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Dr. Raj Rajakumar is an Associate Professor at Western University's Department of Anatomy and Cell Biology, cross-appointed with the Department of Psychiatry. His work focuses on molecular mechanisms underlying schizophrenia symptoms and autism neurobiology, employing animal models to study drug effects and neural signaling. He holds a PhD from the University of Western Ontario, with prior degrees in M.B.B.S. (University of Peradeniya) and M.Sc. (University of Western Ontario). Educations: Ph.D., Anatomy and Cell Biology, University of Western Ontario M.Sc., Anatomy and Cell Biology, University of Western Ontario M.B.B.S., Medicine, University of Peradeniya Research Interests: Molecular pathways in schizophrenia symptom manifestation Neurobiological basis of autism spectrum disorders Pharmacological interventions using antipsychotics and psychotropic drugs Neuroimaging techniques (fMRI, MRS) to study brain connectivity His research combines molecular biology, neuroanatomy, and behavioral assays in animal models to explore schizophrenia pathophysiology. Recent work includes maternal immune activation effects on fetal brain development, cannabinoid impact on executive function, and white matter inflammation in Alzheimer's models. Collaborations with Dr. W.J. Rushlow and others highlight translational research in neuropsychiatric disorders. Key contributions include automated MRI algorithms for medial temporal lobe analysis and longitudinal studies of glutamatergic deficits in schizophrenia. His work bridges basic science with clinical applications in mental health. Dr. Rajakumar's lab focuses on understanding brain circuitry disruptions in psychiatric disorders, with implications for novel therapeutic targets. No formal advisees are listed, but his research team actively engages in interdisciplinary collaborations.

• Molecular Neuroscience
• Schizophrenia Mechanisms
• Autism Neurobiology
• +3 more

Dr. Zichun Zhong is an Associate Professor and Graduate Program Director in the Department of Computer Science at Wayne State University's James and Patricia Anderson College of Engineering. He earned his Ph.D. from the University of Texas at Dallas and completed postdoctoral training at UT Southwestern Medical Center. His research focuses on geometric modeling, computer graphics, medical image processing, and visualization technologies. Research encompasses: Geometric modeling of surfaces and volumes 3D computer vision and reconstruction Medical image segmentation and visualization Virtual/augmented reality applications GPU-accelerated algorithms Awards and honors include NSF CAREER and CRII awards, Faculty Research Excellence Award, and Excellence in Teaching recognition. He serves as Technical Paper Chair for Shape Modeling International conferences and associate editor for multiple journals. Current doctoral advisees: Shiman Zhou, Hongbo Li, Haikuan Zhu, and Sikai Zhong. Notable alumni include researchers at Samsung NEON, Skoltech, and General Motors.

• Geometric Modeling
• Computer Graphics
• 3D Computer Vision
• +5 more

Ellen Currano is Professor of Paleobotany in the Department of Geology and Geophysics at the University of Wyoming. Her research integrates fossil plants, insect herbivory, and paleoenvironmental proxies to understand how ancient forest ecosystems responded to climate perturbations, with field projects spanning Wyoming’s Paleogene strata and East Africa’s Miocene basins. She teaches courses in paleobotany, paleoecology, and paleoclimatology and is co-founder of The Bearded Lady Project , a science-outreach documentary initiative. Education Ph.D., Pennsylvania State University, 2008 B.S., University of Chicago, 2003 Research Interests Currano’s work centers on reconstructing ancient forest ecosystems using fossil plants and their insect-mediated damage. She investigates how taxonomic diversity, ecosystem structure, plant–insect interactions, and biogeographic patterns shifted during past global warming events. Her current projects include: Biotic responses to Paleogene hothouse climates across the Western US, especially Wyoming. Evolution of East African terrestrial ecosystems over the last 30 million years. Fossil-plant proxies for paleoclimate and paleoenvironmental reconstruction. Scientific Awards Paleontological Society Medal, 2021 Teaching & Mentoring Currano emphasizes active, process-based learning and critical thinking in her courses on paleobotany, paleoecology, and paleoclimatology. Leveraging Wyoming’s world-class fossil exposures, she mentors both undergraduate and graduate students in independent research. Outreach & Leadership She co-founded The Bearded Lady Project: Challenging the Face of Science , a documentary film and photography campaign that confronts stereotypes surrounding women in field sciences.

• Paleobotany
• Paleoecology
• Paleoclimatology
• +2 more

Ibrahim RADWAN is an Associate Professor in Machine Learning/AI and Robotics at the University of Canberra. His research focuses on advancing AI techniques in areas such as human pose estimation, affective computing, and healthcare technology. He leads projects addressing challenges in robotics, autonomous systems, and human behavior analysis. RADWAN’s work bridges theory and application, contributing to fields like sports science, medical diagnostics, and security through innovative machine learning approaches. Research Projects: Assistive Technologies for Young People Safety on Two-Wheelers AI-Based Methods for Driver Sentiment and Mood Prediction Robotics Applications in Organic Waste Management Research Interests: RADWAN’s expertise spans human pose reconstruction , nonverbal behavior analysis , and EEG-based healthcare diagnostics . He pioneers methods for real-world applications such as: 6G Extended Reality systems using wearable sensors Multimodal deception detection via motion analysis Affective computing for mood and emotion inference Publications: His recent work emphasizes trends in spatiotemporal data analysis, few-shot learning, and synthetic data applications in healthcare and robotics. Key contributions include novel architectures like CrossFormer for 3D pose estimation and Resanet for dense prediction tasks. Advising & Grants: RADWAN supervises PhD students and has secured grants for projects integrating AI with robotics and medical technology. His team collaborates on interdisciplinary challenges, including railway safety and surgical instrument tracking. Labs/Teams: Part of the AI and Robotics research group at the University of Canberra, contributing to cutting-edge solutions in autonomous systems and human-centered AI.

• Machine Learning
• AI
• Computer Vision
• +9 more

Alina Roitberg is a Junior Professor (Assistant Professor) at the University of Stuttgart , affiliated with the Faculty of Computer Science, Electrical Engineering and Information Technology . Her research focuses on advancing computer vision, machine learning, and robotics applications, particularly in human activity recognition, domain adaptation, and synthetic data generation. She explores challenges in action understanding, cross-domain generalization, and real-world deployment of AI systems in fields like healthcare, autonomous vehicles, and industrial automation. Her work emphasizes robust learning under noisy conditions, multimodal data fusion, and ethical AI applications. Recent projects include foundational studies on large language models in construction (AEC), video-based muscle group estimation, and improving driver activity recognition for autonomous vehicles. She also investigates circular factory design through uncertainty-aware process optimization and human-robot interaction. Dr. Roitberg's contributions span academic publications and industrial collaborations, addressing both theoretical advancements and practical implementations. Her research bridges computer vision techniques with real-world problems, emphasizing scalability and ethical considerations in AI deployment.

• Computer Vision
• Machine Learning
• Human Activity Recognition
• +7 more

Prof. Christian Liebscher is a Professor of Advanced Transmission Electron Microscopy at the Ruhr University Bochum , affiliated with the Faculty of Physics and Astronomy and the Research Center Future Energy Materials and Systems (RC FEMS). His work focuses on developing cutting-edge TEM techniques to understand energy-related materials' atomic-scale structure-functionality relationships. He combines aberration-corrected scanning TEM (STEM), 4D-STEM, and in-situ microscopy with machine learning to analyze complex material datasets. Education and Career: 2000–2006: Study of Materials Science at the University of Bayreuth. 2006–2010: PhD at the University of Bayreuth (summa cum laude) with a thesis on phase and dislocation analysis in superalloys. 2011–2014: Postdoc at the University of California, Berkeley, and the National Center for Electron Microscopy (Lawrence Berkeley National Laboratory). 2014–2015: Staff scientist at the University of Duisburg-Essen. 2015–2024: Group leader at the Max Planck Institute for Sustainable Materials in Düsseldorf. Research Interests: Prof. Liebscher’s research bridges microscopy innovation and materials understanding. He emphasizes atomic-scale characterization of interfaces, defects, and grain boundaries in metals and alloys using advanced STEM and 4D-STEM. His work addresses how structural features—like segregation, strain, and phase transitions—impact material properties. He also pioneers machine learning tools to automate data analysis from microscopy and tomography, advancing materials dataspaces. Key topics include energy materials (e.g., PEM fuel cells), high-entropy alloys, and nanomaterials for applications like semiconductors and electromagnetic absorption. Scientific Contributions: His publications highlight trends in grain boundary phase transitions, microstructure-property correlations, and integration of AI into microscopy. For example, recent work explores how grain boundary complexions affect mechanical strength in alloys and how in-situ TEM reveals deformation mechanisms under realistic conditions. He has contributed significantly to methodologies like scanning precession electron diffraction tomography and unsupervised machine learning for atomic-resolution datasets. Labs and Collaborations: Prof. Liebscher leads the Advanced Transmission Electron Microscopy group at RUB, building on his previous leadership at the Max Planck Institute. His lab collaborates with institutions like the Lawrence Berkeley National Laboratory and integrates interdisciplinary approaches combining experimental microscopy with computational modeling.

• Advanced Transmission Electron Microscopy
• Materials Science
• Energy-Related Materials
• +6 more

Roland N. Horne is the Thomas Davies Barrow Professor of Earth Sciences at Stanford University and Senior Fellow at the Precourt Institute for Energy. He holds positions in the Department of Energy Science & Engineering and is an Affiliate at the Stanford Woods Institute for the Environment. With degrees from the University of Auckland (BE, PhD, DSc), Horne has established himself as a leading expert in geothermal reservoir engineering and energy production optimization. His research focuses on inverse problems in reservoir modeling, including tracer analysis of fractures, computer-aided well test analysis, production schedule optimization, and automated history matching. Horne has made significant contributions to understanding geothermal reservoir engineering and multiphase flow of boiling fluids through porous materials and fractures. The analysis of his recent publications (2023-2025) reveals a strong emphasis on enhanced geothermal systems (EGS), with particular focus on flexible operations, economic modeling, and advanced characterization techniques. His work increasingly incorporates machine learning approaches for reservoir analysis and has expanded into microbial tracing methods for interwell connectivity assessment. There's also significant attention to US geothermal resource potential and integration into the broader energy transition. Honorary Member of the Society of Petroleum Engineers Member of the US National Academy of Engineering Multiple SPE Distinguished Lecturer appointments (1998, 2009, 2020) John Franklin Carl Award recipient Five Best Paper awards from Geothermal Resources Council Patricius Medal from German Geothermal Society Core Values Award from Women in Geothermal (2023) Horne has supervised 60 PhD and 135 MS students throughout his career. His current teaching includes undergraduate and graduate courses in Fundamentals of Energy Processes, Geothermal Reservoir Engineering, Mass and Energy Transport in Porous Media, and Well Test Analysis. He previously served as President of the International Geothermal Association (2010-2013) and Technical Program Chair for multiple World Geothermal Congress events. Horne maintains active research collaborations worldwide, including with the University of Tokyo (where he was a Fellow of the School of Engineering in 2016) and China University of Petroleum. His current research group focuses on advancing EGS technologies and developing more accurate reservoir characterization methods for geothermal applications.

• Geothermal reservoir engineering
• Energy production optimization
• Well test interpretation
• +8 more

Professor Daniel Davis MBE FMedSci is the Head of the Department of Life Sciences and Professor of Immunology at Imperial College London. He holds affiliations with the Institute of Chemical Biology, the CDT in Chemical Biology: Innovation in Life Sciences (as a supervisor), and research groups in Immunology and Molecular Mechanisms of Disease. His academic journey includes a doctorate in Physics from Harvard University and prior roles as Director of Research at the Manchester Collaborative Centre for Inflammation Research (University of Manchester). His research focuses on nanoscale biology of immune cell interactions, employing advanced microscopy techniques to study immune synapse formation, cytotoxicity mechanisms, and immunological regulation. Notable contributions include elucidating how immune cells use adhesion, signaling, and structural reorganization to target pathogens and cancer cells. Professor Davis has authored four popular science books, including Self Defence: A Myth-Busting Guide to Immune Health (2025), The Beautiful Cure (2018), and The Compatibility Gene (2014), which bridge public understanding of immunology and biology. His work has been recognized with prestigious awards such as the Royal Society Science Book Prize and the Prose Award. His articles span topics like NK cell heterogeneity, gene therapy for neurological disorders, and super-resolution microscopy applications. Grants and collaborations include work on AAV-based gene therapies and immunomodulatory drug development. Davis actively engages in public science communication through festivals, media outlets (e.g., BBC, Guardian), and international speaking engagements. His research labs at Imperial College focus on interdisciplinary approaches, combining biophysics, genetics, and clinical applications to advance immunology and translational medicine.

• Immunology
• Biochemistry and Cell Biology
• Clinical Sciences
• +3 more

Elliot Hui, Ph.D., is an Associate Professor in the Department of Biomedical Engineering at the University of California, Irvine (UCI), within the Samueli School of Engineering. His research focuses on biological microtechnology, including spatial cell biology, microscale tissue engineering, global health diagnostics, and microfluidic computing. He leads the Hui Lab, which develops tools for automating biochemical reactions, controlling cellular organization, and understanding tissue development dynamics. Key achievements include pioneering microfluidic logic systems for autonomous laboratory automation and creating novel cell culture platforms to study intercellular communication in tissues. His work bridges engineering and biology, addressing challenges in diagnostics and regenerative medicine. Notable contributions include the development of a programmable finite state machine for microfluidic control and a SLAS Fellowship awarded to his student Erik. Research Interests: Microfluidic devices, cell-cell interaction modeling, tissue engineering, and lab-on-a-chip systems. Labs/Teams: Hui Lab at UCI, specializing in microscale biological systems and automation. Publications span topics such as microfluidic computing architectures, tissue dissociation devices, and Bayesian experimental design. His work emphasizes applications in global health diagnostics and mechanistic studies of cellular processes.

• Biomedical Engineering
• Microfluidics
• Spatial Cell Biology
• +3 more

Naratip Santitissadeekorn is a Senior Lecturer in Data Assimilation at the School of Mathematics and Physics, University of Surrey, where he is affiliated with the Mathematics at the Interface Group. His work bridges mathematics, data science, and real-world applications in urban planning, crime analysis, and geophysical fluid dynamics. Dr. Santitissadeekorn received his PhD from Clarkson University in 2008, with a dissertation titled "Transport Analysis and Motion Estimation of Dynamical Systems of Time-Series data." His doctoral research was supervised by Professor Erik Bollt. Following his PhD, he completed two significant postdoctoral positions: from 2008-2011 at the University of New South Wales, Sydney, Australia, working with Professor Gary Froyland on numerical techniques for finite-time Lagrangian coherent set identification, with applications to delimiting the polar vortex and Agulhas rings; and from 2011-2014 at the University of North Carolina-Chapel Hill, working with Professor Chris Jones on data assimilation projects. Dr. Santitissadeekorn's research focuses on inverse problems and data assimilation in geophysical fluid dynamics, the applications of Lagrangian Coherent Structures (LCS), and computational ergodic theory. His work combines theoretical mathematics with practical applications, particularly in urban growth modeling and crime analysis. He has developed innovative methods for identifying coherent structures in fluid flows, estimating transition probabilities from spatiotemporal data, and creating data-driven frameworks for urban expansion scenarios. His research demonstrates how mathematical techniques can be applied to solve real-world problems in environmental science, urban planning, and public safety. An analysis of Dr. Santitissadeekorn's recent publications (2020-2023) reveals a strong focus on urban expansion modeling and network analysis. His work on urban growth has evolved from basic cellular automata models to sophisticated frameworks that manage uncertainty through parameter clustering and growth mode identification. His research on Hawkes processes has advanced ensemble-based filtering techniques for analyzing count data in large networks. These publications demonstrate a consistent pattern of applying mathematical rigor to complex spatiotemporal phenomena, with increasing emphasis on data-driven approaches and practical applications. Dr. Santitissadeekorn has made significant contributions to data assimilation methods, particularly through the development of the extended Poisson-Kalman filter (ExPKF) for urban crime modeling. His teaching includes courses in Algebra and Bayesian Statistics, reflecting his expertise in both theoretical and applied mathematics. While specific awards are not mentioned in the available information, his extensive publication record in high-impact journals demonstrates recognition within his field. Dr. Santitissadeekorn's research has practical implications for urban planning and law enforcement. His work on urban expansion models helps planners understand different growth trajectories, while his crime modeling research contributes to improved police patrolling strategies. His interdisciplinary approach, combining mathematics, computer science, and domain-specific knowledge, positions him at the forefront of applying data science to societal challenges.

• Data Assimilation
• Inverse Problems
• Geophysical Fluid Dynamics
• +5 more

Professor Adrian Hilton is a distinguished faculty member at the University of Surrey, serving as Director of the Centre for Vision, Speech and Signal Processing (CVSSP) and Director of the Surrey Institute for People-Centred AI. He is affiliated with the School of Computer Science and Electronic Engineering and leads the Visual Media Research Lab (V-Lab). His research focuses on pioneering next-generation 4D computer vision technologies that enable machines to understand and model dynamic real-world scenes. Key areas include 3D/4D shape capture, computer vision, machine learning, graphics, and animation for applications in sports analysis, film/TV production, virtual reality, and medical imaging. His work bridges the gap between real and computer-generated imagery, with notable contributions in volumetric capture, motion capture, and free-viewpoint video. Hilton's recent publications demonstrate a strong trend toward multimodal integration, particularly combining audio and visual processing for spatial audio applications, while advancing 4D reconstruction techniques for human performance capture. His work increasingly incorporates transformer architectures and neural rendering techniques for improved illumination estimation, shadow modeling, and multi-view consistency. Scientific Awards and Recognition Two EU IST Innovation Prizes Manufacturing Industry Achievement Award Royal Society Industry Fellowship (2008-2011) Royal Society Wolfson Research Merit Award in 4D Vision (2013-2018) Fellow of the Royal Academy of Engineering (FREng) Fellow of the International Association for Pattern Recognition (FIAPR) Fellow of the Institution of Engineering and Technology (FIET) Hilton actively mentors PhD and post-doctoral researchers through his leadership of CVSSP, which has a grant portfolio exceeding £31M and comprises 170 researchers. He has successfully commercialized several technologies, including systems used by the BBC for sports commentary visualization. His research collaborations span major industry partners including BBC, BT, Sony, Framestore, and The Foundry. He co-founded the G3 Games forum and the CVMP Conference on Visual Media Production, demonstrating strong engagement with the creative industries. Current research projects include the S3A Programme Grant in Future Spatial Audio and InnovateUK's ALIVE project for 360 video reconstruction.

• Computer Vision
• 4D Vision
• Machine Learning
• +9 more

David Fouhey is an Assistant Professor at New York University, jointly appointed between the Courant Institute of Mathematical Sciences (Computer Science) and the Tandon School of Engineering (Electrical and Computer Engineering). He previously held positions at the University of Michigan and was a postdoctoral researcher at UC Berkeley. His research focuses on learning-based computer vision, particularly in 3D reconstruction, AI for science, and human-object interaction. Education: PhD in Robotics from Carnegie Mellon University (2013-2018) Bachelor of Arts in Computer Science from Middlebury College (2007-2011) Research Interests: His work spans 3D reconstruction from images , AI-driven scientific measurement (e.g., solar physics, evolutionary ecology), and human interaction modeling . Notable projects include Stereo4D for 3D motion analysis and SyntheticIA for solar magnetogram fusion. Recent Articles: Recent work emphasizes interdisciplinary applications of vision (e.g., bird morphology analysis) and robust 3D techniques like Perspective Fields for camera calibration. His 2025 Nature Scientific Data paper on bird skeletal traits highlights his AI-for-science focus. Grants & Collaborations: Secured a NASA grant for heliophysics tools and collaborates with institutions like NASA’s SDO mission and the Astrophysical Journal. Labs & Teams: Leads a NYU research group focused on vision and robotics, with active collaborations in astrophysics and ecology.

• Computer Vision
• Machine Learning
• AI for Science
• +6 more

Christian Jacob is a Professor in the Department of Computer Science within the Faculty of Science at the University of Calgary . He holds a B.S. in Computer Science and a Doctor of Engineering Science from Erlangen University . His research focuses on nature-inspired algorithms, biocomputing, and agent-based simulations applied to biological systems and education. Key initiatives include the LINDSAY Virtual Human Project , which uses immersive virtual reality to explore human anatomy and physiology. He contributes to the university's strategic priorities in Digital Worlds and Health and Life initiatives. His work integrates evolutionary algorithms, cellular automata, and swarm intelligence into creative and medical applications. Notable achievements include the ASTech Award (2015) from Alberta Science and Technology. His projects emphasize interactive education through tools like LeukemiaSIM , Eukaryo , and the Giant Walkthrough Gut . Jacob also explores visualization techniques, such as evoVision3D and LifeBrush , to enhance scientific understanding. His research bridges computational methods with real-world applications in healthcare, architecture, and game design. Collaborative efforts include developing agent-based models for immune systems, nervous responses, and crowd behavior. Jacob's work spans interdisciplinary fields, blending computer science with biology, engineering, and the arts.

• Algorithms gleaned from nature
• Biocomputing
• Bioinformatics
• +6 more

Robin S. Matoza is a Professor in the Department of Earth Science at the University of California, Santa Barbara (UCSB). His research focuses on volcano seismology, acoustics, and infrasound, with particular emphasis on understanding volcanic processes through seismic and infrasound data. He leads studies on volcanic eruption dynamics, infrasound propagation, and the application of seismoacoustic methods for hazard mitigation. Roles: Professor, Principal Investigator Affiliations: Department of Earth Science, Earth Research Institute, UCSB Research interests include volcano acoustics, infrasound source characterization, and the development of infrasound monitoring tools. He has contributed to global volcanic eruption detection systems, such as the IMS_VASC software for automated volcanic infrasound cataloging. His work integrates field data from volcanoes like Tungurahua (Ecuador), Yasur (Vanuatu), and Kīlauea (Hawaii) with computational modeling. Key projects include studying infrasonic signals from explosive eruptions, submarine volcanic activity, and the interaction between volcanic processes and atmospheric dynamics. He collaborates on international initiatives like the International Monitoring System (IMS) for nuclear treaty verification and volcanic monitoring.

• Volcanology
• Seismology
• Infrasound
• +3 more

Hazem U. Abdelhady is a Postdoctoral Research Fellow at the University of Michigan's School for Environment and Sustainability (SEAS), jointly appointed with the Cooperative Institute for Great Lakes Research (CIGLR). He will join Texas A&M University's Department of Geography as an Assistant Professor in Fall 2025. His research focuses on coastal and hydrodynamic processes, leveraging machine learning, remote sensing, and physics-based modeling to address climate-driven challenges in lakes and coastal systems. Dr. Abdelhady holds a PhD from Purdue University in Hydraulics and Hydrology Engineering and Computational Engineering (2024), an MS in Irrigation and Hydraulics Engineering from Cairo University (2020), and a BS in Civil Engineering (2018). His postgraduate certificate in Geospatial Information Sciences underscores his expertise in spatial data analysis. His research interests include coastal hydrodynamics, physical limnology, and AI-driven environmental modeling. Key projects involve understanding shoreline changes in Lake Michigan, predicting ice cover dynamics, and developing tools for climate adaptation. The Aggie CIS Lab , launching at Texas A&M in Fall 2025, will further advance these efforts, bridging disciplines to enhance coastal resilience. Recent work highlights include studies on climate impacts on lake temperatures, machine learning applications for wave modeling, and automated shoreline detection algorithms. He actively recruits PhD students for Fall/Spring 2026 to investigate Great Lakes dynamics and resilience strategies. Collaborations span academic and governmental institutions, emphasizing interdisciplinary approaches to environmental challenges. His publications span high-impact journals and conferences, reflecting contributions to both theoretical and applied aspects of water resources engineering.

• Coastal Processes
• Hydrodynamic Modeling
• Remote Sensing
• +4 more