جست‌وجوی استاد و پژوهشگر

Kathryn Hess Bellwaldمشاهده پروفایل

استاد

• Algebraic Topology
• Homotopy Theory
• Neuroscience
• +۴ مورد دیگر

Kathryn Hess Bellwald is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL) in both the School of Life Sciences and School of Basic Sciences . She leads the Laboratory for Topology and Neuroscience and serves as Academic Director for the Euler Programme . Her work bridges pure mathematics and interdisciplinary applications in neuroscience, materials science, and data analysis. Education : PhD in Mathematics (MIT, 1989), preceded by positions at Stockholm, Nice, and Toronto universities. Her research spans algebraic topology , homotopy theory , operad theory , and algebraic K-theory , with applications in neuroscience and materials science . She has pioneered topological data analysis methods for classifying neuronal morphologies , microglia phenotypes , and nanoporous materials , creating a parameter-free framework linking neural network structure to activity. The 15 most recent publications highlight her work on topological inverse problems , neuroinflammation , and equivariant homotopy . These studies often involve collaborations with the Blue Brain Project and EPFL teams in neuroscience , machine learning , and materials science . Scientific Awards : Fellow, American Mathematical Society (2017); Distinguished Speaker, European Mathematical Society (2017); Crédit Suisse Teaching Prize (2012); Polysphère d'Or (2013); Full Member, Swiss Academy of Engineering Sciences (2016); Chaire de la Vallée Poussin (2023); Fellow, Association for Women in Mathematics (2024). She has mentored numerous PhD students in mathematics and neuroscience, including Adélie Eliane Garin , Varvara Karpova , and Dimitri Zaganidis . Her EPFL Mathematics affiliations include the DIVISION MATH , while her Neuroscience lab operates under the Brain Mind Institute (BMI) in the School of Life Sciences (SV). Grants and collaborations are evident in her work on neurodegenerative diseases , synthetic materials , and machine learning frameworks .

Per-Arne Andersenمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Reinforcement Learning
• Tsetlin Machines
• +۷ مورد دیگر

Per-Arne Andersen is an Associate Professor at the Department of Information and Communication Technology within the University of Agder . His research focuses on artificial intelligence , reinforcement learning , Tsetlin machines , and deep learning , with applications in real-time strategy games , industrial environments , and IoT systems . Projects: RESTORE Research Groups: CAIR - Center for Artificial Intelligence Research, CIEM - Center for Integrated Crisis Management, Intelligent Mechatronics (iTron) His work explores safe and sustainable reinforcement learning , interpretable AI , and generative environment modeling . He has developed frameworks like CaiRL and CostNet for high-performance RL environments and goal-directed learning. Recent publications include advancements in Tsetlin automaton analysis , GNSS jamming classification , and road quality detection . Articles from 2025-2016 span machine learning , computer vision , and environmental modeling . He contributes to IEEE , Springer , and LNCS publications, with a focus on interdisciplinary AI applications in crisis management , cybersecurity , and industrial optimization .

• Sustainable Energy and Environment
• Combustion Engineering
• Turbulent Reacting Flows
• +۸ مورد دیگر

Jay P. Gore is the Vincent P. Reilly Professor in Combustion Engineering at Purdue University's School of Mechanical Engineering, with courtesy appointments in Aeronautics & Astronautics and Chemical Engineering. He holds positions at the West Lafayette campus and leads the Gore Research Group, focusing on combustion, radiation heat transfer, and sustainable energy systems. Education: B.E. from University of Poona (1978), M.S. and Ph.D. from Penn State (1982, 1986), and a Postdoctoral Certificate from University of Michigan (1987). His research spans combustion fundamentals, CO2 recycling via char gasification, laser diagnostics, and propulsion systems. He pioneered the Summer Undergraduate Research Fellowship (SURF) program at Purdue. Research interests include turbulent reacting flows, biomedical heat transfer, and global energy policy. Key subfields are combustion diagnostics, flame structure analysis, and hydrogen storage. His work integrates experimental and computational methods, with applications in aerospace, energy, and environmental sectors. Awards: Purdue Innovator Hall of Fame (2014) Fellowships: AIAA (2009), ASME (2006) Reilly Chair Professor (2000) Presidential Young Investigator Award (1991) Grants & Collaborations: Supported by DoE, NASA, and industry partnerships. Leads interdisciplinary projects on CO2 utilization and renewable energy systems. Labs/Teams: Gore Research Group specializes in combustion diagnostics, laser-based measurements, and sustainable energy solutions. Collaborations include international conferences and policy initiatives.

Bedrich Benesمشاهده پروفایل

استاد

• Computer Graphics
• Geometric Modeling
• Computational Biology
• +۵ مورد دیگر

Bedrich Benes is a Professor and Associate Department Head in the Department of Computer Science at Purdue University. He holds a Ph.D. and M.S. in Computer Science from Czech Technical University in Prague (1998 and 1991, respectively). His research focuses on generative methods for geometry synthesis, procedural modeling, simulation of natural phenomena, and additive manufacturing. He has published over 200 research papers and secured grants from organizations like the NSF, NASA, and DOE. Editor-in-Chief of Elsevier's Graphical Models Senior Member of ACM and IEEE Fellow of Eurographics Association Research interests include graphics, visualization, geometric modeling, and computational biology. He leads projects on tree digital twins, urban forestry modeling, and immersive VR/XR education. Advised students include Bosheng Li and Xiaochen Zhou, who recently defended their Ph.D. theses. Notable contributions include neural ranking algorithms for forest reconstruction and tools like Tree-D Fusion for tree dataset generation. His work bridges computer graphics with environmental science and agriculture.

Mihran Tuceryanمشاهده پروفایل

استاد

• Computer Vision
• Image Processing
• Pattern Recognition
• +۳ مورد دیگر

Professor Mihran Tuceryan is a Professor of Computer Science at Purdue University Indianapolis, affiliated with the Department of Computer Science within the College of Science. He holds a PhD from the University of Illinois at Urbana-Champaign (1986) and a BS from MIT (1978). His expertise spans Computer Vision, Image Processing, Pattern Recognition, and Augmented Reality. Recent research focuses on crime prediction via video analysis, forensic imaging, and distributed tracking systems. He is a Senior Member of IEEE and ACM. Key research interests include augmented reality integration for industrial training, real-time illumination modeling, and monocular SLAM algorithms. His work addresses challenges in photorealistic AR, dynamic object labeling, and medical imaging applications such as hepatic fibrosis detection. He has contributed to projects like the e-DOTS indoor tracking system and forensic 3D impression acquisition. His publications span over three decades, emphasizing real-world applications in security, healthcare, and robotics. Education: Bachelor of Science in Computer Science and Engineering, MIT, 1978 PhD in Computer Science, University of Illinois at Urbana-Champaign, 1986 Awards: Senior Member, IEEE Senior Member, ACM Labs/Teams: Focus on AR, SLAM, and medical imaging applications Collaborative frameworks for distributed visual SLAM

Wendy M. Murrayمشاهده پروفایل

استاد

• Biomechanical Modeling
• Upper Limb Rehabilitation
• Prosthetics and Exoskeletons
• +۵ مورد دیگر

Wendy M. Murray is a Professor of Biomedical Engineering and Physical Medicine and Rehabilitation at Northwestern University's McCormick School of Engineering. She leads the ARMS Lab, focusing on biomechanical models of upper limb muscles to improve rehabilitation and prosthetic design. Her work addresses spinal cord injury, stroke, and orthopedic interventions. Education: Ph.D. and M.S. in Biomedical Engineering from Northwestern University, B.S. in Mathematics (summa cum laude) from University of Notre Dame. Research interests include musculoskeletal modeling, prosthetics control, and surgical simulations. Key contributions include widely cited anatomical databases and models for hand/wrist function. Current projects explore neuromuscular control, exoskeletons, and injury prevention in sports like baseball. Publications (selected 2024-2017) highlight advancements in motion capture, ultrasound imaging, and computational models for clinical applications. Her work bridges bioengineering with clinical practice to enhance functional recovery. Labs/Teams: Directs the ARMS Lab, collaborating with clinicians and engineers to translate biomechanical insights into real-world medical solutions.

• Antennas and Propagation
• Electromagnetics
• Wireless Networks
• +۴ مورد دیگر

Can Ding is an Associate Professor in the School of Electrical and Data Engineering at the University of Technology Sydney (UTS), affiliated with the Faculty of Engineering and IT. He is a core member of the Global Big Data Technologies Centre (GBDTC). Ding holds a BEng in Microelectronics from Xidian University (2009) and a joint PhD in Electromagnetic Fields and Microwave Technology from Xidian University and Macquarie University (2016). His research focuses on engineering electromagnetics, particularly in base station antennas for 5G/6G networks, cross-band interference mitigation, and antenna array design. He has led numerous industry-collaborative projects, including ARC-funded initiatives, and has over 120 publications in top-tier journals/conferences, featured in IEEE's 'What’s Hot in Antennas and Propagation.' Teaching highlights include coordinating foundational electrical engineering courses and studio subjects, recognized with UTS's 2023 'Mid-Career Educator of the Year' award. He actively contributes to professional societies like IEEE AP-S, serving as an editor and conference organizer. His awards include the ARC DECRA grant (2020), Top 2% World Scientist (2023), and multiple outstanding reviewer distinctions. His grants include 'Advancing Millimeter-Wave Base Station for 6G' (ARC DP, 2025–2027) and 'Maximizing 5G Signal Transparency' (UTS Bluesky, 2024). Ding supervises students in antenna design and has mentored over a dozen researchers, many of whom have won international conference awards.

• Smart Cities
• Geovisual Analysis
• Urban Dynamics
• +۵ مورد دیگر

Dr. Gavin McArdle is an Associate Professor at the University College Dublin (UCD) School of Computer Science, specializing in spatial data analysis and smart cities. He holds academic affiliations with the National Centre for Geocomputation (Maynooth University) and CeADAR (Data Analytics Centre). His research focuses on urban dynamics, geovisual analytics, smart transportation, and remote sensing applications. He has received a College of Science Teaching Excellence Award for his contributions to education. McArdle earned his BSc, PhD, and a Prof Dip in University Teaching & Learning from UCD. His work bridges academia and industry through collaborative grants, including those from Science Foundation Ireland and EU funding. Notable projects include the Dublin Dashboard (urban analytics platform) and DubSim (traffic simulation using digital footprints). His research outputs span over 147 publications, with recent work addressing Airbnb's impact on urban gentrification, sustainable mobility, and environmental monitoring via satellite data. He actively contributes to professional committees, including roles in the UCD Data Protection Impact Assessment Committee and international conferences like Web and Wireless GIS. McArdle coordinates courses such as Research Practicum and Computer Programming II, emphasizing practical research and technical skills. His interdisciplinary approach integrates machine learning, spatial statistics, and urban informatics to address real-world challenges in smart cities and environmental sustainability.

H. Siegfried Stiehlمشاهده پروفایل

استاد

• Computer Vision
• Computational Neuroscience of the Visual System
• Cognitive Science
• +۳ مورد دیگر

Prof. Dr.-Ing. H. Siegfried Stiehl is a retired Senior Professor (until Sept 2021) at the Department of Informatics, University of Hamburg. He previously held roles including Dean of the Faculty of Mathematics, Computer Science, and Natural Sciences (2001–2006), Vice President for Research (2007–2013), and Head of the Image Processing Research Group. His academic journey includes a PhD from TU Berlin (1980) and a Habilitation in Computer Vision (1987). Education: 1973: Ing. Degree in Ingenieur-Informatik, Fachhochschule Furtwangen 1976: Diploma in Computer Science, TU Berlin 1980: Dr.-Ing. Dissertation on medical image processing, TU Berlin Research focuses on Computer Vision , Computational Neuroscience , and Cognitive Science , with contributions to medical image registration, 3D landmark detection, and biomechanical modeling. Key projects include the EU-funded 'COVIRA' consortium (1989–1995) and leadership in the SFB 950 'Manuscript Cultures' project (2015–2019). His 110+ publications span biomedical image registration, elastic deformation algorithms, and real-time signal processing. Notable collaborations include work with institutions like the University of Pennsylvania, University of Birmingham, and Philips Research. Leadership roles include organizing scientific events, serving on editorial boards (e.g., Biological Cybernetics), and founding the Interdisciplinary Nanoscience Center Hamburg (INCH) in 2001. His research has addressed challenges in neurosurgical interventions, VLSI implementation of neural networks, and interdisciplinary education.

Weiwen Jiangمشاهده پروفایل

استادیار

• Quantum Computing
• AI Accelerators
• Hardware-Software Co-Design
• +۳ مورد دیگر

Weiwen Jiang is a tenure-track Assistant Professor in the Department of Electrical and Computer Engineering at George Mason University (GMU), affiliated with the College of Engineering and Computing (CEC). He leads the JQub lab, focusing on hardware/software co-design for computing systems, spanning classical (FPGAs, ASICs) and quantum computing applications in AI-driven fields like medical imaging and geophysics. Prior to GMU, he held a postdoctoral position at the University of Notre Dame and earned his PhD in Computer Science from Chongqing University with a joint PhD in Electrical and Computer Engineering from the University of Pittsburgh. His research emphasizes quantum computing, AI accelerators, and domain-specific computing. Notable achievements include the 2025 NSF CAREER Award, ACM Sigda Meritorious Service Award (2024), and IEEE QuantumWeek Best Paper Award (2023). His work is funded by NSF, DoE, ARO, Meta, and Leidos. He co-chaired IEEE QuantumWeek (2023–2025) and created workshops like StableQ at ESWEEK 2023. Key contributions include developing frameworks like QuPAD for quantum learning and JQub's AI-driven geophysical and medical imaging tools. His lab graduated Dr. Yi Sheng (now at University of South Florida) and Dr. Zhepeng Wang (Amazon Applied Scientist). Current research explores quantum machine learning, noise mitigation, and fairness in AI for edge devices.

Jingsong Zhouمشاهده پروفایل

استاد

• Neuromuscular Diseases
• Striated Muscle Physiology
• Calcium Signaling
• +۴ مورد دیگر

Dr. Jingsong Zhou is a Professor of Kinesiology and Associate Director of the Bone-Muscle Research Center at The University of Texas at Arlington. Her research focuses on neuromuscular diseases, particularly Amyotrophic Lateral Sclerosis (ALS), with expertise in striated muscle physiology, calcium signaling, and mitochondrial dysfunction. She leads the Neuromuscular Diseases Lab, which develops genetic mouse models and molecular probes to study ALS mechanisms. Dr. Zhou’s work has been supported by NIH, MDA, DOD, and the ALS Association. She serves on the NIH SMEP study section and has over 20 years of academic experience, including postdoctoral training at Vanderbilt University College of Medicine and a PhD from Rush University School of Medicine. Education: Postdoctoral Fellow in Pharmacology, Vanderbilt University College of Medicine (2001) PhD in Molecular Biophysics and Physiology, Rush University School of Medicine (1997) Diploma in Medicine, Hunan Medical University (Xiangya Medical School) (1986) Research Interests: Mechanisms of calcium signaling and mitochondrial dysfunction in ALS Role of sarcolemma repair and autophagy in neuromuscular disease progression Development of therapeutic strategies targeting mitochondrial health and membrane integrity Grants and Funding: NIH grants focused on ALS pathogenesis and muscle-bone interactions Support from MDA, DOD, and ALS Association for translational research projects Labs and Teams: Director of the Neuromuscular Diseases Lab at UT Arlington Collaborations in developing mouse models and molecular tools for ALS research

Thomas A. Cooperمشاهده پروفایل

دانشیار

• Solar Energy
• Thermal Science
• Optics
• +۵ مورد دیگر

Dr. Thomas A. Cooper is an Associate Professor at the Lassonde School of Engineering, York University, specializing in Mechanical Engineering. He focuses on solar energy systems, integrating thermal science, optics, and materials to develop technologies for solar energy conversion into electricity, heat, and fuels. His research has received international recognition through awards and fellowships. BASc (University of Toronto) MSc & DrSc (ETH Zurich) Research interests include solar concentrators, high-temperature materials, and thermochemical processes. His work spans fundamental and applied domains, such as radiation heat transfer , nonimaging optics , and CO2 capture materials . Recent publications highlight his innovation in solar thermal desalination, aerogel composites, and Martian dust conversion. Key article trends demonstrate expertise in concentrated solar power (2023), nonimaging optical design (2022), plasmonics (2017), and thermochemical redox cycles (2016). Collaborative projects with institutions like Synhelion AG and Toronto Metropolitan University emphasize interdisciplinary and industrial applications. ASME Solar Energy Graduate Student Award ETH Medal Hans Eggenberger Prize Chorafas Prize NSERC PGS-M/D Fellowships Swiss National Science Foundation Fellowship The CooperLab at York University houses advanced facilities for solar simulation, thermal testing, and spectroscopy. Active projects funded by NSERC, CFI, and Lassonde Innovation Fund explore photothermal materials, CO2 capture, and Martian resource utilization. The lab advises graduate researchers like Matteo Timpano and Niknaz Atashdehghan.

David Mouldمشاهده پروفایل

استاد

• Computer Graphics
• Computer Games
• Non-Photorealistic Rendering
• +۴ مورد دیگر

David Mould is a Professor in the School of Computer Science at Carleton University. His research focuses on computer graphics, procedural modeling of natural phenomena, non-photorealistic rendering, and computer games. He holds a PhD from the University of Toronto (2002), MSc from the University of Saskatchewan (1996), and BSc from the University of British Columbia (1994). PhD: University of Toronto (2002) MSc: University of Saskatchewan (1996) BSc: University of British Columbia (1994) Research interests include procedural modeling of trees, lightning, and terrain; image stylization techniques such as stained glass transformation and wax crayon simulation; and nonlinear storytelling in games. His work emphasizes algorithmic innovation and perceptual quality in graphics. Recent publications span topics like texture synthesis, real-time video stylization, and fluid animation techniques. He leads the Graphics, Imaging, and Games (GIGL) research group at Carleton. Teaching responsibilities include courses in game development (COMP 1501–4501), technical writing (COMP 3301), and graduate courses on game design and image processing.

Fei Liuمشاهده پروفایل

استادیار

• Robotics
• Surgical Robotics
• Medical Robotics
• +۳ مورد دیگر

Fei Liu is an Assistant Professor in the Min H. Kao Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville. His research focuses on surgical robotics, medical robotics, and control systems. He holds a PhD in Robotics from the University of Lyon (INSA de Lyon), France, an MSc in Control Systems and Automation Engineering from INSA de Lyon, and a BSc in Control Systems and Automation Engineering from Northwestern Polytechnical University, China. Fei's research interests include autonomous robotic systems, deformable object manipulation, and perception frameworks for surgical applications. His work emphasizes bridging real-world and simulation environments through advanced modeling and control techniques. Recent projects involve optimizing robotic actions using multi-modal demonstrations, improving tool-tissue interaction tracking, and developing frameworks for boundary parameter estimation in surgical settings. His articles highlight contributions to surgical robotics, including real-to-sim matching of deformable tissues, autonomous suturing, and trajectory optimization for wound care. He has also explored applications in haptic training systems and medical telerobotics. Fei's work often combines machine learning, physics-based simulation, and real-time control to address challenges in robotic surgery. Fei is affiliated with the Tickle College of Engineering and maintains an active research profile with collaborations in robotics and medical engineering domains. His lab focuses on advancing robotic autonomy in healthcare environments through interdisciplinary approaches.

Naglaa Elagamyمشاهده پروفایل

دانشیار

• Advanced Composite Materials
• Micro Computed Tomography (micro-CT)
• Stress Simulation
• +۶ مورد دیگر

Naglaa Elagamy is an Associate Teaching Professor in the Department of Mechanical and Manufacturing Engineering at Ontario Tech University. She holds a Ph.D. in Mechanical Engineering from Carleton University (2015), an M.A.Sc. in Engineering from Alexandria University (2002), and a B.Sc. in Engineering from the same institution (1994). As a licensed Professional Engineer (P.Eng.) in Ontario (2016–present) and a Certified SolidWorks Associate (CSWA), her expertise spans advanced composite materials, micro-CT imaging, stress simulation, and fatigue assessment of composite structures. Her research focuses on predicting progressive damage in materials and applying micro-CT for quantitative and qualitative damage analysis in carbon fiber reinforced polymers (CFRP). She has also explored aerodynamic performance optimization of small unmanned aerial vehicles (UAVs) through propeller design studies. Elagamy’s publications and presentations emphasize interdisciplinary approaches, combining experimental techniques like micro-CT with computational methods such as the Cohesive Zone Model and Finite Element Analysis. Her work addresses challenges in composite material durability, structural integrity, and multi-mode fatigue behavior. Beyond research, she contributes to teaching core mechanical engineering courses, including Kinematics and Dynamics of Machines, Statics, Solid Mechanics, and Computer-aided Design. Her professional recognitions include the Carleton University Development Grant (2014) and the AUD Recognition for Services (2018). Her advising and grants activities are not explicitly detailed here, but she has secured funding for her research at Carleton University. She is affiliated with the Faculty of Engineering and Applied Science and collaborates with industry and academic conferences such as SAMPE and CAMX. While specific lab affiliations are not mentioned, her research aligns with cutting-edge structural and materials analysis within the department.