جست‌وجوی استاد و پژوهشگر

Tho Leمشاهده پروفایل

استادیار

• Transportation Modeling
• Logistics and Supply Chain Optimization
• AI/Machine Learning Applications
• +۶ مورد دیگر

Tho Le is a tenure-track Assistant Professor of Industrial Engineering Technology at Purdue University’s School of Engineering Technology. He leads the Smart Logistics (SmartLogs) Systems Research Lab and is affiliated with the Institute for Control, Optimization, and Network (ICON), Realizing the Digital Enterprise (RDE) initiative, Integrative Data Science Initiative (IDSI), and Semiconductors @ Purdue. His research focuses on system-scale transportation modeling using optimization, AI/ML, and econometrics to guide industry and policy decisions. Education: Ph.D. in Transportation Systems, Purdue University MSc in Industrial Engineering (Operations Research), Purdue University M.Eng. in Transportation Engineering (Best Thesis Award), Hiroshima University Research Interests: Emerging technologies: sidewalk delivery robots, indoor service robots, drones Semiconductor supply chain resilience and Lean Six Sigma applications Digital twins for logistics systems and fleet management Freight transport, connected/autonomous vehicles, travel behavior modeling Awards & Recognition: Recipient of National Science Foundation grant for energy efficiency modeling (2024) Polytechnic Research Awards (July 2024) Lab & Collaboration: SmartLogs Lab: develops data-driven solutions for urban logistics and asset management Leadership in Purdue’s semiconductor initiatives aligned with the CHIPS Act

Keith LeGrandمشاهده پروفایل

استادیار

• Multi-sensor Multi-object Tracking
• Spacecraft Navigation
• Space Domain Awareness
• +۵ مورد دیگر

Keith LeGrand is an Assistant Professor in the School of Aeronautics and Astronautics at Purdue University, part of the Cislunar Space Initiative. He holds a Ph.D. in Aerospace Engineering from Cornell University (2022), an M.S. (2015), and a B.S. (2014) in Aerospace Engineering from Missouri University of Science and Technology. His research focuses on multi-object tracking, spacecraft navigation, space domain awareness, and intelligent sensor control. Key projects include developing probabilistic filters for cislunar space object tracking and information-driven autonomy systems. LeGrand leads the Sensing, Controls, and Probabilistic Estimation (SCOPE) Group, which advances space surveillance and autonomous systems. Notable awards include the 2025 AFOSR and ISIF Young Investigator Awards, 2023 AMOS Best Paper Award, and the E.F. Bruhn Teaching Award for excellence in undergraduate instruction. LeGrand advises a diverse group of graduate and undergraduate students in astrodynamics and space applications. His work is supported by grants from AFOSR, ISIF, and partnerships with institutions like Sandia National Laboratories and Draper Labs. The SCOPE lab collaborates on projects such as lunar landing navigation, satellite proximity operations, and multi-sensor fusion for space surveillance.

• Intelligent Transportation Systems
• Automated Vehicles
• Control Systems
• +۶ مورد دیگر

Lingxi Li is a Professor at the Elmore Family School of Electrical and Computer Engineering at Purdue University's Indianapolis campus. His research focuses on modeling complex systems, connected and automated vehicles, intelligent transportation systems, and parallel intelligence. He holds a Ph.D. from the University of Illinois at Urbana-Champaign (2008), and master's and bachelor's degrees from the Chinese Academy of Sciences (2003) and Tsinghua University (2000). Research Interests: Dr. Li's work bridges control systems, transportation engineering, and AI, with emphasis on human-machine interaction, autonomous vehicle systems, and scenario-based traffic modeling. His projects include developing frameworks for Industry 5.0 collaboration, enhancing traffic flow prediction through parallel learning, and advancing safety in micro-mobility systems like e-scooters. Recent Publications: Over 15+ articles (2023-2025) explore topics such as game-theoretic vehicle interaction modeling, vision-language systems for autonomous driving, and acoustic SLAM technologies. These studies reflect a focus on real-world validation and system integration in smart transportation. Labs & Initiatives: Leads research in autonomous mining systems and scenario engineering for intelligent vehicles, leveraging parallel intelligence concepts. Collaborates on projects like ParallelWorkforce (Industry 5.0 frameworks) and SceNDD++ (naturalistic driving datasets).

• Machine Learning
• Natural Language Processing
• Medical Informatics
• +۳ مورد دیگر

Stefan Riezler is a full professor of Statistical Natural Language Processing at Heidelberg University's Department of Computational Linguistics (since 2010), affiliated with the Faculty of Mathematics and Computer Science. Prior to this, he worked in Silicon Valley at Xerox PARC and Google Research. He holds a PhD in Computational Linguistics from the University of Tübingen (1998) and conducted postdoctoral research at Brown University (1999). His research spans machine learning, NLP, and medical informatics, focusing on interactive statistical learning. He co-leads the Interdisciplinary Center for Scientific Computing (IWR) and serves on the editorial boards of Computational Linguistics and Transactions of the Association for Computational Linguistics . Key research areas include neural machine translation, healthcare AI (e.g., sepsis prediction), data augmentation, and reproducibility in ML. He develops tools like JoeyNMT and explores ethical challenges in clinical machine learning. Notable recent work includes advancements in time series analysis, multimodal interfaces (e.g., NLMaps for OpenStreetMap), and ethical frameworks addressing validity in healthcare ML. His publications emphasize practical applications of NLP in healthcare, speech translation, and cross-lingual systems. Grants and collaborations include interdisciplinary projects on medical data science and training next-gen NLP researchers. He actively contributes to open-source toolkits and reproducible research practices.

Chuchu Fanمشاهده پروفایل

دانشیار

• Formal Methods
• Control Theory
• Machine Learning
• +۳ مورد دیگر

Chuchu Fan is the Leonardo Career Development Professor and Director of the REALM Lab (REliable Autonomous system Lab) at MIT's School of Engineering , with a primary appointment in the Department of Aeronautics and Astronautics and Laboratory for Information and Decision Systems . Her work bridges formal methods , control theory , and machine learning to ensure safety in autonomous systems. Ph.D., University of Illinois at Urbana-Champaign (2019) B.E., Tsinghua University (2013) Her research focuses on rigorous safety verification of autonomous systems through neural Lyapunov-barrier functions , control contraction metrics , and formal logic specifications . Recent work emphasizes LLM integration for symbolic planning, multi-robot collaboration , and robustness against model uncertainties . The 15 most recent articles highlight trends in safety-critical control using graph neural networks , reinforcement learning , and temporal logic . Key themes include collision avoidance , multi-agent coordination , and runtime safety filters applied to drones, self-driving cars, and microgrids. Scientific Awards & Honors : 2025 ONR YIP Award 2023 NSF CAREER & AFOSR YIP Awards 2020 ACM Doctoral Dissertation Award 2016 Rising Stars in EECS As head of the REALM Lab, she leads projects on autonomous air taxis , safety verification , and neural certificates for robotic systems. Her teaching includes courses on feedback control and formal methods for autonomous systems.

Wooram Parkمشاهده پروفایل

دانشیار

• Robotics
• Biomedical Robotics
• Computational Structural Biology
• +۳ مورد دیگر

Wooram Park is an Associate Professor in the Department of Mechanical Engineering at the University of Texas at Dallas (UT Dallas), affiliated with the Erik Jonsson School of Engineering and Computer Science. He leads the Robotics and Intelligent Systems Laboratory (ROBINS Lab) and holds a PhD from Johns Hopkins University (2008), along with MS and BS degrees from Seoul National University (2003 and 1999). His research focuses on robotics, biomedical robotics, computational structural biology, and image processing. Key projects include flexible needle steering for medical applications, haptic feedback systems, and advanced algorithms for motion planning and image reconstruction. He has received notable awards such as the Creel Fellowship (2007) and Critics’ Choice Award in ArtBot Design (2004). His work spans theoretical contributions in stochastic systems and practical innovations like vibratory magnetic robots (Vimbot) and wearable haptic devices. The ROBINS Lab emphasizes interdisciplinary research at the intersection of mechanical engineering, computer science, and biomedical applications.

Suresh Khatorمشاهده پروفایل

استاد

• Modeling of Energy Systems
• Health Care Systems
• Manufacturing Systems
• +۳ مورد دیگر

Suresh Khator is a Professor and Senior Associate Dean for Graduate Programs and Computing Facilities at the University of Houston's Cullen College of Engineering, Department of Industrial and Systems Engineering. He holds a Ph.D. in Industrial Engineering from Purdue University and has extensive experience in academia, industry, and administrative roles. His research focuses on modeling energy, healthcare, and manufacturing systems, facilities design, production planning, and project management. He has supervised 10 PhD dissertations and 37 Master's theses, and his work has been published in top-tier journals and conferences. Khator has received numerous awards, including the Fellow of IISE and multiple teaching excellence awards. His administrative roles include Director of Engineering Computing and Interim Associate Dean at the University of South Florida. He has also contributed to community initiatives, such as science fairs and outreach programs. His articles span power systems resilience, renewable energy integration, and manufacturing automation. He has led over 30 grants and contracts, including projects with the Florida Department of Transportation and utility companies.

Tingkai Wangمشاهده پروفایل

مدرس ارشد

• Mobile Robots
• Intelligent Systems
• Artificial Intelligence (AI)
• +۵ مورد دیگر

Dr. Tingkai Wang is a Senior Lecturer in the School of Computing and Digital Media at London Metropolitan University. His research focuses on mobile robots, intelligent systems, artificial intelligence, control systems, image/signal processing, and virtual reality. He teaches the Programming for Computer Science module and has led projects like the Virtual Environment and Simulation System (2000-2002) and Navigation and Control of Mobile Robots (1995-1998). His work emphasizes interdisciplinary approaches, combining expert systems, neural networks, and fuzzy logic to address challenges in autonomous systems. Notable contributions include AGV navigation algorithms, hybrid control systems, and predictive modeling. Over 30 publications span robotics, control engineering, and AI applications. He collaborates internationally and has presented at venues like the International Conference on Intelligent Systems Engineering and the IEEE Conference on Engineering in Medicine and Biology. Dr. Wang’s expertise bridges theoretical modeling and practical implementation, with applications in manufacturing automation, environmental monitoring, and industrial management systems. His current research continues exploring adaptive control mechanisms and AI-driven robotics solutions.

• Fluid Power (Hydraulics)
• Acoustic Sensing
• Dynamic Modelling
• +۴ مورد دیگر

Travis Wiens is an Associate Professor in the Department of Mechanical Engineering at the University of Saskatchewan. His research focuses on fluid power systems, acoustic sensing, dynamic modeling, mining mechatronics, and artificial intelligence applications in engineering. He holds a B.Sc., M.Sc., and Ph.D. in Mechanical Engineering from the same institution, completed in 2002, 2004, and 2008 respectively. His research interests emphasize innovative solutions for hydraulic control systems, pipeline resonance reduction, and mining safety through acoustic technologies. He has developed low-cost electrohydrostatic actuators and explored additive manufacturing in valve design. Notable contributions include vibrational data communication tools for extractive industries and machine learning models for mine roof stability assessment. Dr. Wiens teaches ENGC 01A - Introduction to Fluid Power Components . His work bridges theoretical fluid dynamics with practical applications in energy efficiency, structural health monitoring, and biomimetic systems. Ongoing research trends include integrating AI with hydraulic systems and advancing non-destructive testing methods for infrastructure integrity. His publications highlight interdisciplinary approaches, combining mechanical engineering principles with computational modeling, neural networks, and mechatronics. Collaborative efforts focus on mining safety, oil and gas infrastructure, and sustainable hydraulic technologies.

Gabor Oroszمشاهده پروفایل

استاد

• Nonlinear dynamics and control
• Time delay systems
• Connected and automated vehicles
• +۶ مورد دیگر

Gabor Orosz is a Professor at the University of Michigan in both the Department of Mechanical Engineering and Department of Civil and Environmental Engineering . His work bridges nonlinear dynamics and control , time delay systems , and connected automated vehicles , with a focus on traffic flow optimization and vehicle safety . Education: PhD in Engineering Mathematics, University of Bristol, UK (2006) MSc in Engineering Physics, Budapest University of Technology and Economics, Hungary (2002) Research Focus : Orosz's research explores the intersection of vehicle automation , connectivity , and nonlinear dynamics . He investigates time delay effects in teleoperation , intent-sharing protocols for cooperative maneuvering , and control barrier functions for safety-critical systems . His work spans theoretical analysis, numerical validation, and real-world experimentation. Article Trends : Recent publications highlight advancements in latency mitigation for remote driving , nonholonomic vehicle control , intent-sharing frameworks , and energy-efficient strategies for connected vehicle systems . Themes include delayed feedback , stochastic communication , and safety-guaranteed control . Awards & Appointments : NSF CAREER Award (2014) Fulbright Scholar at Budapest University of Technology (2023-2024) Editorial roles in Vehicle System Dynamics (2020) and Time Delay Systems (2017) Student Mentorship : Orosz has advised numerous PhD students, including Anil Alan (2024, TU Delft), Chaozhe He (2018, University at Buffalo), and Tamás Molnár (2020, Wichita State University). His alumni work at institutions like Toyota Research Institute , Ford Motor Co. , and Zoox . Labs & Teams : He leads research at the University of Michigan's Mechanical Engineering Department and collaborates with international institutions such as Caltech and Budapest University of Technology . His team focuses on experimental validation of connected vehicle systems and delay-tolerant control .

Karen Mullenersمشاهده پروفایل

دانشیار

• Fluid Dynamics
• Unsteady Flow Phenomena
• Bio-inspired Robotics
• +۴ مورد دیگر

Karen Mulleners is an Associate Professor at the École polytechnique fédérale de Lausanne (EPFL), affiliated with the School of Engineering (STI), the Institute of Mechanical Engineering (IGM), and the UNFOLD Laboratory (Laboratoire de diagnostic des écoulements instationnaires). She also serves in the SGM-ENS teaching department and is a member of the EDEY-GE doctoral program commission. Her research focuses on experimental fluid dynamics, particularly unsteady flow phenomena and vortex dynamics. Professor Mulleners specializes in the intersection of fluid dynamics and bio-inspired engineering, with research interests including: Unsteady vortex-dominated flow phenomena Fluid-structure interaction in flexible systems Experimental methods for flow visualization and measurement Application of fluid dynamics principles to bio-inspired robotics Aerodynamic performance optimization of wind turbine systems Vortex dynamics in flapping and rotating wing systems Her recent publications (2022-2025) demonstrate a strong experimental focus on understanding complex fluid phenomena, particularly in bio-inspired robotics and renewable energy applications. Mulleners' work consistently addresses fundamental questions about vortex formation, flow control, and fluid-structure interactions, with significant contributions to understanding dynamic stall in wind turbines and undulatory swimming mechanics. Her research group employs advanced diagnostic techniques to study unsteady flows, often bridging engineering and biological principles. Professor Mulleners actively supervises PhD students and has directed multiple EPFL theses. Her teaching responsibilities include courses on Measurement Techniques and Aerodynamics, where she imparts knowledge on experimental methods for observing and measuring physical variables such as force, resistance, temperature, flow velocity, and structural deformation. The UNFOLD Laboratory, which Professor Mulleners leads, focuses on diagnostic techniques for unsteady flow phenomena, employing advanced experimental methods including flow visualization, particle image velocimetry, and force measurement systems to study complex fluid dynamics problems with applications in renewable energy and bio-inspired engineering.

Kais Atallahمشاهده پروفایل

استاد

• Electromechanical Energy Conversion
• Magnetic Torque/Force Transmission Systems
• Renewable Energy Systems
• +۴ مورد دیگر

Professor Kais Atallah is a Professor in Electrical Engineering at the University of Sheffield's School of Electrical and Electronic Engineering, with a secondary role as a Lecturer in Aerospace Engineering. He joined the University in 1989 as a PhD student and became academic staff in 2000. His research focuses on electromechanical energy conversion, magnetic torque systems, and applications in renewable energy, electric vehicles, and aerospace actuation. He is a member of the Centre for Research Into Electrical Energy Storage and Applications (CREESA) and leads the Electrical Machines and Drives Research Group. His research interests include novel drivetrain designs for wind turbines, flywheel systems, and fault-tolerant machine systems for safety-critical aerospace applications. He has advised multiple PhD students and contributed to over 150 publications, with recent work emphasizing magnetic gear design, high-performance ferrite machines, and modular multilevel converters. His articles explore themes like high-efficiency power transmission, magnetic gear optimization for wind turbines, and traction machine control systems. Collaborations include work on subsea ROV propulsion and flywheel energy storage. He oversees research labs focused on advanced electrical machine design and energy storage solutions.

Bayu Jayawardhanaمشاهده پروفایل

استاد

• Mechatronics
• Nonlinear Control Systems
• Robotics
• +۵ مورد دیگر

Prof. Bayu Jayawardhana is a Full Professor in Mechatronics and Control of Nonlinear Systems at the University of Groningen, affiliated with the Faculty of Science and Engineering. He leads the Jayawardhana Group focusing on opto-mechatronics and advanced nonlinear control theories. His roles include Director of Engineering and Scientific Director of the Engineering and Technology Institute Groningen. He holds editorial positions in journals like International Journal of Robust and Nonlinear Control and European Journal of Control . Education: PhD in Control and Power Group from Imperial College London (2006), M.Eng from Nanyang Technological University (2003), and B.Eng from Institut Teknologi Bandung (2000). Research interests span opto-mechatronics for high-tech systems, nonlinear control, and systems biology. Key projects include digital twins for energy optimization, control of ocean energy systems, and modeling of cryogenic actuators for telescopes. His work integrates AI and model-based methods for high-performance systems. Notable awards include the 2016 FSE Faculty Teacher of the Year Award and the Ben Feringa Impact Award (2020). He advises on ventures like Ocean Grazer B.V. and Sencilia B.V. Teaching includes graduate courses on nonlinear control, opto-mechatronics, and fitting dynamical models to data. His research labs include the Groningen Centre for Systems and Control and the Data Science and Systems Complexity Center.

Mehmet Öztürkمشاهده پروفایل

استاد

• Energy Harvesting
• Thermoelectrics
• Nanoelectronics
• +۵ مورد دیگر

Dr. Mehmet Öztürk is a Professor in the Department of Electrical and Computer Engineering at North Carolina State University. His research focuses on nanoelectronics, energy harvesting, and advanced materials for flexible electronics, particularly thermoelectric devices for body heat energy conversion. He holds a Ph.D. in Electrical Engineering from NC State, a Master’s from Michigan Technological University, and a Bachelor’s from Bogazici University. Dr. Öztürk’s research interests span Physical Electronics, Photonics, and Magnetics, with emphasis on novel materials and processes for thermoelectric generators and wearable technologies. His work includes developing flexible, high-efficiency thermoelectric systems using liquid metal interconnects and graphene-doped elastomers. Recent projects involve aerosol spray deposition techniques for stretchable electronics and optimizing materials for body heat harvesting systems. Key scientific contributions include analytical models for thermoelectric energy extraction, high thermal conductivity composites, and microporous CNT nanocomposites. His work bridges fundamental material science with applied engineering solutions for energy-efficient wearable devices. Awards: 2020 William F. Lane Outstanding Teaching Award 2009 IEEE Fellow for contributions to Si/SiGe epitaxy 2006 IEEE Undergraduate Teaching Award Lab Affiliations: Center for Advanced Self-Powered Systems of Integrated Sensors and Technologies (ASSIST)

Vijay K. Shahمشاهده پروفایل

استادیار

• Networking
• Communications
• Controls
• +۷ مورد دیگر

Vijay K. Shah is an Assistant Professor in the Electrical and Computer Engineering Department at North Carolina State University, leading the NextG Wireless Lab. His research focuses on advancing wireless communication and network technologies for beyond 5G/6G systems, including O-RAN architecture, spectrum management, and AI-driven network optimization. Education: Ph.D. in Computer Science, University of Kentucky (2019) Bachelor's in Computer Science and Engineering, National Institute of Technology, Durgapur (2013) Research emphasizes open radio access networks (O-RAN), mmWave testbeds, and cross-layer optimization. Recent work highlights include ORAN-Bench-13K (LLM benchmarking), ZT-RIC (zero-trust security frameworks), and Milli-O-RAN (reconfigurable mmWave networks). His contributions span O-RAN applications (xApps/rApps), satellite-terrestrial coexistence, and AI-driven positioning systems. Experimental validations include 3GPP-compliant 5G positioning and adversarial attack defenses. Publications reflect expertise in O-RAN architecture evolution, spectrum policy tools (ASCENT), and UAV-based network coordination (GLIDE). Current projects explore LEO satellite constellations and resilient disaster response networks. Labs/Teams: Head of the NextG Wireless Lab at NC State, focusing on prototype development in O-RAN, 6G, and secure AI-driven networks.