Find Academic Supervisors

• Renewable Power Systems
• Wind Energy Integration
• Hybrid Electric Vehicles
• +3 more

Ola Carlson is a Professor in Sustainable Electric Power Production at Chalmers University of Technology. He specializes in electrical systems for renewable power production and hybrid electric vehicles. Since 2022, he serves as a senior advisor to the Swedish Wind Centre, focusing on island operation with Chalmers wind turbine and battery systems. Research Interests His research spans renewable power systems, wind energy integration, grid stability, and microgrid optimization. Key projects include modeling Nordic transmission systems, analyzing wind turbine bearing currents, and developing maintenance schedules for aging components. Article Trends Recent publications emphasize wind turbine design, microgrid stochastic optimization, and dynamic state estimation for transmission protection. Topics cover machine learning applications in forecasting, fault handling, and battery degradation impacts on energy systems. Projects & Collaborations RESIST - Energy islanding for resilient systems (2026–2027) COSPACT - Nordic-Baltic co-simulation platform (2020–2023) Fossil Free Energy Districts (2016–2019) Collaborations with ABB, Swedish Energy Agency, and European Commission Labs & Teams Works with Power Grids and Components at Chalmers, leading projects like 'Detecting and eliminating bearing currents' (2018–2023) funded by the Swedish Energy Agency. Involved in Chalmers Campus as a testbed for intelligent grids.

Neda Haj HosseiniView profile

Senior Lecturer

• Biomedical Engineering
• Medical Imaging
• Artificial Intelligence in Healthcare
• +3 more

Neda Haj Hosseini is a Senior Lecturer and Associate Professor in Biomedical Engineering at Linköping University's Department of Biomedical Engineering (IMT) . She contributes to teaching courses like TBMT56 - Medical Technology and TBME08 - Biomedical Modeling and Simulation , while leading research initiatives in AI-driven cancer diagnostics and biomedical optics. Research Focus: Development of AI methods for cancer diagnostics, optical coherence tomography (OCT) applications, and fluorescence spectroscopy in surgical guidance Affiliations: Center for Medical Image Science and Visualization (CMIV) , Analytic Imaging Diagnostic Arena (AIDA) , Swedish Medical Technology Association Recent Research Trends demonstrate expertise in applying deep learning to: Pediatric brain tumor classification using multimodal imaging Optical biopsy techniques for intraoperative decision support Automated biomarker quantification in histopathology Medical imaging data integrity and algorithm validation Scientific Awards include grants from: Joanna Cocozza Foundation (2022) Swedish Childhood Cancer Foundation (2024) Academic Leadership involves mentoring students in projects such as: "Multiple Instance Attention-based Learning for Brain Tumor Classification" "Vision Transformers for Multiclass Brain Tumor Tissue Classification" "Reaction-diffusion Models for Image-driven Tumor Simulation"

Leah SchubertView profile

Associate Professor

• Medical Physics Education
• Radiation Oncology Safety
• Quality Assurance
• +6 more

Leah Schubert, PhD is an Associate Professor in the Department of Radiation Oncology at the University of Colorado Anschutz Medical Campus School of Medicine. She serves as Director of the Medical Physics Residency Program, leading educational initiatives in medical physics training. Her professional focus centers on improving safety, quality, and educational standards in radiation oncology physics. Dr. Schubert earned her PhD from the University of Wisconsin - Madison in 2009 and completed her undergraduate studies with a BS from the University of California–San Diego in 2003. She is board certified in Therapeutic Medical Physics by the American Board of Radiology (2012). Her research spans medical physics education, radiation safety, quality assurance, and functional imaging applications in radiation therapy. She has pioneered work in physics plan review training, safety checklist implementation, and 4DCT-ventilation imaging for functional avoidance radiation therapy. Her educational research focuses on concept inventories, virtual interviewing for residency matches, and cross-institutional residency training frameworks. Analysis of her recent publications reveals a consistent focus on improving safety culture in radiation oncology through systematic approaches including failure modes and effects analysis, simulated error training, and safety checklist development. Her work increasingly incorporates cross-institutional collaboration and educational innovation in medical physics training. ABR Volunteer Services Award, American Board of Radiology (2023) Board Member at Large, Society of Directors of Academic Medical Physics Programs (2022) AAPM Fellow, American Association of Physicists in Medicine (2022) Excellent Patient Safety Role Model, University of Colorado Hospital (2021) ABR Volunteer Services Award, American Board of Radiology (2020) IAEA Competition Towards a Strong Safety Culture in Radiation Medicine, International Atomic Energy Agency (2019) As Director of the Medical Physics Residency Program, Dr. Schubert oversees comprehensive training for future medical physicists, implementing innovative approaches to curriculum development and assessment. Her leadership extends to national committees including the AAPM Work Group on Periodic Review of Medical Physics Residency Training and various SDAMPP committees. She has secured funding for educational initiatives focused on improving residency training standards and safety culture development. Dr. Schubert collaborates extensively with multi-institutional research teams, particularly in the area of 4DCT-ventilation imaging and its clinical applications for functional avoidance radiation therapy. Her work bridges clinical practice, safety initiatives, and educational innovation in medical physics.

• Human-Computer Interaction
• Virtual Reality
• Extended Reality
• +4 more

Teresa Hirzle is a Tenure Track Assistant Professor at the Department of Computer Science , University of Copenhagen , specializing in Human-Centred Computing . Her research focuses on Human-Computer Interaction (HCI) , Virtual Reality (VR) , Extended Reality (XR) , and Gaze-Based Interaction . Research Interests: Designing interaction techniques for immersive environments Eye movement analysis for educational applications Addressing digital eye strain in interactive systems Evaluating user experience in VR/AR Recent Research Trends: Her recent publications examine AI representation in VR co-creation, VR sickness in locomotion, eye strain in gaze-driven systems, and hybrid applications of comics/AR. She also explores pedagogical implications of eye tracking in remote learning. Contact: Email: tehi@di.ku.dk Office: Sigurdsgade 41, 2200 København N.

• Architectural Technology
• Bioclimatic Design
• Building Performance
• +8 more

Giacomo Chiesa is a Full Professor at the Department of Architecture and Design (DAD) at Politecnico di Torino. He is a member of the Interdepartmental Center Ec-L - Energy Center Lab. His research focuses on Architectural Technology , Bioclimatic Design , Building Performance , and Urban Climate . Research Interests : Building Simulation, Passive Cooling, Smart Buildings, Digital Twin, Climate Change Adaptation Recent publications analyze urban weather datasets for energy simulations, shading control thresholds , and ventilation strategies in educational buildings. His work covers energy renovation roadmaps , thermal comfort , and climate-resilient building systems . Teaching : PhD courses in Human-Centric Methodologies and MSc courses in ICT in Building Design Research Leadership : Scientific Director for projects like Urban Generation and Prelude , EU-funded initiatives

Andreas LööwView profile

Lecturer

• Hardware Verification
• Software Verification
• Symbolic Execution
• +5 more

Andreas Lööw is a Lecturer at Royal Holloway, University of London , focusing on hardware and software verification. Previously, he was a postdoctoral researcher at Imperial College London under Philippa Gardner , contributing to the Gillian Platform . He completed his PhD at Chalmers University of Technology under Magnus Myreen , specializing in interactive theorem proving and hardware verification. His research explores symbolic execution, separation logic, and formal verification of hardware/software systems. Key projects include Betterlog (Verilog semantics reformulation) and foundational work on the Gillian Platform . 2025 : Compositional Symbolic Execution for Memory Models 2025 : Simulation Semantics of Synthesisable Verilog 2024 : Compositional Symbolic Execution for Correctness/Incorrectness 2023 : Exact Separation Logic (Distinguished Paper at ECOOP'24) 2023 : Hardware Verification of Pipelined Processors 2022 : Verilog Concurrency Analysis 2021 : Verified Verilog Compiler (Lutsig) Scientific Awards : Distinguished Paper at ECOOP 2024 He maintains the vv Verilog visualization tool and collaborates on the Gillian Platform . Contact: andreas.loow@rhul.ac.uk

Doug BowmanView profile

Professor

• Virtual Reality
• Augmented Reality
• 3D User Interfaces
• +3 more

Doug Bowman is the Frank J. Maher Professor in the Department of Computer Science at Virginia Tech and Director of the Center for Human-Computer Interaction. His work focuses on advancing virtual reality (VR), augmented reality (AR), and 3D user interfaces, with a strong emphasis on human-computer interaction and immersive environments. Education: Ph.D., Computer Science, Georgia Institute of Technology (1999) M.S., Computer Science, Georgia Institute of Technology (1997) B.S., Mathematics and Computer Science, Emory University (1994) Research Interests: Bowman explores the design and evaluation of immersive technologies, including VR/AR interfaces, 3D interaction techniques, and the application of these technologies in fields like healthcare, education, and collaborative work. His work often addresses challenges in spatial awareness, gaze-driven systems, and context-aware interfaces. Recent publications highlight trends in collaborative AR/VR systems, glanceable interfaces, and adaptive techniques for immersive analytics. His research emphasizes real-world applications, such as medical training through AR and improving productivity in virtual workspaces. Lab Affiliation: Director of Virginia Tech’s Center for Human-Computer Interaction, which focuses on interdisciplinary research in interactive technologies.

Xujie SiView profile

Assistant Professor

• Artificial Intelligence
• Machine Learning
• Software Engineering
• +5 more

Xujie Si is an Assistant Professor in the Department of Computer Science at the University of Toronto. He is also a faculty affiliate at the Vector Institute and an affiliate member at Mila - Quebec AI Institute, holding a Canada CIFAR AI Chair. Previously, he served as an Assistant Professor at McGill University's School of Computer Science. Education: Ph.D., Computer and Information Science, University of Pennsylvania (advised by Mayur Naik) M.S., Computer Science, Vanderbilt University B.E. (with Honors), Nankai University Research Focus: His work bridges AI and program reasoning, emphasizing the integration of statistical and logical methods. Key areas include: Static analysis and verification using deep learning/reinforcement learning Neuro-symbolic systems for urban simulation (e.g., LogiCity) Automated theorem proving via LLMs and symbolic reasoning Program repair and compiler fuzzing Recent Article Trends: Recent work focuses on synergizing LLMs with symbolic reasoning (e.g., Olympiad inequality proving), advancing SAT solving with graph neural networks, and applying neuro-symbolic methods to Euclidean geometry formalization. Awards: Canada CIFAR AI Chair (2023) Lab/Teams: Leads research teams exploring program analysis, neuro-symbolic AI, and formal verification at the University of Toronto and Vector Institute.

Mario A. SvirskyView profile

Professor

• Auditory Neuroscience
• Cochlear Implants
• Speech Perception
• +3 more

Mario A. Svirsky is the Noel L. Cohen Professor of Hearing Science and Professor of Neuroscience at NYU Grossman School of Medicine. He leads the Laboratory for Translational Auditory Research, focusing on auditory neural prostheses like cochlear implants and their impact on speech perception and neuroplasticity. His work bridges clinical care and scientific discovery, addressing how the brain adapts to sensory deprivation and degraded auditory input. Education: PhD in Biomedical Engineering from Tulane University (1988). Postdoctoral training at MIT and prior academic appointments at Indiana University and Purdue University before joining NYU in 2005. Research: Explores cochlear implant performance optimization, speech perception in hearing-impaired individuals, and neuroplasticity mechanisms. Collaborates with the Froemke Lab on animal models of cochlear implantation. Active in developing computational models and signal processing techniques to improve implant efficacy. Funding: Principal investigator on multiple NIH grants (e.g., R01 DC016839, R01 DC016834) and industry partnerships. His lab’s work has advanced clinical management strategies for cochlear implant users, including those with contralateral hearing aids. Labs/Teams: Directs the Laboratory for Translational Auditory Research, collaborating with multidisciplinary teams including engineers, neuroscientists, and clinical audiologists. Mentors postdocs, audiologists, and medical students in auditory research.

• Industrial Organization
• Game Theory
• Econometrics
• +5 more

C. Lanier Benkard is the Gregor G Peterson Professor of Economics at the Graduate School of Business, Stanford University. He is a prominent researcher in industrial organization, game theory, and econometrics, focusing on dynamic models of market competition and structural estimation. Research Interests: His work spans Dynamic games and equilibrium modeling Hedonic pricing and demand estimation Econometric tools for imperfect competition Computational methods for large-scale industries Publication Trends: His research emphasizes oblivious equilibrium approximations, strategic interactions in concentrated industries, and empirical analysis of markets with heterogeneous consumers. He frequently collaborates with scholars like Gabriel Weintraub and Patrick Bajari. Tools & Extensions: He has developed computational resources, including C++ and Matlab code, to analyze oblivious equilibrium. Current work includes extensions to Markov Perfect Industry Dynamics and aggregate shock modeling.

Yongjie Jessica ZhangView profile

Professor

• Finite Element Method
• Isogeometric Analysis
• Image-Based Geometric Modeling
• +5 more

Dr. Yongjie Jessica Zhang is a Professor at Carnegie Mellon University, holding appointments in both the Department of Mechanical Engineering and the Department of Biomedical Engineering . She received her B.S. and M.S. in Engineering Mechanics from Tsinghua University, followed by an M.S. in Aerospace Engineering and a Ph.D. in Computational Engineering and Sciences from the University of Texas at Austin. After a postdoctoral fellowship at ICES, she joined CMU in 2007, advancing from assistant to full professor by 2016. Research Interests : Image-based geometric modeling, mesh generation, finite element analysis (FEA), isogeometric analysis, and applications in computational biomedicine, materials science, and computer-assisted surgery. Leadership Roles : Chair of Solid Modeling Association (2019-2020), USACM Executive Committee Member-at-Large (2017-2021), and ELATE Fellow (2017-2018). Her work addresses the critical challenge of automating high-fidelity geometric modeling and mesh generation for complex domains (e.g., human anatomy), which traditionally consumes ~80% of FEA time. Her group develops AI-driven methods for multiscale modeling (molecular to organ), with applications in neuroscience , biomechanics , and 4D printing . Notable awards include the Presidential Early Career Award (PECASE) , NSF CAREER Award , and ASME Van C. Mow Medal (2025) . Dr. Zhang’s publications span over 170 peer-reviewed articles, focusing on truncated hierarchical B-splines , polycube meshing , and neurite transport modeling . She has advised more than 40 students, including PhD candidates and postdoctoral fellows. Her editorial roles include Associate Editor of Computer Aided Geometric Design and editorial board memberships in Computer-Aided Design and Engineering with Computers .

Aayush JainView profile

Assistant Professor

• Cryptography
• Theoretical Computer Science
• Applied Cryptography
• +3 more

Aayush Jain is an Assistant Professor in the Computer Science Department at Carnegie Mellon University. Previously, he was a Postdoctoral Fellow at NTT Research and a PhD student at UCLA, advised by Professor Amit Sahai. His work bridges theoretical and applied cryptography with core computer science principles. Education PhD in Computer Science, University of California, Los Angeles (UCLA) Postdoctoral Fellowship, NTT Research Research Focus His research explores: foundational cryptography, indistinguishability obfuscation, functional encryption, lattice-based cryptography, secure multi-party computation, and post-quantum security. Work emphasizes rigorous theoretical frameworks with practical implications. Publication Trends Recent articles (2021-2024) demonstrate consistent focus on cryptographic primitives, obfuscation techniques, and security reductions. Dominant venues include CRYPTO, EUROCRYPT, FOCS, and STOC with emerging work in machine learning interfaces. Awards Best Paper Award at STOC 2021 for foundational contributions to indistinguishability obfuscation Advising and Collaboration Current PhD advisees: Alper Cakan, Quang Dao (co-advised), Sagnik Saha, Noah Singer (co-advised). Mentored postdocs: Mitali Bafna (2022-2023) and Rex Fernando (2022-2023). Teaches graduate courses in cryptography and theoretical tools. Leadership Leads the CMU Cryptography research group; organized the CMU Cryptography Workshop. Program committee member for FOCS, TCC, ITCS, and ICALP.

• Climate Change
• Environmental Hydrology
• Extreme Rainfall Patterns
• +3 more

Dr Conrad Wasko is a Sydney Horizon Fellow at the University of Sydney and an honorary fellow at the University of Melbourne. He specializes in environmental hydrology and climate change impacts on extreme rainfall and flooding. His work has been cited by the IPCC and he co-leads the update to Australia’s flood estimation guidelines. Previously, he held an ARC DECRA Fellowship and a McKenzie Fellowship. He has published over 50 articles and received awards including the Batterham Medal (2023) and the MSSANZ Early Career Research Excellence Award (2019). His research focuses on quantifying climate-driven changes in rainfall patterns and flood risks, with applications to infrastructure resilience and policy. Education: PhD in Civil Engineering, UNSW Sydney (2016) Bachelor/Master’s qualifications (not explicitly stated in text) Key Roles: Member of The Net Zero Institute Editor of Journal of Hydrology X and Advances in Water Resources Hydroclimate Stream Leader, Modelling and Simulation Society of Australia and New Zealand His research emphasizes the intensification of extreme rainfall events with global warming, particularly their implications for flood risk and urban infrastructure. He uses advanced statistical models and climate data to project future flood scenarios and improve design standards. Recent work includes analyzing non-stationary rainfall patterns and improving flood frequency analysis techniques. Awards and Honors: Batterham Medal (Australian Academy of Technological Sciences and Engineering, 2023) Veski Victoria Fellow (2020) MSSANZ Early Career Research Excellence Award (2019) Lorenz G Straub Award (2016) Grants and Projects: ARC DECRA Fellowship (University of Melbourne) Contributions to national climate change adaptation frameworks Labs and Collaborations: Partnerships with the Water Research Centre (UNSW) and the Net Zero Institute Collaborations on global flood risk assessments and hydrological modeling tools

Brian FrederkingView profile

Professor

• International Relations
• United Nations Security Council
• Collective Security
• +4 more

Brian Frederking is a Professor of Political Science at McKendree University, where he has held positions since 1990. He earned his Ph.D. from Syracuse University (1997), with earlier degrees from the same institution (M.A., 1993) and McKendree College (B.A., 1990). His research focuses on international organizations, collective security, conflict resolution, and foreign policy, with a particular emphasis on the United Nations Security Council and post-Cold War dynamics. Frederking has authored or co-authored multiple books, including Renegotiating the Liberal Order: Evidence from the UN Security Council (2023) and The United States and the Security Council: Collective Security since the Cold War (2007). His scholarly work bridges constructivist theory with empirical analysis of diplomatic discourse, security dilemmas, and international norms. He frequently collaborates with undergraduate students in research, including co-authored articles on nuclear proliferation and conflict resolution. His recent academic contributions include analyses of the Israel-Hamas conflict, transitional justice mechanisms, and the legitimacy of UN Security Council actions. Frederking has also engaged in public commentary through radio appearances on topics like the Iraq War and Middle East conflicts. He serves as editor of the Illinois Political Science Review and reviewer for numerous journals, reflecting his leadership in the field. Frederking advises McKendree's Model United Nations and Scholars journal, emphasizing experiential learning. His research datasets, such as the Collective Security Dataset, offer empirical tools for studying global governance. Despite no explicit mention of grants or labs, his work demonstrates sustained engagement with international political challenges.

Misa FaezipourView profile

Associate Professor

• System Dynamics Modeling
• Healthcare Systems Engineering
• Complex Systems Modeling
• +3 more

Dr. Misa Faezipour is an Associate Professor in the Department of Engineering Technology at Middle Tennessee State University (MTSU) and director of the Systems Engineering Lab (SEL). She holds a Ph.D. and M.Sc. in Industrial Engineering and Engineering Management from the University of Texas at Arlington and a B.Sc. in Software Engineering from Islamic Azad University North Tehran Branch. Her research focuses on system dynamics modeling, healthcare systems engineering, complex systems, and sustainability optimization. Dr. Faezipour has advised numerous graduate students in M.S. and Ph.D. programs, focusing on topics such as healthcare disparities, AI robustness, and policy impact analysis. She teaches courses including Engineering Economy, Operations Management, and Engineering Management Systems. Her work spans collaborations with institutions like NASA, the Systems Engineering Research Center, and healthcare organizations. Her recent publications emphasize AI-driven healthcare solutions, system dynamics applications in policy analysis, and optimizing healthcare delivery through data-driven models. She actively contributes to professional organizations such as INCOSE, IEEE, and the System Dynamics Society. Dr. Faezipour’s lab, SEL, develops innovative tools for healthcare informatics, including diagnostic recommenders and policy simulation frameworks. Her research bridges systems engineering with healthcare challenges, addressing issues like racial health inequities and pandemic response strategies.