Find Academic Supervisors

• Meteorology
• Climatology
• Numerical Weather Prediction
• +4 more

Piet Termonia is an Associate Professor at Ghent University in the Department of Physics and Astronomy within the Faculty of Sciences. His work focuses on meteorology, climatology, and numerical weather prediction systems with strong connections to the Royal Meteorological Institute of Belgium. Termonia's research interests include: Numerical Weather Prediction and Climate Modeling Regional Climate Downscaling Urban Climate Modeling Atmospheric Dispersion Modeling Extreme Weather Events Analysis Climate Services Development His research spans both theoretical meteorological development and practical applications for climate adaptation. Termonia has made significant contributions to the ALARO model used in the EURO-CORDEX framework for regional climate modeling across Europe. His work addresses critical challenges in representing extreme weather events, urban climate effects, and developing reliable climate services for policymakers and stakeholders. Termonia has supervised numerous PhD students in climate science, including Wenqiang Zhang (2024), Michiel Van Ginderachter (2023), and Fengqi Cui (2023). He leads research on climate extremes, particularly flood-drought transitions, precipitation modeling, and the application of machine learning in weather forecasting systems. As a key contributor to the CORDEX.be initiative, Termonia has helped establish Belgium's foundation for climate services. His collaborative work extends across European institutions, with frequent co-authorship with Rafiq Hamdi, Bert Van Schaeybroeck, and Steven Caluwaerts on projects related to urban climate modeling, extreme events, and climate change impacts.

Les NorfordView profile

Professor

• Building Energy Efficiency
• Urban Climate
• HVAC Systems
• +6 more

Les Norford is a Professor at MIT’s Department of Architecture, specializing in sustainable building design, energy efficiency, and urban climate studies. He holds academic appointments since 1988 and served as Associate Head of the Department of Architecture from 2006. His research integrates building system diagnostics, HVAC optimization, and urban heat island mitigation, with notable contributions to non-intrusive load monitoring (NILM) and thermal comfort modeling. Education: BS in Engineering Science (Cornell University, 1973); PhD in Mechanical & Aerospace Engineering (Princeton University, 1984) Professional Experience: Former nuclear engineer (US Navy/DOE), lecturer at Princeton, consultant with Tabors Caramanis & Associates Labs/Initiatives: Director of Singapore-MIT Alliance for Research and Technology (SMART)’s Center for Environmental Sensing and Modeling (CENSAM) Research interests include energy-efficient building operations, climate-responsive architecture, and smart grid technologies. His work addresses challenges in tropical urban environments, cooling system innovation, and decarbonized energy infrastructure. Collaborations with institutions like Lawrence Berkeley National Lab and Montana State University highlight his interdisciplinary approach. Notable projects include developing NILM systems for real-time energy monitoring and creating urban microclimate models (e.g., WRF-based simulations for Singapore). He advocates for data-driven approaches to improve building controls and reduce operational carbon footprints.

• Molecular Dynamics
• Condensed Matter Physics
• Biophysics
• +3 more

Raffaello Potestio is an Associate Professor in the Department of Physics at the University of Trento and serves as Coordinator of the Doctoral Course in Physics. His research focuses on molecular dynamics, soft matter physics, and computational modeling of biological systems. He teaches courses such as Physics 2 (electromagnetism fundamentals), Multi-scale Methods in Soft Matter Physics, and Statistical Mechanics, emphasizing theoretical and computational approaches. His work integrates advanced simulation techniques, including adaptive resolution methods, to study complex systems like proteins, DNA, and viral capsids. He has contributed to tools like EXCOGITO for coarse-grained modeling and explored topics ranging from knot interactions in polymers to chromatin mechanics in diseases. His research bridges theoretical physics with applications in biophysics, materials science, and epidemiology. Education details are not explicitly provided in the text. His teaching activities span undergraduate and graduate levels, with a focus on equipping students with analytical and computational skills for modern physics challenges. His publications highlight contributions to multiscale modeling frameworks, protein dynamics, and data-driven analysis of mobility patterns during the pandemic. Collaborations involve interdisciplinary teams addressing both fundamental and applied questions in physics and biology. Labs and teams associated with his work include computational physics groups at the University of Trento, though specific lab names are not mentioned. His research emphasizes the development of novel algorithms and their application to diverse systems, reflecting a commitment to advancing both methodological and applied aspects of theoretical and computational physics.

Fabian UnruhView profile

Academic

• Nuclear Disarmament Verification
• Machine Learning
• Nuclear Archaeology
• +3 more

Fabian Unruh is a Doctoral Researcher at the Peace Research Institute Frankfurt (PRIF) , affiliated with the Cluster for Natural and Technical Science Arms Control Research (CNTR) . His work focuses on nuclear disarmament verification and machine learning applications in nuclear archaeology for reconstructing fissile material production histories. He previously held a postgraduate assistant role at RWTH Aachen University’s Nuclear Verification and Disarmament group (2023–2024), following academic achievements including a Master of Physics (2021–2023) and Bachelor of Physics (2018–2021) from RWTH Aachen. Research Interests include: Nuclear archaeology and verification methodologies AI/ML integration in arms control contexts Nonproliferation and nuclear security frameworks Policy implications of emerging technologies He actively participates in interdisciplinary initiatives such as the AMC Cross-Disciplinary Conference 2025 and the Princeton School on Science and Global Security , collaborating with networks like the PEACE Network (COST Action) and the Science for Nuclear Diplomacy research group. Fabian also contributes to public outreach, including the Book A Scientist event organized by the Leibniz Association.

Bijaya AcharyaView profile

Research Fellow

• nuclear theory
• predictive modeling
• uncertainty quantification
• +2 more

Bijaya Acharya is a Neutrino Theory Network Fellow at Oak Ridge National Laboratory (ORNL), where he conducts research in the Theoretical and Computational Physics Group within the Physics Division's Fundamental Nuclear and Particle Physics Section. His work bridges nuclear theory, computational physics, and data science to advance predictive modeling in nuclear systems. Dr. Acharya earned his Ph.D. in Physics and Astronomy from Ohio University in 2015, followed by postdoctoral research appointments at the University of Tennessee, Knoxville, and the University of Mainz in Germany. His academic trajectory reflects deep specialization in theoretical nuclear physics with international collaboration experience. His research focuses on nuclear theory , predictive modeling , uncertainty quantification , nuclear astrophysics , and machine-learning applications . He develops computational frameworks for ab initio nuclear structure calculations, particularly using chiral effective field theory and coupled-cluster methods, to model electroweak processes in nuclei. This work addresses critical challenges in neutrino physics, stellar nucleosynthesis, and nuclear reaction rates. Analysis of his 15 most recent publications reveals a strong trend toward integrating machine learning with nuclear theory to enhance uncertainty quantification and anomaly detection in electroweak processes. His research spans nuclear structure (e.g., 40 Ca, 48 Ca), few-body systems (deuteron, 11 Li), and astrophysical applications (solar fusion), demonstrating interdisciplinary innovation at the intersection of physics and computational science. Dr. Acharya has received these notable scientific awards: Neutrino Theory Network Fellowship (inaugural recipient) 2022 Few Body Systems Award for Young Professionals Funded by the competitive Neutrino Theory Network Fellowship, his research leverages ORNL's high-performance computing resources for large-scale nuclear simulations. He collaborates with national laboratories and academic institutions on projects related to neutrino-nucleus interactions, nuclear astrophysics, and fundamental symmetries, contributing to major initiatives like the NSAC long-range plan. His grant portfolio emphasizes theoretical development with practical applications in nuclear energy and astrophysics. As a core member of ORNL's Theoretical and Computational Physics Group, he contributes to cutting-edge research in nuclear theory while mentoring early-career scientists. The group's work focuses on advancing ab initio methods for nuclear structure and reactions, with strong ties to experimental programs at facilities like the Spallation Neutron Source.

Alexander WhiteheadView profile

Research Fellow

• Medical Imaging
• Image Reconstruction
• Survival Analysis
• +5 more

Alexander Whitehead serves as a Visiting Fellow in the Department of Computer Science and Informatics, focusing on advanced medical imaging research and software development for image reconstruction systems. His work bridges computational techniques with clinical applications in medical data analysis. His research interests center on medical imaging, particularly tomographic reconstruction and survival analysis methodologies. Whitehead develops open-source frameworks like STIR and SIRF that integrate machine learning for enhanced image processing, statistical modeling of medical data, and reproducible research environments. These tools address critical challenges in computational imaging and clinical data interpretation. Recent publications (2023-2024) reveal a concentrated effort on software infrastructure for medical imaging, including reconstruction frameworks, virtualization tools, and survival analysis models. Key themes include tomographic reconstruction optimization, reproducible research environments, and statistical modeling of censoring events in medical datasets. Scientific Awards: None documented in available materials. Advising and grant activities are not specified in current records, though collaborative software projects indicate extensive interdisciplinary teamwork across international institutions. Whitehead actively contributes to major collaborative initiatives including STIR (Software for Tomographic Image Reconstruction) and SIRF (Synergistic Image Reconstruction Framework), working within distributed teams of developers and researchers to advance medical imaging standards and computational methodologies.

• Experimental physics of fundamental interactions
• Electronic technologies for particle accelerators
• High-energy physics experiments
• +7 more

Alessandro Gabrielli is a Full Professor at the Department of Physics and Astronomy "Augusto Righi" at the University of Bologna, where he also serves as Coordinator of the PhD Course in Physics. His primary scientific discipline is PHYS-01/A Experimental physics of fundamental interactions and applications. He is affiliated with both the National Institute for Nuclear Physics (INFN) and CERN in Geneva. His research focuses on experimental physics, particularly electronic technologies applied to particle accelerators. His current research activities center on the ATLAS experiments at CERN in Geneva and DUNE in the United States. More recently, he has expanded his research interests to include cybersecurity, artificial intelligence, and quantum computing, aligning with new international research initiatives in applied physics. Professor Gabrielli has been engaged in numerous national and international research projects, collaborating extensively with the National Institute for Nuclear Physics. He has coordinated multiple experimental research activities and authored over 1,000 publications in international peer-reviewed journals. His H-Index is 116 (SCOPUS, February 2025). His scientific recognition includes serving as Editor in Chief for MDPI Journals: Electronics since 2021, Guest Editor for special issues on Microelectronics in 2023, and Editor of Frontiers in Detector Science and Technology. He has also served as a reviewer for the Dutch Research Council (NWO) for a grant of €280,000. In terms of academic guidance, he has supervised 6 PhD theses in Physics, 1 PhD thesis in Data Science and Computation, and 14 Master's theses in Physics at the University of Bologna. His research has been supported by multiple grants, including a PRIN 2022 grant of 173k€ for "High performance microelectronics for low-noise cryogenic applications" and an AlmaIdea 2022 grant of 24,000€ for developing a Hardware Firewall. Professor Gabrielli is actively involved in international collaborations, having served as a "Visiting Scientist" at the Rutherford Appleton Laboratory in the UK (2009), "Visiting Professor" at the Center for Human Space Robotics at the Italian Institute of Technology (2012-2013), and "Project Associate" contractor at CERN (2008-2010). He currently coordinates the Bologna section of the INFN for the DUNE experiment and various ATLAS hardware activities.

• Scientific Visualization
• Data Visualization
• Computer Graphics
• +4 more

Pere Pau Vázquez Alcocer is an Associate Professor in the Department of Computer Science at Universitat Politècnica de Catalunya (UPC), affiliated with the ViRVIG research group and the School of Informatics (FIB). With a PhD in Software from UPC (2003), he specializes in Scientific Visualization , Data Visualization , and Virtual Reality applications. His work bridges Computer Graphics with Medical Data Visualization and Molecular Visualization , emphasizing AI applications to visualization . His research spans two decades, focusing on Interactive volume rendering VR-based biomedical analysis Perceptual optimization in visualizations Urban mobility data modeling with recent publications in Computer Graphics Forum , IEEE CG&A , and arXiv on AI-driven visualization frameworks and molecular interaction techniques. His 15 most recent publications (2025-2023) demonstrate trends in AI integration for data visualization, immersive analytics for biomedical applications, and optimization of rendering techniques on mobile and VR platforms, with keywords spanning Computer Science , Neuroscience , and Urban Planning . Awarded the Best PhD thesis (2003) and Best Paper at international conferences, he has supervised 8 PhD students including Pedro Hermosilla (now Assistant Professor at TU Wien) and Jesús Díaz (now Associate Professor at Universitat de Vic). Teaching for over 20 years at UPC across five schools, he currently leads courses in Data Visualization , Scientific Visualization , and Virtual Reality .

H. Akın ÜnverView profile

Associate Professor

• Conflict Research
• Computational Methods
• Digital Crisis Communication
• +7 more

H. Akın Ünver is an Associate Professor in the Department of International Relations at Ozyegin University, specializing in conflict research, computational methods, and digital crisis communication. He coordinates DE-CONSPIRATOR , a HorizonEU project involving 15 European institutions combating foreign information manipulation. He also serves as a fellow at the Carnegie Endowment's Digital Democracy Network and advises TikTok's MENA-T Security Advisory Council. PhD in Government, University of Essex (2010) Postdoctoral research: University of Michigan (2010-2012), Princeton University (2012-2014) Former Research Associate at Oxford University's Center for Technology and Global Affairs Senior Research Fellow at Alan Turing Institute's GUARD program His research spans conflict modeling , digital disinformation , and energy politics , with recent publications focusing on AI weaponization, LLM applications in social science, and technology's role in information warfare. He founded the Istanbul Twitter Developers' Community and organizes SICSS (Summer Institute in Computational Social Science) in Istanbul. Recent article trends highlight his work on: Computational approaches to diplomatic text analysis Geopolitical implications of AI trade Human rights impacts of authoritarian technologies Agent-based modeling of nonstate armed groups Automated fact-checking systems Scientific recognition includes: MESA Malcolm H. Kerr Award (2010) TÜBA Promising Scientist Award (2019) Alan Turing Institute Defense Modeling Award (2019) Society for Digital Diplomacy Best Article (2017) Oxford Cybersecurity Showcase Award (2017) He supervises research through Ozyegin's Cyber Research Program and contributes to institutions like EDAM think tank and Doğruluk Payı fact-checking initiative.

Andrew KennedyView profile

Professor

• Materials Science
• Additive Manufacturing
• Porous Materials
• +7 more

Professor Andrew Kennedy is the Chair in Advanced Manufacturing and Head of the Department of Engineering at Lancaster University . A graduate of Imperial College and Cambridge University, he previously held academic positions at Nottingham University. His research focuses on novel manufacturing methods for advanced materials, particularly multi-phase materials like metal matrix composites, metal foams, and porous materials, using techniques such as additive manufacturing, powder processing, and gel casting. Research Interests: Development of lightweight and energy-absorbing structures, novel batteries and energy storage systems, thermal/fluid flow management, and medical devices. Collaborations: Leads the TWI-Lancaster Joining 4.0 Centre and works with experts in AI, robotics, and machine learning to enhance manufacturing processes. Scientific Achievements: Published over 140 peer-reviewed papers, holds 2 patents, supervised 40+ PhD students, and led 65+ research projects including EU initiatives with 10+ industrial/academic partners. International Collaborations: Partnerships with institutions in Spain, Germany, Finland, Romania, Greece, Italy, Switzerland, China, Thailand, India, Malaysia, Mexico, Chile, Australia, and Canada.

Christopher D. JimenezView profile

Associate Professor

• Global Anglophone Literature
• Ecocriticism
• Nuclear Criticism
• +6 more

Christopher D. Jimenez is Associate Professor of English at Stetson University, specializing in 20th- and 21st-century global Anglophone literature with interdisciplinary expertise in ecocriticism, nuclear criticism, and digital humanities. His research examines how catastrophe discourse expands literary representation beyond national boundaries into global political and aesthetic forms. Education: PhD in English, University of Pennsylvania (2017) MA in English, University of Pennsylvania (2012) BA in English with distinction, University of Washington (2010) Jimenez's scholarship bridges literary catastrophe studies with digital methodologies. His book project "The Exploding Globe" analyzes how nuclear disasters and ecological crises reshape global literary aesthetics, informed by fieldwork in Hiroshima and Fukushima funded by a Penfield Research Fellowship. Concurrently, he pioneers computational approaches to literary analysis through digital humanities projects like the Contemporary Fiction Database. His publication trends reveal dual trajectories: literary studies of disaster narratives and digital humanities applications in education. Recent works integrate AI text generation for teaching cultural bias while maintaining core focus on postcolonial and ecocritical frameworks. Awards: Penfield Research Fellowship (2015) Andrew W. Mellon Price Lab Doctoral Fellowship in Digital Humanities (2016-2017) Jimenez directs significant research initiatives including the Contemporary Fiction Database Project with James F. English and secured funding for transnational nuclear disaster research. His teaching spans global literature, disaster fiction, computational humanities, and film noir, reflecting his interdisciplinary approach to literary studies and digital pedagogy. As an inaugural Mellon Fellow at Penn's Price Lab, he advanced digital scholarship through project incubation and seminars while developing methodologies for analyzing large-scale literary datasets and catastrophe narratives across cultural contexts.

Donna J. CrossView profile

Associate Professor

• Neuroimaging
• Neurodegenerative Disorders
• Traumatic Brain Injury
• +6 more

Donna J. Cross, PhD, serves as Research Associate Professor in the Department of Radiology & Imaging Sciences at the University of Utah, directing the NeuroImaging and Biotechnology Laboratory (NIBL). Her work pioneers neuroimaging applications to transform therapeutic and diagnostic approaches for neurological disorders and dementia through advanced techniques like MR-guided focused ultrasound and molecular imaging. Dr. Cross's academic foundation includes a PhD and BSE from the University of Michigan, senior fellowship training at the University of Washington, and additional studies at Michigan State University. Her educational journey established the groundwork for her innovative research in brain imaging and therapeutic development. Her research program spans neurodegenerative disorders, traumatic brain injury, and dementia, with emphasis on Alzheimer's disease mechanisms, spinal cord injury treatment via focused ultrasound, and intranasal drug delivery systems. NIBL's projects integrate molecular imaging, AI-driven analysis, and cross-species models to address critical gaps in neurological care. Recent publications demonstrate accelerating focus on AI-enhanced imaging biomarkers, avian cognition models for human brain function, and microtubule-stabilizing therapies for neurodegeneration. These works reveal growing interdisciplinary convergence between computational neuroscience, therapeutic delivery systems, and translational neurotrauma research. As 2022/2023 president of the SNMMI Brain Imaging Council and active NIH study section participant, Dr. Cross shapes national research priorities. Her laboratory receives funding from the International Atomic Energy Agency and Alzheimer's Association for multi-center dementia imaging and intranasal therapy development. NIBL operates as a multidisciplinary hub with faculty collaborators, lab technologists, and student researchers advancing seven core projects from brain mapping to traumatic injury therapeutics.

Rosemary KnightView profile

Professor

• Hydrogeophysics
• Groundwater Evaluation and Management
• Geophysical Imaging
• +3 more

Rosemary Knight is the George L. Harrington Professor of Geophysics at Stanford University (2000–Present) and a Senior Fellow at the Woods Institute for the Environment (2005–Present). She previously held faculty positions at the University of British Columbia (1988–2000). Her career spans over 35 years, with leadership roles in academic governance, professional societies, and interdisciplinary initiatives. Education: Ph.D. in Geophysics (Stanford, 1985), M.S. and B.S. in Geological Sciences (Queen's University, 1978 and 1976) Key Committees: Chair of Stanford Faculty Senate (2011–12), Director of NSF Hydrologic Measurement Facility (2003–08), Vice-President of Society of Exploration Geophysicists (2001–02) Rosemary pioneered the field of hydrogeophysics in 1985, focusing on non-invasive subsurface imaging for groundwater systems. Her work integrates geophysical methods (NMR, electromagnetic, resistivity) with remote sensing and machine learning to address groundwater sustainability. Current research emphasizes managed aquifer recharge , 3D hydrogeologic modeling , and field-scale rock-physics transforms . Recent publications highlight advancements in NMR logging for hydraulic conductivity estimation (2023), airborne electromagnetic imaging of groundwater systems (2022), and machine-learning rock-physics transforms (2022). These works span hydrology , environmental geophysics , and subsurface characterization . Scientific Awards Frank Frischknecht Award (2002) Life Membership, Society of Exploration Geophysicists (2009) Honorary Life Membership, SEG Near-Surface Geophysics Section (2012) Killam Research Prize (1996) Charles McDowell Medal (1996) Dr. Knight advises doctoral and master's students in groundwater-focused geophysics, leads Stanford's I-Earth educational initiative for planetary literacy, and maintains active collaborations with institutions like Aarhus University (HyGEM Project) and UC Berkeley. Her work bridges field experiments , laboratory research , and computer modeling to advance sustainable water management.

• Machine Learning
• Bioinformatics
• Computational Biology
• +7 more

Satwik Rajaram is an Assistant Professor at the Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center , with secondary appointments in the Department of Pathology and the Center for Alzheimer's and Neurodegenerative Diseases . His lab develops biology-guided machine learning approaches to study tissue morphology in kidney cancer and neurodegenerative diseases . Education : PhD in Theoretical Physics (University of Illinois at Urbana-Champaign) Postdoctoral Training : Joint labs of Drs. Altschuler and Wu (UTSW, then UCSF) Research Interests focus on leveraging tissue organization as a biomarker through: Kidney Cancer : Linking tumor architecture to molecular states and drug responses Neurodegeneration : Using tau protein aggregate morphology to refine disease taxonomy Radiation Oncology : Predicting treatment outcomes via histopathology analysis Deep Learning for Histopathology : Addressing challenges like image size and staining variability Publications highlight his work on intratumoral heterogeneity , machine learning for biomarker discovery , and quantitative microscopy , with applications spanning cancer evolution, tauopathies, and clinical pathology.

• Hyperspectral Imaging
• Machine Learning
• Image Processing
• +3 more

Raymond David Dunphy is a Research Assistant at the University of Strathclyde's Centre for Signal and Image Processing. He is completing his PhD on hyperspectral imaging for microbiological applications while contributing to interdisciplinary projects in nuclear and space industries. His work bridges machine learning with advanced imaging techniques. MEng in Computer and Electronic Systems (University of Strathclyde) PhD candidate in Hyperspectral Imaging (ongoing) His research focuses on developing machine learning tools for hyperspectral data analysis , with applications spanning nuclear fuel manufacturing, microbiology, and aerospace. Key projects include optimizing uranium hexafluoride conversion and enhancing quality assurance in UO₂ nuclear fuel pellet production. Current collaborations include industry partnerships with Terumo Aortic Limited and participation in the Interdisciplinary Centre for Doctoral Training in Antimicrobial Resistance (AMR). He actively contributes to UN Sustainable Development Goals through nuclear energy efficiency innovations.