015. Her research investigates collaborative work practices to design cooperative technologies, focusing on domains like healthcare, global software development, startup companies, and digital fabrication. Faculty of Science, University of Copenhagen Human-Centred Computing Section Research Interests : Bjørn’s work spans CSCW , Human-Computer Interaction , and Digital Fabrication , with applications in healthcare systems, cross-cultural software development, and inclusive technology design. She explores collaborative virtual reality training, FemTech, and crisis computing. ACM Distinguished Member (2024) Publications : Published in top venues like ACM Transactions on Computer-Human Interaction , CSCW , and CHI , her recent work examines hybrid work asymmetry, neurodiverse accessibility, and art-driven collaborative research.

Otto LappiView profile

Research Fellow

• Cognitive Science
• Human Performance
• Gaze Control
• +3 more

Dr. Otto Lappi is a Research Fellow at the University of Helsinki's Department of Digital Humanities, Faculty of Arts. His work bridges cognitive science and human performance in complex dynamic tasks, particularly focusing on predictive processing in visuomotor control. PhD in Cognitive Science Title of Docent at University of Helsinki Academy Research Fellow (2020-2025) His research explores: Cognitive mechanisms in high-speed sports and driving Predictive gaze strategies and steering control Flow states in skill acquisition VR and eye-tracking applications in archaeomusicology Neural substrates of domain expertise Recent publications analyze: Flow-state dynamics in visuomotor learning Predictive gaze behavior in automated driving Computational models of attention in distracted driving Chunking mechanisms in high-speed sports performance Scientific contributions include: Academy Research Fellow (Research Council of Finland) Editorial work on high-performance cognition Organizing cognitive science workshops As doctoral supervisor, he has guided: Samuel Tuhkanen (Predictive Gaze and Steering) Jesse Kuokkanen (Mechanistic Computationalism) Ida Maasalo (Driver Behavior) Markus Mattsson (Psychometrics)

Eric LeeperView profile

Professor

• Macroeconomics
• Monetary and Fiscal Policy Analysis
• Applied Time Series

Eric Leeper is the Paul Goodloe McIntire Professor in Economics at the University of Virginia (since 2018) and Director of the Virginia Center for Economic Policy. He is also a Research Associate at the National Bureau of Economic Research and serves on advisory councils for the Federal Reserve Bank of Atlanta and Bundesbank. Previously, he held the Rudy Professorship at Indiana University and worked in the Federal Reserve System. Ph.D. in Economics (University of Minnesota, 1989) B.S. in Economics (George Mason University, 1980) His research focuses on macroeconomic policy modeling, emphasizing monetary-fiscal interactions, the fiscal theory of the price level, sovereign risk, and fiscal limit analysis. Recent work examines government spending impacts, fiscal imbalances resolution, and heterogeneous-consumer environments in fiscal inertia. Key publication themes include fiscal theory of the price level, inflation dynamics, sovereign debt risk, policy regime shifts, and monetary-fiscal coordination challenges. Articles frequently address historical policy frameworks (e.g., Great Depression) and modern crises like the post-COVID inflationary period. Appointments required for office hours. Contact: Monroe Hall, Room 252, University of Virginia; 434-924-3933.

• Sustainable Architecture
• Urban Climate Modeling
• Internet of Things in Construction
• +6 more

Matteo Giovanardi serves as a Visiting Professor at the Interuniversity Department of Regional and Urban Studies and Planning (DIST) at Politecnico di Torino. He has been actively engaged as a course collaborator for architecture and urban planning programs since the 2019/20 academic year, teaching modules in Architectural Technology, Advanced Environmental Technological Design, and Environmental Technological Design across both Bachelor's and Master's degree courses. His research focuses on the intersection of sustainable architecture, digital technologies, and urban planning, with particular emphasis on: Urban climate and microclimate modeling tools for Sustainable Development Goals Internet of Things applications for building process innovation Circular economy approaches in façade and building envelope design Environmental sensing systems for healthy urban districts Urban agriculture solutions for self-sufficient cities Giovanardi's publication record demonstrates an evolving research trajectory toward integrating digital technologies with sustainable building practices. His recent work shows increasing emphasis on IoT for building traceability, circular construction methodologies, and sophisticated environmental modeling techniques that bridge architecture, environmental engineering, and urban policy. His 2023 doctoral thesis on IoT applications for building envelope design represents a significant contribution to this field. He maintains active collaborations with researchers including Riccardo Pollo (who served as his doctoral advisor), Matteo Trane, Thaleia Konstantinou, and Tillmann Klein, producing interdisciplinary work that addresses contemporary urban challenges related to climate change adaptation, resource efficiency, and healthy city development.

Fabrizio MarinelliView profile

Associate Professor

• Biophysics
• Molecular Simulation
• Membrane Transport
• +3 more

Fabrizio Marinelli is an Associate Professor of Biophysics and Data Science at the Medical College of Wisconsin (MCW), effective July 2025, and holds an adjunct senior investigator position at the Versiti Blood Research Institute. He previously served as a staff scientist at the National Heart, Lung, and Blood Institute (NHLBI/NIH) and conducted postdoctoral research at the Max Planck Institute of Biophysics and NIH. Educational background includes a PhD in Statistical and Biological Physics from the International School for Advanced Studies (Trieste, Italy), an MS in Chemistry from La Sapienza University (Rome), and postdoctoral training in molecular biophysics. His research focuses on computational modeling of molecular mechanisms in membrane transport, signaling, and morphological changes, integrating advanced simulation techniques with experimental data (e.g., EPR/DEER, HDX-MS, cryo-EM). Key methodologies include enhanced sampling methods, free-energy calculations, and machine learning. Research highlights include elucidating mechanisms of Na+/Ca2+ exchangers, ion selectivity in lysosomal K+ channels, and structural interpretation of DEER and HDX data. He leads the Biophysics Graduate Program’s recruitment efforts and actively collaborates with experimental labs to bridge theory and experiment. Lab members include postdocs William Brown and Sandra Byju, and graduate student Tyler Trask. Publications emphasize computational tools (e.g., PLUMED, Colvars library) and reproducibility in molecular simulations. His work aims to advance therapies for infectious diseases, drug resistance, and cancer through mechanistic insights into proteins and membranes.