Find Academic Supervisors

Oskar MencerView profile

Professor

• Numerical methods and simulations
• Imaging
• Discretization of space, time and value
• +7 more

Oskar Mencer is a Professor in the Department of Computing at Imperial College London , where he has been a member of academic staff since 2000. He was also a Consulting Professor at Center for Computational Earth and Environmental Science , Stanford University (2009-2010). His research focuses on Multiscale Dataflow Computing , exploring the interaction of hardware and software systems through domain-specific representations, parallel programming, VLSI design, and compiler methodologies. He has contributed to fields including high-performance computing, FPGA optimization, and computational finance. Dr. Mencer's work has been recognized with a Special Award from Com.sult (2012), Imperial College Research Excellence Award (2007), and a Top EPSRC Advanced Fellowship (2001). He has received multiple best paper awards, including at ICFPT'08 and ASAP 2008, and his 2000 paper on stream architectures was recognized as historically significant in 2015. His publications demonstrate a strong emphasis on FPGA acceleration , custom architectures , and parallel processing across geophysics, finance, and neuroscience applications. Special Award for Dataflow Innovation (2012) Best Paper Award - ICFPT'08 Best Paper Award - ASAP 2008 He has served on technical committees for conferences such as FPL , DATE , and FPT , and leads the Computer Architecture Research Group (currently inactive).

Vanessa EcheverriaView profile

Lecturer

• Learning Analytics
• Artificial Intelligence in Education
• Multimodal Data Analysis
• +3 more

Vanessa Echeverria is a Lecturer in the School of Computing Technologies at RMIT University, Australia, and an Assistant Professor at Escuela Superior Politécnica del Litoral (ESPOL), Ecuador. She holds a PhD in Information Technology from the University of Technology Sydney (2020), a Master’s in Computer Science from KU Leuven (2012), and a Bachelor’s in Computer Science from ESPOL (2004). Her research focuses on human-centred AI, learning analytics, and educational technologies, emphasizing the design of AI-driven tools for stakeholders in education and healthcare. She has held postdoctoral roles at Monash University and Carnegie Mellon University. Her work integrates multimodal data analysis, generative AI, and human-centred design to enhance educational outcomes and healthcare simulations. Research Interests: Learning analytics, multimodal data, AI in education, human-centred AI systems, and collaborative learning environments. Her projects include developing dashboards like TeamVision for healthcare simulations and TeamTeachingViz for team-based reflection. She also explores ethical considerations in AI and learning analytics through frameworks like VALA/AID and FATE in MMLA . Teaching: Teaches Python Programming (COSC3106) at RMIT, emphasizing practical coding skills and their application in computational problem-solving. Publications: Over 80 outputs since 2020, including high-impact journal articles in Computers & Education and conference papers at CHI and LAK. Recent work addresses generative AI adoption policies, data storytelling in dashboards, and human-AI collaboration in thematic analysis. Collaborations: Engages in transdisciplinary research across institutions, including Monash University’s Centre for Learning Analytics and partnerships with healthcare and educational institutions globally.

Debra K. BorkovitzView profile

Clinical Professor

• Mathematics Education
• Teaching Methodologies
• Mastery Grading
• +3 more

Debra K. Borkovitz is a Clinical Professor of Mathematics and Mathematics Education at Boston University. Her office is located in CDS 425. She is committed to innovative teaching methodologies, including mastery grading and ungrading, and advocates for inclusive educational policies accommodating students with chronic illnesses. Her research and writing focus on mathematics pedagogy, fraction operations, and the integration of technology in education. Dr. Borkovitz’s work emphasizes compassionate approaches to syllabus design and classroom management. She has explored challenges faced by educators and students with health issues, advocating for supportive academic environments. Her contributions include developing resources for fraction education, critiquing educational technologies, and creating engaging geometric visualizations through animations and interactive applets. Her publications span topics such as MOOCs in programming education, chronic illness management in academia, and problem-solving strategies in mathematics. She has also shared insights on adapting teaching practices during personal health challenges and fostering student engagement through creative methods. No scientific awards are listed for Dr. Borkovitz. Her advising and grant activities are not detailed in the available information. She maintains an active blog and has contributed to educational resources, including handouts on syllabus policies and fraction-based learning activities.

Markus LindemannView profile

Researcher

• Photonics
• Terahertz Technology
• Semiconductor Lasers
• +5 more

Dr. Markus Lindemann is a Senior Researcher at Ruhr-University Bochum's Faculty for Electrical Engineering and Information Technology, working within the Photonics and Terahertz Technology department. His research focuses on advanced semiconductor laser technologies with particular emphasis on VCSELs (Vertical-Cavity Surface-Emitting Lasers) and their applications in high-speed optical communications and terahertz generation. Dr. Lindemann's research interests span photonics, terahertz technology, spintronics, and semiconductor laser physics. His work primarily investigates polarization dynamics in spin-VCSELs, birefringence engineering, and the development of coupled-cavity laser systems capable of ultra-high-frequency modulation. His research has significant implications for next-generation optical data transmission systems that require bandwidths beyond 100 GHz. Analysis of Dr. Lindemann's recent publications reveals a strong focus on advancing VCSEL technology through innovative cavity designs. His work on coupled-cavity VCSEL arrays demonstrates promising approaches for coherent terahertz generation and ultra-broadband optical communications. The research shows a clear trajectory toward overcoming bandwidth limitations in optical data transmission through sophisticated manipulation of laser polarization states and photon-photon resonance phenomena. Dr. Lindemann has published extensively in high-impact journals including Nature, IEEE Photonics Journal, and Applied Physics Letters, with numerous conference presentations at major international venues such as SPIE Photonics West and the IEEE Photonics Conference. His collaborative research approach is evident through his extensive co-authorship network across multiple institutions. Within the Photonics and Terahertz Technology team at Ruhr-University Bochum, Dr. Lindemann contributes to advancing laser technology research, particularly in developing novel VCSEL configurations for high-speed optical communications and terahertz applications. His work bridges fundamental semiconductor physics with practical applications in next-generation optical transmission systems.

Hans-Peter SeidelView profile

Professor

• Computer Graphics
• 3D Image Analysis
• Digital Geometry Processing
• +3 more

Hans-Peter Seidel is a leading academic in computer graphics, serving as Director of the Max Planck Institute for Informatics and Full Professor at Saarland University since 1999. Previously held roles include Full Professor at University of Erlangen (1992–1999) and Assistant Professor at University of Waterloo (1989–1992). Holds a PhD in Mathematics (1987) and Habilitation in Informatics (1989) from University of Tübingen. Research focuses on 3D image analysis, digital geometry processing, visual computing, and free viewpoint rendering. Key achievements include pioneering work in surface editing, motion capture, and multi-view video processing. Has organized major conferences like Eurographics and SIGGRAPH, serving as editor for journals including IEEE TVCG and Computer Aided Geometric Design. Recipient of the Eurographics Distinguished Career Award (2012), Gottfried Wilhelm Leibniz Prize (2003), and numerous fellowships. Led initiatives such as the Cluster of Excellence on Multimodal Computing and Interaction (M2CI) and the Max Planck Center for Visual Computing and Communication (MPC-VCC). Active in academic leadership roles including Eurographics Chair and DFG committees. Publications span over 30 SIGGRAPH and 50 Eurographics contributions, with an h-index of 62 and 14,000+ citations. Recognized as a top-cited researcher in computer graphics. Current research explores advanced visualization techniques and geometric modeling innovations.

Kyle J. HuntView profile

Assistant Professor

• Computational Research and Modeling
• Finance, Business and Management
• Healthcare Analytics
• +5 more

Kyle J. Hunt is an Assistant Professor in Management Science and Systems at the School of Management, University at Buffalo. He is affiliated with the Institute for Artificial Intelligence and Data Science and focuses on interdisciplinary research bridging academia and industry. Education: PhD in Industrial Engineering (Operations Research), University at Buffalo BS in Industrial Engineering, University at Buffalo His research integrates operations research, machine learning, and empirical methods to address challenges in security and defense, healthcare analytics, information management, and technology management. Key areas include attacker-defender games, pandemic decision-making, and misinformation detection during crises. Recent publications analyze adversarial belief formation, counterterrorism technology signaling, and open-set recognition algorithms. Research trends highlight interdisciplinary approaches combining game theory, machine learning, and policy analysis in security and public health contexts. Grants: STTR Phase 2: Machine Learning Detection and Response for Space Force Ground Systems ($540,000, Air Force Research Lab, 2024–2025) AMiRA: Assessing and Mitigating Risks in the Arctic ($460,000, Department of Homeland Security, 2024–2025) NSF DDRIG: Multi-target Technology Deployment in Attacker-Defender Settings ($15,325, 2022–2023) Professional affiliations include INFORMS, Association for Information Systems, INFORMS Information Systems Society, and INFORMS Decision Analysis Society.

Aly A FaragView profile

Professor

• Computer Vision
• Biomedical Imaging
• Image Processing
• +5 more

Aly A. Farag is a Professor of Electrical and Computer Engineering at the University of Louisville, where he founded the Computer Vision and Image Processing (CVIP) Laboratory. His research focuses on imaging science, computer vision, and biomedical imaging, with applications in cancer detection and medical visualization. He has authored over 350 technical papers and two upcoming textbooks. Dr. Farag holds patents in imaging technologies and has led projects funded by NSF, DoD, NIH, and industry. Educations: B.S. in Electrical Engineering, Cairo University, 1976 M.S. in Bioengineering, University of Michigan, 1984 M.S. in Biomedical Engineering, Ohio State University, 1981 Ph.D. in Electrical Engineering, Purdue University, 1990 Research Interests: Scene analysis, multimodal imaging reconstruction, statistical segmentation, and biomedical visualization. His work has advanced tubular topology visualization, colon segmentation, and lung nodule analysis. Collaborations span medical institutions and federal agencies. Awards: 2002 University Scholar designation for technical achievements. Served as associate editor for IEEE Transactions on Image Processing and general co-chair of IEEE ICIP-09. Grants & Advising: Principal investigator on NSF/NIH-funded projects. Advised 15 PhD and 26 MS students, trained 10 postdocs, and introduced new ECE curriculum topics. Labs/Teams: CVIP Lab pioneers innovations in medical imaging and AI-driven diagnostics. Active in interdisciplinary teams for STEM education engagement metrics.

Ryan ShenviView profile

Professor

• Chemical Synthesis
• Natural Products Chemistry
• Medicinal Chemistry
• +3 more

Ryan Shenvi is a Professor of Chemistry at The Scripps Research Institute (TSRI) in La Jolla. His research focuses on developing innovative synthetic methodologies to access complex natural products with potential biomedical applications. He earned his PhD in Chemistry from TSRI (2008) and a B.S. in Chemistry from Pennsylvania State University (2003). His lab pioneered the metal-hydride atom transfer (MHAT) paradigm, enabling efficient synthesis of branched hydrocarbons and natural products like salvinorin A. Major research areas include opioid receptor ligands, neurotrophic agents, and anti-malarial compounds. Notable achievements include the first gram-scale synthesis of jiadifenolide and stabilization of salvinorin A for therapeutic development. Dr. Shenvi has secured over 20 prestigious awards, including the E.J. Corey Award (2021) and Tetrahedron Young Investigator Award (2019). His work bridges organic synthesis, medicinal chemistry, and neuroscience, with collaborations spanning academic and industrial partners like Eli Lilly and Novartis. His lab emphasizes sustainability, using industrial waste in drug development and advancing computer-aided synthesis planning (CASP). Key projects include exploring κ-opioid receptor agonists for non-addictive pain management, annotating the pharmacology of asmarine alkaloids, and synthesizing neurotrophic terpenes with anti-psychotic activity. His group’s MHAT-based cross-coupling reactions have been commercialized and widely adopted in academia and industry.

Hervé VERJUSView profile

Associate Professor

• Decision aiding software systems
• Information fusion methods
• Business process engineering
• +3 more

Hervé VERJUS is an Associate Professor in Computer Science at Université Savoie Mont Blanc, affiliated with Polytech Annecy-Chambéry and the LISTIC Laboratory. He has held this position since 2002. His research focuses on decision-aiding software systems under uncertainty, integrating heterogeneous data, AI-driven anomaly detection, and dynamic adaptable architectures. Key areas include information fusion models, business process mining, and distributed software design. Education: BSc/MSc in Mathematics/Computer Science (University of Savoie, 1996), MSc in Information Systems (University of Grenoble, 1997), PhD in Computer Science (University of Savoie, 2001) under Professors Jacky Estublier and Flavio Oquendo. Research Applications: Snow avalanche risk assessment (mountain decision support), human resource processes, manufacturing systems, and tourism itinerary recommendations. Previously leveraged π-calculus for system architecture design. Current projects emphasize software prototypes for proof-of-concept validation. Academic Roles: Vice-Dean of IAE Savoie Mont-Blanc (2013–2018), permanent faculty at IAE Savoie Mont-Blanc. Member of LSR Lab (CNRS UMR 5526) and LLP Lab during his PhD and early career. Professional Background: Founded and managed an IT company (1996–1999) before academia. Worked in IT, communications, and NGOs from 1993–1999. Contact: Office A115 at LISTIC, reachable via +33(0)4 50 09 65 94. Personal website: https://hverjus.github.io/

• Robotics
• Artificial Intelligence
• Medical Imaging
• +5 more

Dr Shahnewaz Ali is a Postdoctoral Fellow in the Faculty of Engineering's School of Electrical Engineering & Robotics at Queensland University of Technology (QUT). He is affiliated with the Centre for Robotics and holds a PhD from QUT and an MSc in Computer Engineering from Politecnico di Milano. His research focuses on the intersection of robotics, artificial intelligence, and biomedical applications, emphasizing wearable technology, surgical robotics, and sensor systems. Key research interests include AI-driven medical imaging, robotic surgery systems, and biomarker detection using wearable devices. His work spans sensor technologies for robotics, real-time surgical scene analysis, and predictive performance monitoring. Recent projects include developing a wearable monitoring system for stress biomarkers and advancing arthroscopic surgical techniques through 3D mapping and deep learning. Education: PhD, Queensland University of Technology MSc (Computer Engineering), Politecnico di Milano Dr Ali's publications cover topics like surgical scene restoration, microRNA-based performance prediction, and sensor development for medical robotics. His research bridges engineering and healthcare, aiming to enhance diagnostic accuracy and robotic surgical precision. Collaborations include multidisciplinary teams at QUT and international institutions.

• Human-Computer Interaction (HCI)
• Game Design
• Educational Technology
• +4 more

Prof. Peter Purgathofer is an Associate Professor at TU Wien's Department of Human Computer Interaction within the Faculty of Informatics. His work focuses on interdisciplinary research at the intersection of technology, design, and society. He leads projects such as 'Gesture controlled computer game for dementia prevention' and 'Haptic e-learning instrument for handicapped pupils,' demonstrating expertise in healthcare technologies and inclusive design. His research emphasizes ethical AI, game design for education, and human-centered interaction paradigms. Education background includes advanced degrees in engineering and informatics, reflected in his dual role as educator and researcher. Notable contributions include co-creating flipped classroom models for large cohorts, integrating adversarial chatbots into AI ethics curricula, and developing peer-review frameworks for large university courses. Over 20 student theses supervised span topics from AI ethics to gamified health interventions. Publications highlight his work in design-based research, educational technology, and healthcare applications. Projects often involve co-creation with students and end-users, emphasizing participatory design principles. Ongoing interests include responsible innovation in technology and bridging societal challenges through interactive systems.

Victor J MilenkovicView profile

Professor

• Computational Geometry
• Robotics
• Computer-Aided Design (CAD)
• +3 more

Victor J. Milenkovic is a Professor and Department Chair in the Department of Computer Science at the University of Miami's College of Arts and Sciences. His research focuses on computational geometry, geometric algorithms, and their applications in robotics, computer-aided design (CAD), and high-performance computing. He specializes in developing robust algorithms for handling degenerate cases in geometric computations, free space construction for robotic motion planning, and efficient implementations of geometric operations using modern hardware like GPUs. Key contributions include: Advanced techniques for detecting degenerate predicates in computational geometry GPU-accelerated Minkowski sum computations Robust free space construction for polyhedra Geometric rounding methods for preserving mesh topology His work emphasizes practical implementations with provable correctness and efficiency, validated through applications in CAD, robotics, and HPC environments. No academic awards are explicitly listed in the provided materials. Advising and grants: No student advisees or grant details are provided in the profile. His research has been applied to problems in algorithmic robustness, geometric modeling, and parallel computing. Labs/Teams: No specific lab or team affiliations are mentioned beyond his departmental role.

Michael Rygaard HansenView profile

Professor

• Mechatronic Systems
• Hydraulic Components and Systems
• Dynamic Modeling and Simulation
• +5 more

Michael Rygaard Hansen is a Professor at the Department of Engineering Sciences , University of Agder , and has served as Dean of the Faculty of Engineering and Science since 2016. He holds a Ph.D. in Computer-Aided Analysis and Design of Mechanical Mechanisms from Aalborg University (1992) and has been active in research and teaching since 1990. His academic interests focus on Numerical methods for modeling , design and optimization of dynamic mechatronic systems , and hydraulic component analysis . He has taught courses on Modeling and Simulation of Mechatronic Systems , Mechanism Theory , and Fluid Power System Design at undergraduate, master's, and doctoral levels. 2025 : Real-Time Simulation of Electro-Hydraulic Manipulators 2024 : Energy Consumption Analysis in Knuckle Boom Cranes 2022 : Linear Time-Invariant Electrohydraulic Cylinder Models His research groups include Intelligent Mechatronics (iTron) and Machine Design , with applications in offshore engineering, wind turbine mechanics, and crane systems. He has collaborated with industry leaders like Danfoss, Akersolutions, and National Oilwell Varco during his career.

Raska SoemantoroView profile

Researcher

• Machine Learning
• Computer-Aided Design (CAD)
• Fusion Energy
• +6 more

Raska Soemantoro is a Research Assistant at the University of Manchester's College of Engineering, Department of Mechanical and Aerospace Engineering. He is currently pursuing a PhD through the EPSRC Fusion Energy CDT, focusing on automated de-featuring of CAD geometries for simulation of complex systems. His work involves NVIDIA’s Omniverse platform and collaboration with the UK Atomic Energy Authority. Education : BEng in Aerospace Engineering (University of Manchester, 2021) MSc in Computational & Software Techniques in Engineering (Cranfield University, 2022) Research Interests center on machine learning applications for spatial and geometric analysis. Key areas include digital twin technology, CAD geometry simplification, neutronics simulation, and point cloud processing. His work aligns with UN Sustainable Development Goals related to education and computational engineering. Research Output Trends highlight collaborations across engineering software platforms, fusion energy systems (e.g., MAST-U Tokamak), and AI-driven geometric analysis. His projects involve digital twin platforms for lithium-based reactors, robotics for medical imaging, and LiDAR-based geospatial algorithms. Scientific Awards include: Best BEng Research Project (2021) Best Project Award (2022) Best Overall Achievement in MSc Computational Intelligence for Data Analytics (2023) CIUK Best Poster Prize (2024)

Yongliang YangView profile

Senior Lecturer

• Computer Graphics
• Shape Understanding
• Computational Design
• +6 more

Yongliang Yang is a Senior Lecturer in the Department of Computer Science at the University of Bath, affiliated with the Centre for the Analysis of Motion, Entertainment Research & Applications (CAMERA). His research spans computer graphics, shape understanding, and computational design with applications in 3D vision and geometric processing. His primary research focuses on developing shape analysis and optimization algorithms for geometric structures, with recent work emphasizing neural radiance fields, point cloud processing, and generative adversarial networks. Key contributions include novel approaches to dynamic scene representation, facial inpainting, and surface approximation techniques. Recent publications demonstrate strong trends in neural rendering for dynamic scenes and generative image synthesis, bridging geometry processing with deep learning for practical 3D reconstruction applications. Scientific recognition includes: Computer Aided Geometric Design Most Cited Paper Award (2011) Computer Aided Geometric Design Most Cited Paper Award (2012) Dr. Yang serves as Principal Investigator for Dynamic Human Reconstruction and Editing with Neural Radiance Fields (Royal Society, 2024-2026) and is Co-Investigator on CAMERA 2.0 (EPSRC, 2020-2025) and EU Horizon 2020 projects. He has supervised 9 students and serves as Associate Editor for Computer Graphics Forum (2025-2028). He actively contributes to CAMERA's research ecosystem focused on motion capture, virtual reality, and entertainment applications, driving innovation in motion analysis and digital content creation.