Find Academic Supervisors

Marcia SchulmeisterView profile

Teaching Professor

• Hydrogeology
• Geochemistry
• Environmental Geology
• +4 more

Dr. Marcia Schulmeister serves as Director and Teaching Professor in the Environmental Geology Programs at the University of Kansas Edwards Campus, with a dual appointment in the Department of Geology. With over 30 years of experience, she specializes in applied hydrogeology and geochemistry, focusing on contaminated site remediation and groundwater management. Her professional work spans government agencies in the U.S., China, Thailand, and Germany, addressing soil and groundwater contamination challenges. Dr. Schulmeister holds prestigious titles including Fellow of the Geological Society of America and Fulbright Scholar. She contributes to academic leadership as associate editor for professional journals and serves on multiple boards. Her research explores innovative methods like electrical resistivity tomography and direct-push geochemical profiling, with recent emphasis on virtual geology education and international environmental projects in Thailand and Vietnam. Key Expertise: Hydrogeology field methods, contaminant transport modeling, karst terrain studies International Experience: Collaborations in China, Thailand, Germany, and Vietnam Teaching Innovation: Pioneering online geoscience education for non-traditional students Her work integrates field-based learning through the Robert P. Harrison Field Station and virtual museum tours. Current research trends emphasize climate change impacts on groundwater systems and geohazard mitigation for infrastructure protection.

• Cyber Physical Systems
• Risk/Reliability Analysis
• Deep Learning
• +3 more

Dr. Saptarshi Sengupta is an Assistant Professor in the Department of Computer Science at San José State University (SJSU), leading the Machine Intelligence and Complex Systems (MICoSys) Lab. He advises the ACM student club at SJSU and holds a 'Alien of Extraordinary Ability' visa (Einstein Visa) from USCIS. His work focuses on resilient cyber-physical systems, risk analysis, and deep learning applications in healthcare and industrial systems. Education: Ph.D. in Electrical Engineering, Vanderbilt University M.S. in Electrical Engineering, Vanderbilt University B.Tech. in Electronics & Communication Engineering, West Bengal University of Technology Research Interests: Cyber-Physical Systems Security Healthcare AI for Cancer and Chronic Disease Prediction Battery Prognostics and Energy Systems Machine Learning for Complex Systems Analysis Key Achievements: Dr. T.M.A. Pai Gold Medal Award for Healthcare AI contributions Recipient of multiple best paper awards at international conferences Author of over 30 peer-reviewed publications Labs & Teams: Leads the MICoSys Lab, developing AI solutions for healthcare diagnostics, industrial prognostics, and smart infrastructure systems. Collaborations include interdisciplinary projects with biomedical and engineering domains.

• Computational Methods
• High Performance Computing
• Cloud Computing
• +3 more

Professor Simon Cox is a Professor of Computational Methods and Director of the Microsoft Institute for High Performance Computing within the Faculty of Engineering and Physical Sciences at the University of Southampton. He holds a doctorate in Electronics and Computer Science, complemented by first-class degrees in Mathematics and Physics. His research focuses on computational tools and platforms, particularly in high-performance computing, cloud computing, and interdisciplinary applications in engineering and science. He has secured over £30 million in research and enterprise funding, published over 250 papers, and is a Microsoft Most Valuable Professional since 2003. Research interests include computational electromagnetics, meshless methods, and data management. His team, the Computational Engineering and Design Group, develops high-performance computing systems and commercial distributed computing solutions. Notable projects include a Raspberry Pi and Lego-based supercomputer and a spin-off company from computational electromagnetics research. He actively supervises PhD students in Engineering and Environmental Science. Key awards include the Microsoft MVP title. His work spans environmental monitoring (e.g., methane sensors, IoT-based peatland tracking), cybersecurity for IoT devices, and biomedical applications like 3D X-ray histology. He leads outreach initiatives, including the 'Supercomputing in Engineering Course' since 2005.

Josh ReissView profile

Professor

• Audio Engineering
• Signal Processing
• Music Production
• +4 more

Josh Reiss is a Professor of Audio Engineering at Queen Mary University of London (QMUL), part of the School of Electronic Engineering and Computer Science . He holds additional roles including President-Elect and Fellow of the Audio Engineering Society (AES), and Visiting Professor at Birmingham City University. His research focuses on audio signal processing, procedural audio, and intelligent music production. He earned degrees including BSc in Physics, BSc in Mathematics, and a PhD. Research & Awards : Reiss has published over 200 papers, authored books like Intelligent Music Production , and received awards such as the AES Board of Governors Award (2009, 2010) and Best JAES Paper 2016. His work spans sound synthesis, dynamic range compression, and live audio systems. Teaching & Industry : Teaches modules like Artificial Intelligence and Sound Design. Co-founded startups LandR (AI mixing), Tonz, and Nemisindo. Leads the Centre for Digital Music at QMUL, advancing research in audio technology. Labs & Teams : Active in the Centre for Digital Music, collaborating on projects like the Open Multitrack Testbed and semantic audio evaluation tools.

Mario Costa SousaView profile

Professor

• Computer Graphics
• Scientific Visualization
• Sketch-based Modeling
• +5 more

Mario Costa Sousa is a Professor in the Department of Computer Science at the University of Calgary. He holds a BSc from Catholic University of Petrópolis (1989), an MSc from Pontificia Universidade Católica do Rio de Janeiro (1994), and a PhD in Computer Science from the University of Alberta (1999). His primary research focuses on computer graphics, scientific visualization, and sketch-based modeling with applications to geoscience and reservoir engineering. He leads the illustrares research group, which develops novel visual computing paradigms for interdisciplinary challenges in science, engineering, and design. Research interests include non-photorealistic rendering, sketch-based interfaces, visualization/visual analytics, and human-data interaction. His work integrates geoscientific data with interactive modeling tools to address reservoir uncertainty and enhance decision-making in energy and environmental domains. Recent projects involve rapid prototyping of subsurface CO2 sequestration models and machine learning for drill core analysis. He teaches courses such as CPSC 591/691 Rendering (Fall 2024), CPSC 319 Data Structures (Winter 2025), and DATA 501 Data Science Capstone (Winter 2025). His research has contributed to energy innovation initiatives at the University of Calgary, focusing on geothermal energy and unconventional reservoirs. Key collaborations include work on Gaussian process-based uncertainty quantification, functional data analysis for production forecasting, and immersive VR tools for surgical training (e.g., NeuroSimVR and JackVR oil rig simulators). His publications span reservoir modeling, geological visualization, and interactive systems for spatial data exploration.

Sebastian HeathView profile

Associate Clinical Professor

• Roman Archaeology
• Digital Humanities
• Numismatics
• +4 more

Sebastian Heath is a Clinical Associate Professor of Computational Humanities and Roman Archaeology at New York University's Institute for the Study of the Ancient World (ISAW). He holds additional roles including Director of Graduate Studies (AY2024-26), Chair of the PhD Admissions Committee, and editor of ISAW Papers. His expertise spans Roman archaeology, digital humanities, and numismatics, with a focus on computational methods applied to Mediterranean material culture. He earned an A.B. in Medieval Studies from Brown University and a Ph.D. in Classical Art and Archaeology from the University of Michigan. His research integrates fieldwork (e.g., excavations in Cyprus, France, Greece, and Italy) with digital initiatives like the Pompeii Artistic Landscape Project (funded by the Getty Foundation) and the Linked Ancient World Data Institute (LAWDI). Recent courses include 'Graph Databases and Network Analysis,' '3D and Virtual Reality for the Ancient World,' and 'Data Modeling and Querying.' He co-directs projects such as the digital publication Greek, Roman, and Byzantine Pottery at Ilion and serves as a Research Scientist, Life Fellow, and Trustee at the American Numismatic Society. Publications include DATAM: Digital Approaches to Teaching the Ancient Mediterranean (2020) and articles on Roman amphitheaters, numismatic data standards, and digital pedagogy. His work emphasizes open science practices and the application of computational tools to archaeological challenges.

Laura HarperView profile

Senior Lecturer

• Architecture
• Urban Design
• Materials Science
• +8 more

Dr Laura Harper is a Senior Lecturer in the Department of Architecture at Monash University, part of the Faculty of Art, Design and Architecture. She holds a PhD in Architecture from Monash (2018), with research focusing on material systems, urban geology, and sustainable design. Her work bridges academic research and professional practice, including collaborations with firms like NMBW Architecture Studio and Roland Snooks. Research Interests: Laura explores material processes and their connections to urban environments, particularly geological influences on cities. Key areas include the 'Afterlife of Mines,' urban fringe quarries, and Indigenous-led water design. She leads projects like the Repair of Memory and Place collaboration with the Boon Wurrung Foundation and Melbourne Water. Projects and Grants: Current projects include the Monash Urban Lab's 20-Minute Neighbourhoods initiative and funded work with the NSW Government's Building 4.0 CRC. She has contributed to significant built works such as the award-winning Box Hill Gardens (AIA Urban Design Award 2014) and Point Lonsdale House (AIA New Residential Award 2016). Awards: Laura and her teams have received multiple architecture awards, including the 2016 National Architecture Award for Residential Architecture and the 2023 ArchitectureAU Social Impact Commendation for St Albans Housing . Teaching and Practice: Laura teaches at Monash while practicing collaboratively with Roland Snooks, exploring advanced manufacturing and material innovation. She is a graduate research supervisor and actively participates in public lectures and exhibitions.

• Robotic Vision
• Autonomous Systems
• Computer Vision
• +6 more

Annette Stahl is a Professor at the Department of Engineering Cybernetics, NTNU, and an Onsager Fellow. She leads the Robot Vision Group and oversees the AILARON project, funded by the Research Council of Norway. Her expertise spans robotic vision, control theory, and autonomous systems. She holds a PhD in Applied Mathematics (Computer Vision) from Heidelberg University. Her research focuses on underwater robotics, autonomous vehicles, and aquaculture monitoring, with applications in fish health analysis and marine environmental sensing. Stahl has supervised numerous PhD and master’s students, including projects on autonomous ships (SFI AutoShip), underwater SLAM (AROS), and plankton identification. She collaborates with industry partners like Zebop AS and SINTEF Ocean. Notable projects include the robotic microplankton sniffer-dog and AI-driven fish welfare monitoring. Her work is published in top journals/conferences like IEEE Access and MIC Journal. She actively contributes to datasets like the VAROS Synthetic Underwater Data Set.

Brian FisherView profile

Professor

• Cognitive Science
• Visual Analytics
• Human-Computer Interaction
• +2 more

Brian Fisher is a Professor at Simon Fraser University's School of Interactive Arts and Technology, where he leads the Interaction Science Research Group. He holds affiliate positions at the University of British Columbia and serves as Associate Director for the Media And Graphics Interdisciplinary Centre (MAGIC). His research investigates human reasoning in responsive environments through cognitive science approaches, developing visualization systems that support individual and distributed cognition. Fisher's work spans personalized health, aircraft safety analysis, space object classification, and emergency management. His teaching integrates perceptual, cognitive, and social science knowledge into design education. He actively participates in science policy through organizations including NSERC, Defence R&D Canada, EUREKA Eurostars, and IEEE committees. Fisher has been recognized as a Fellow of the Psychonomics Society and chaired major conferences including IEEE VIS 2019. His research is characterized by strong interdisciplinary collaboration and real-world applications in high-stakes decision domains.

Joe D. WarrenView profile

Professor

• Computer Graphics
• Geometric Modeling
• Computational Geometry
• +3 more

Joe D. Warren is a Professor of Computer Science at Rice University, where he has served since 1986. His research focuses on computer graphics, geometric modeling, and computational geometry, with notable contributions to subdivision surfaces, as detailed in his book Subdivision Methods for Geometric Design . He also explores bioinformatics applications, including 3D modeling of mouse brain gene expression and lung motion analysis from 4D CT scans. Additionally, Warren teaches courses in computer game design and introductory programming, co-developing award-winning Coursera specializations. He earned his Ph.D. from Cornell University and previously served as Department Chair (2008-2013). Education: B.Sc. (Rice University, 1983), Ph.D. (Cornell University, 1986) Research Collaborators: Baylor College of Medicine, MD Anderson Cancer Center, Texas A&M Teaching: COMP460 (Game Design), COMP110 (Introductory Computing) His work on the GRACE tool (Graphical Ruler and Compass Editor) won the 1998 Quest for Java award. He has advised PhD students now at Washington University and Texas A&M. Current projects include game prototyping with Pi Studios and lung motion modeling for medical diagnostics.

Chen WeiView profile

Assistant Professor

• Computer Vision
• Machine Learning
• Generative AI
• +3 more

Chen Wei is an Assistant Professor of Computer Science at Rice University (starting Fall 2025) and a Postdoctoral Researcher at Meta AI's FAIR division. She holds a PhD from Johns Hopkins University (2024) and a B.Sc. from Peking University (2019). Her research focuses on advancing visual intelligence through generative AI, multimodal learning, and self-supervised learning. She has been recognized with awards such as EECS Rising Stars (2023) and Most Influential CVPR Papers (2023). Education: PhD, Computer Science, Johns Hopkins University (2024) BSc with Honors, Computer Science, Peking University (2019) Research Interests: Chen's work addresses core challenges in AI by transforming visual data into structured knowledge. Key areas include: Generative Understanding: Building world models via generative systems Multimodal Learning: Integrating visual data with LLMs for higher-order cognition Self-Supervised Learning: Discovering structures in raw visual data Awards: EECS Rising Stars, 2023 Most Influential CVPR Papers, 2023 Lab Openings: Recruiting PhD students (2025) and Rice undergraduates. Focus areas include generative models, multimodal systems, and scalable self-supervised learning. Contact via email for advising inquiries.

Vien CheungView profile

Associate Professor

• Colour and Philosophical Studies
• Imaging and Vision Science
• Textile and Materials Science
• +4 more

Dr Vien Cheung is an Associate Professor at the University of Leeds' School of Design, part of the Faculty of Arts, Humanities and Cultures. Her research focuses on colour science, imaging, and textile technology, with specializations in areas like colour in EDI, cultural heritage, and material design. She holds a Gold Medal (2023) from the Society of Dyers and Colourists (SDC) for contributions to colour research and education. Dr Cheung’s expertise includes Colour and Philosophical Studies, Imaging and Vision Science, and Textile/Materials Science. She has explored topics such as colour perception, textile manufacturing innovation, and the cultural significance of colours in historical art. Her work bridges art, science, and technology, addressing both theoretical and applied challenges. Education: BSc (Hon) Textile Chemistry, MSc Colour Imaging, PhD in Colour and Imaging Science. Professional Memberships: International Colour Association (AIC), Society of Dyers and Colourists (SDC), and others. Her research outputs span colour harmony, digital anthropometry in textiles, and instructional design for language learning. She advocates for inclusive design practices and has contributed to the University of Leeds’ World Changemakers series on impactful research. Awards: SDC Gold Medal (2023), Fellowship of the SDC (FSDC), and Chartered Colourist (CCol) certification.

David Ryan KoesView profile

Associate Professor

• Computational Drug Discovery
• Deep Learning
• Discrete Algorithms
• +3 more

David Ryan Koes is an Associate Professor in the Department of Computational and Systems Biology at the University of Pittsburgh, affiliated with the Joint CMU-Pitt PhD Program in Computational Biology. His research focuses on computational drug discovery, deep learning, and discrete algorithms, aiming to develop novel methods for rapid drug development and open-source software tools. He holds an office at 3064 Biomedical Science Tower 3 and 748 Murdoch Building. Key roles include Associate Director of the CPCB program and leadership in initiatives like CompBio Academy. His software contributions include libmolgrid, gnina, and 3Dmol.js, which advance molecular modeling and visualization. Research interests emphasize AI-driven drug discovery, including molecular docking, pharmacophore modeling, and generative models for molecule design. Recent work involves deep learning for protein structure prediction and pharmacophore elucidation. He has secured NIH grants (e.g., R35GM140753) and collaborations with institutions like CMU and industry partners. Advising over 25 students in computational biology, biotech, and data science programs, Koes bridges academia and industry through projects like Pharmit and the Teach-Discover-Treat initiative. His lab's work spans from foundational ML research to applied drug discovery, with a focus on open science and reproducibility.

Claus Brøndgaard MadsenView profile

Associate Professor

• Computer Vision
• Virtual Reality
• Augmented Reality
• +7 more

Claus Brøndgaard Madsen is an Associate Professor in the Department of Architecture, Design and Media Technology at Aalborg University, under The Technical Faculty of IT and Design. He is based at Campus Aalborg and is affiliated with the Computer Graphics Group and VR Light research environment. His work bridges computer vision, virtual reality, and architectural design, with a strong focus on real-time visualization and human interaction in digital environments. Research Interests: His primary research areas include Computer Vision , Virtual Reality (VR) , Augmented Reality (AR) , 3D Reconstruction , Structure-from-Motion (SfM) , and Image-Based Lighting . These are applied in industrial VR, urban design evaluation, and sensory augmentation systems. His research fingerprint highlights strong engagement with Virtual Reality (100%), Augmented Reality (71%), Illumination Conditions (41%), and Wind Turbine Engineering (28%). The recent publications (2023–2025) reflect a consistent trend in enhancing user experience in VR/AR environments, with emphasis on spatial cognition, locomotion techniques, exposure control, and machine learning integration for lighting classification and part direction prediction in industrial contexts. These works are published in top-tier conferences such as EG, GRAPP, WACV, and CAADRIA. Scientific Awards: No specific awards or fellowships are mentioned in the provided text. Advising and Grants: Madsen has supervised PhD students and served as a supervisor in research projects like AAIVR. He is Principal Investigator (PI) in multiple funded projects, including BUMUS: Sustainable Expansion of Mussel Production (2024–2027), CityVR: Evaluating Parametric City Designs in VR (2020–2022), and V-BRT: Virtual Bus Rapid Transit (2019). These projects reflect substantial grant acquisition and leadership in applied VR research. Labs and Research Groups: He is a key member of the Computer Graphics Group and VR Light at Aalborg University, which focus on real-time visualization, lighting techniques, and immersive technologies for industrial and architectural applications.

Ammar HooriView profile

Academic

• Cardiac Imaging
• Data Science
• Artificial Intelligence
• +7 more

Ammar Hoori, PhD, is a Research Assistant Professor in the Department of Biomedical Engineering at Case Western Reserve University, affiliated with both the Case School of Engineering and School of Medicine. His research focuses on cardiac image analysis, leveraging advanced techniques like image registration, deep learning, and survival analysis. He leads NIH-funded projects involving CT calcium scoring, IVOCT, and chest CT imaging, collaborating with cardiologists from University Hospitals Cleveland and engineers from CWRU. His work emphasizes developing calcium-omics and fat-omics features to improve cardiovascular disease prediction. His research team employs cutting-edge methods such as deep learning segmentation for epicardial adipose tissue analysis, aiming to optimize patient care through AI-driven risk stratification. Hoori’s contributions include the development of the DeepFat algorithm for automated fat quantification and collaborations on stent under-expansion prediction using OCT imaging. He is also involved in the Biomedical Imaging Laboratory (BMIL), contributing to advancements in cryo-imaging and 3D visualization techniques. Key areas of innovation include AI-enabled risk prediction for heart failure, MACE (Major Adverse Cardiovascular Events), and coronary artery disease using opportunistic data from routine CT scans. His work bridges clinical and engineering expertise to advance non-invasive diagnostic tools and personalized medicine strategies.