جستجوی استاد راهنمای دانشگاهی

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.

Jianxi Gaoمشاهده پروفایل

دانشیار

• Network Science
• Artificial Intelligence
• Control Theory
• +۳ مورد دیگر

Jianxi Gao is an Associate Professor in the Department of Computer Science at Rensselaer Polytechnic Institute (RPI). His research focuses on network science, particularly network resilience, robustness, and control, integrating network theory, control theory, statistical physics, and operations research. He also explores the intersection of network science and AI, including applications of AI to network analysis and vice versa. His work aims to understand, predict, and control the resilience of complex systems against cascading failures. Key research areas include network resilience in transportation systems, quantum networks, and biological systems, with applications to pandemic response and infrastructure optimization. Gao's contributions span theoretical frameworks and computational tools, such as the NuRsE MATLAB package for network resilience analysis. His GitHub repositories (e.g., NuRsE and NON) showcase his open-source contributions to network science and computational methods. His recent publications address topics like AI-driven network analysis, quantum network percolation, and pandemic-induced healthcare system stress. He actively collaborates on interdisciplinary projects, emphasizing real-world applications of network science principles.

M. Tariq Iqbalمشاهده پروفایل

استاد

• Hybrid Power Systems
• Renewable Energy Systems
• Consumer Electronics
• +۱ مورد دیگر

M. Tariq Iqbal is a Professor in the Department of Electrical and Computer Engineering at Memorial University of Newfoundland. He holds a B.Sc. from UET Lahore, M.Sc. from QAU Islamabad, and PhD from Imperial College London. His research develops renewable energy solutions including hybrid power systems, solar applications, and IoT-based monitoring. Projects focus on off-grid communities, industrial applications, and energy-efficient electronics. Specific interests include microgrid design, solar water pumping, and power consumption analysis. Recent publications emphasize techno-economic modeling of microgrids, IoT-enabled SCADA systems, and energy efficiency in computing. Work demonstrates increasing focus on practical implementations in remote locations. No scientific awards are documented. Iqbal advises graduate students on projects across 20+ countries. Current research includes solar-powered oil pumps, electric vehicle charging, and community microgrids. He directs multiple projects through the faculty's engineering design initiative.

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.

Jonathan Clarkمشاهده پروفایل

استاد

• Robotics
• Legged Locomotion
• Dynamic System Analysis
• +۴ مورد دیگر

Dr. Jonathan Clark is a Professor and Director of the CISCOR at the FAMU/FSU College of Engineering's Department of Mechanical Engineering. His research focuses on bioinspired robotics, legged locomotion, and mechanical design, emphasizing robots for unstructured environments. He holds a Ph.D. (2004), M.S. (2000), and B.S. (1998) in Mechanical Engineering from Stanford University and Brigham Young University, respectively. Key research areas include dynamic climbing robots, compliant leg design, and shape deposition manufacturing. Notable projects involve the Sprawl family of robots and the development of multimodal robots like STARQ and Aquaclimber. His work bridges biomechanics and robotics, with applications in rescue, exploration, and industrial automation. Publications emphasize gait optimization, material science for robotics, and energy-efficient locomotion. Recent trends include bioinspired swimming robots and terrain-adaptive systems. Clark collaborates with biologists and engineers to advance robotics in complex environments. He advises on grants relating to dynamic systems and robotics education, and leads CISCOR's initiatives in advanced manufacturing and robotics innovation. Labs and teams include the CISCOR facility, focusing on prototyping and testing next-generation robotic platforms.

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.

Fernando Lopez-Lezcanoمشاهده پروفایل

مدرس

• Computer Music
• Spatial Audio
• 3D Sound Diffusion
• +۶ مورد دیگر

Fernando Lopez-Lezcano is a Lecturer at Stanford University's Center for Computer Research in Music and Acoustics (CCRMA) where he has been working since 1993. His work combines music composition, electronic engineering, and programming with a focus on spatial audio and sound diffusion technologies. He was the Edgar Varese Guest Professor at TU Berlin during the Summer of 2008 and is the 2014 winner of Stanford's Marsh O'Neill Award for Exceptional and Enduring Support of Stanford University's Research Enterprise. Lopez-Lezcano's research interests center on computer music, spatial audio technologies, and sound diffusion systems. He has pioneered work in High Order Ambisonics (HOA), developing novel decoders and reverberation architectures for immersive sound environments. His work on the SpHEAR Project has created innovative 3D-printed soundfield microphone arrays, while his development of the GRAIL (Giant Radial Array for Immersive Listening) has revolutionized concert speaker arrays for HDLAs (High Density Loudspeaker Arrays). He has also created numerous open-source tools and software environments for spatial sound composition and diffusion. His recent creative output demonstrates a consistent exploration of 3D sound spatialization, modular synthesis, and interdisciplinary collaborations. Across his compositions, he frequently integrates custom-built hardware like his modular synthesizers (including the famous 'El Dinosaurio' built in 1980-81) with sophisticated software environments written in SuperCollider. His work often bridges acoustic and electronic sound sources, creating rich spatial experiences that explore the relationship between technology and artistic expression. Among his notable achievements is the 2014 Marsh O'Neill Award, recognizing his exceptional support of Stanford's research enterprise. This prestigious award was inspired by Marsh O'Neill, Associate Director of the W.W. Hansen Laboratories, and honors outstanding staff members who support faculty research activities. Lopez-Lezcano has mentored numerous students in the development of musical instruments and performance systems, most notably the 'Ensemble AnaLocos' (Analógicos Locos or 'Crazy Analogs') which created the 'Noise Toaster' synthesizers. He has also developed important infrastructure for CCRMA including 'Planet CCRMA,' a collection of open-source audio software for Linux. His teaching includes the 'Sound in Space' course (Music 222), which covers historical background, techniques, and theory on the use of space in music composition and diffusion. He directs the CCRMA Stage concerts and has been instrumental in developing CCRMA's spatial audio infrastructure, including the GRAIL system used in Bing Concert Hall. His work with the SpHEAR Project has advanced 3D sound recording techniques, while his collaborations with performers like Michiko Theurer (violin) and Chris Chafe (celletto) have produced innovative interdisciplinary performances.

Peter Molnarمشاهده پروفایل

استاد

• Hydrology
• Geomorphology
• Sediment Dynamics
• +۷ مورد دیگر

Peter Molnar is a Professor at ETH Zürich's Department of Civil, Environmental and Geomatic Engineering, where he leads research in hydrology, geomorphology, and environmental engineering. His work spans river basin dynamics, sediment transport, precipitation modeling, and climate-water interactions, with field sites focused on Alpine systems. His research interests center on river basin water and sediment dynamics , precipitation analysis and stochastic modeling , fluvial systems including river networks and riparian zones , and geomorphic processes in mountain streams . Key projects include the Maggia River Experimental Site, basin sediment cascade modeling, and hydroclimatic analysis of rainfall intensity-temperature relationships. His publication record shows consistent high-impact work in journals including Nature , Nature Climate Change , and Water Resources Research , with recent focus on climate change impacts, sensor development, and sustainable agriculture. Golden Owl Award for best teaching (2011) Organizer of international workshops on geomorphology complexity and urban precipitation Patron of CometX initiative Molnar actively mentors PhD students including current candidates working on droughts in Ethiopia, Alpine Rhine sediment budgets, and mountain ecohydrology. His research is supported by Swiss National Science Foundation grants, ETH funding, and international collaborations. He leads experimental work at the Maggia River site and develops warning systems for rainfall-triggered landslides.

Carlos Silvera Batistaمشاهده پروفایل

استادیار

• Chemical Engineering
• Materials Science
• Nanotechnology
• +۳ مورد دیگر

Carlos Silvera Batista is an Assistant Professor of Chemical and Biomolecular Engineering at Vanderbilt University’s School of Engineering. His research focuses on manipulating colloidal systems to design functional materials, emphasizing nanoscale interactions and electrokinetic phenomena. He holds a Ph.D. from the University of Florida and a B.E. from City College of New York. Education: Ph.D., Chemical Engineering, University of Florida B.E., Chemical Engineering, City College of New York Research Interests: Dr. Batista investigates the forces and flows governing colloidal assembly, with applications in nanomedicine, energy, and materials science. Key areas include solvation forces in nanoscale systems, electrokinetic transport of anisotropic colloids, and the directed assembly of reconfigurable materials. Techniques such as analytical ultracentrifugation and confocal microscopy are central to his work. Articles Trends: Recent work emphasizes electrodiffusiophoresis-driven colloidal dynamics, long-range transport of charged particles, and applications in CRISPR delivery and structural materials. His studies bridge fundamental physics with practical applications in biomedicine and nanotechnology. Awards: None explicitly listed. Advising & Grants: No advisees listed. Received the NSF CAREER Award (2023) for research on colloidal dynamics under electrodiffusiophoresis. Labs & Teams: Leads the Colloids & Interfacial Phenomena lab, part of Vanderbilt’s Nano Science and Technology intellectual neighborhood. Focus areas include colloidal dispersions, nanomaterials, and interfacial phenomena.

Eugene Vinitskyمشاهده پروفایل

استادیار

• Reinforcement Learning
• Multi-agent Learning
• Autonomous Vehicles
• +۲ مورد دیگر

Eugene Vinitsky is an Assistant Professor at NYU Tandon School of Engineering, holding joint appointments in Civil and Urban Engineering and Computer Science. His research develops multi-agent reinforcement learning systems for autonomous vehicles and traffic control, with applications in robotics and intelligent infrastructure. He directs the Computational Transportation Systems Lab and leads projects like CIRCLES on congestion reduction. Research Focus: Designs algorithms enabling complex behaviors through unsupervised agent interactions, human-AI compatibility, and environment synthesis for autonomous systems. Awards & Leadership: NSF Graduate Fellow (2016), Eisenhower Fellow (2018, 2020), and PI on multiple grants including Amazon Research Awards. Mentored 14+ graduate students and organized international RL conferences.

Jia Wuمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Data Mining
• Deep Learning
• +۷ مورد دیگر

Dr. Jia Wu is an Associate Professor and Research Director of the Centre for Applied Artificial Intelligence at Macquarie University. He holds a PhD in Computer Science from the University of Technology Sydney (2009) and is an IEEE Senior Member. His research focuses on artificial intelligence, data mining, graph neural networks, and anomaly detection, with over 200 publications in top-tier journals/conferences like IEEE TPAMI, TKDE, and conferences like KDD, IJCAI, and NeurIPS. He has received awards including the Heidelberg Laureate Forum Fellowship (2019) and multiple best paper awards. Education: PhD in Computer Science (UTS, 2009). Current roles include Director of HDR (Higher Degree Research) and Associate Editor for IEEE TNNLS and ACM TKDD. He leads projects in AI-driven cybersecurity, personalized banking solutions, and disaster response systems. Research interests emphasize graph-based learning, fake news detection, and deep learning applications. His recent work explores hypergraph neural networks for fraud detection and brain graph analysis for neurological disorders. He has pioneered scalable semi-supervised clustering techniques and transformer-based hypergraph models for anomaly detection. Awards include CIKM'22 Best Paper Runner-Up, ICDM'21 Best Student Paper, and the 2023 Faculty of Science and Engineering Collaboration Award. His work spans 13 active research projects, including mitigating AI deepfakes in identity systems and enhancing disaster response networks through graph-based simulations. Labs/Teams: Leads teams in the Data Horizons Research Centre, Future Communications Research Centre, and Hearing Research Centre. Collaborates internationally in AI, data mining, and social network analysis.

Raja Jurdakمشاهده پروفایل

استاد

• Distributed Systems
• Blockchain Technology
• Network Modeling
• +۷ مورد دیگر

Professor Raja Jurdak is a leading academic in distributed systems and applied data sciences at Queensland University of Technology (QUT), where he directs the Trusted Networks Lab. He holds dual roles as Professor of Distributed Systems and Chair in Applied Data Sciences, alongside leadership in the Centre for Data Science. His research focuses on dynamic network modeling, blockchain-based trust frameworks, and IoT applications, with particular emphasis on cybersecurity, energy efficiency, and mobility-driven diffusion processes. Jurdak formerly led CSIRO's Distributed Sensing Systems Group and maintains a visiting scientist role there. Education: PhD in Information and Computer Science, University of California, Irvine MS in Computer Networks and Distributed Computing, University of California, Irvine BE in Computer and Communications Engineering, American University of Beirut Research Interests: Network science, blockchain technology, IoT security, sustainable energy systems, and data-driven decision-making. His work bridges theoretical advancements with practical applications in smart grids, health surveillance, and urban mobility. Awards: Finalist for the 2019 Eureka Prize, multiple CSIRO accolades, and IEEE Senior Member status. His research has received industry recognition for interdisciplinary innovation, including the DiNeMo project's real-time disease surveillance system. Advisory & Grants: Leads high-impact projects funded by government and industry partnerships. Supervises PhD candidates in areas like decentralized data processing and privacy-preserving AI. Holds editorial roles at journals such as Ad Hoc Networks and PLoS ONE . Labs & Teams: Directs the Trusted Networks Lab at QUT, fostering collaborations with institutions like Oxford University and MIT. His work emphasizes cross-disciplinary teams to address global challenges in cybersecurity and sustainable systems.

Vikrant Vazeمشاهده پروفایل

دانشیار

• Transportation Optimization
• Aviation Systems
• Healthcare Analytics
• +۳ مورد دیگر

Vikrant Vaze is the Stata Family Career Development Associate Professor and Executive Director of the Master of Engineering Management Program at Dartmouth's Thayer School of Engineering. He leads research in transportation systems, aviation optimization, and healthcare analytics, developing data-driven solutions for complex logistics challenges. His work integrates game theory, statistical modeling, and large-scale optimization. Research spans sustainable urban mobility, airline disruption recovery, multimodal pricing alliances, and healthcare operations. Articles consistently focus on optimization algorithms for real-world transportation and healthcare systems, with recent emphasis on electric aerial mobility and pandemic-responsive logistics. Major Awards: INFORMS Aviation Applications Best Paper (2024, 2023) AGIFORS Best Innovation Award (2024) NSF CAREER Award (2018) President of India Gold Medal As founding co-director of the Operations Research Group, he collaborates with industry partners like Multivariate Systems to translate academic research into deployable solutions.

Binil Starlyمشاهده پروفایل

استاد مدعو

• Digital Manufacturing
• Additive Manufacturing
• Tissue Biofabrication
• +۵ مورد دیگر

Binil Starly is an Adjunct Professor at North Carolina State University's Edward P. Fitts Department of Industrial and Systems Engineering, part of the College of Engineering. He leads the Data Intensive Manufacturing Laboratory (DIME Lab), focusing on digital-physical integration in manufacturing, additive manufacturing, and biofabrication. His work emphasizes democratizing manufacturing access through machine learning and smart systems. Starly holds a B.S. in Mechanical Engineering from the University of Kerala (2001) and a Ph.D. from Drexel University (2006). He previously worked at the University of Oklahoma on tissue engineering platforms. His research spans digital factories, smart manufacturing, and biometrology, with over 45 journal publications. His awards include the NSF CAREER Award (2009), SME Young Manufacturing Engineer Award (2011), and multiple teaching/research recognitions at NC State. He teaches courses on product development, additive manufacturing, and Python for industrial engineers. Starly’s research trends emphasize blockchain in manufacturing ecosystems, cybersecurity for IoT devices, and knowledge graphs for service discovery. He co-leads the Functional Tissue Engineering (FTE) Program, integrating regenerative medicine with scalable manufacturing processes. His grants focus on smart manufacturing innovation, blockchain platforms, and real-time bioprinting monitoring. He advises 7 graduate and 3 undergraduate students, having guided 22 M.S. and 6 Ph.D. students. His outreach includes online courses on smart manufacturing and Python programming through NC State’s Wolfware Outreach. The DIME Lab develops advanced manufacturing technologies, including digital twins for industrial metaverse applications and machine authentication systems. Collaborations span academia, industry, and government to advance personalized manufacturing solutions.