جست‌وجوی استاد و پژوهشگر

• Adaptive and robust control
• Nonlinear control
• Precision control
• +۴ مورد دیگر

Bin Yao is a Professor of Mechanical Engineering at Purdue University, located in West Lafayette, Indiana. He holds positions within the School of Mechanical Engineering and has affiliations with Purdue's broader Engineering College. His research focuses on adaptive and robust control systems, nonlinear control, precision mechanical systems, vehicle control, and robotics, with applications in human-machine interaction, transportation, and advanced robotics. Yao earned his B.Eng. from Beijing University of Aeronautics & Astronautics (1987), M.Eng. from Nanyang Technological University (1992), and Ph.D. from UC Berkeley (1996). He has received numerous awards, including the 2010 Changjiang Chair Professorship and the 2007 ASME Outstanding Young Investigator Award. His work emphasizes theoretical advancements in control systems and their practical implementation in industrial and robotic applications. Key research trends in his publications include precision motion control of gantry systems, adaptive strategies for hydraulic manipulators, and teleoperation systems with haptic feedback. His articles often bridge theoretical control methodologies with real-world mechanical systems, emphasizing robustness and adaptability. Awards: Over 10 prestigious awards spanning from 1985 to 2010, including international recognitions in control systems and academic excellence. Grants: Secured major funding through NSF CAREER Award (1998) and other industrial collaborations. His research lab focuses on advanced control systems integration in mechanical and robotic platforms, with ongoing projects in precision manufacturing and autonomous vehicle dynamics.

Mustafa Abdallahمشاهده پروفایل

استادیار

• Cybersecurity
• Artificial Intelligence
• Game Theory
• +۷ مورد دیگر

Mustafa Abdallah is an Assistant Professor at the Computer and Information Technology (CIT) department of Purdue University in Indianapolis, with a courtesy appointment at the Purdue Polytechnic Institute. He holds a PhD in Electrical and Computer Engineering from Purdue University (2022) and prior degrees from Cairo University (MS: 2016, BS: 2012). His research focuses on game theory, behavioral decision-making, explainable AI, and deep learning, applied to cybersecurity, autonomous systems, and IoT anomaly detection. His work has been recognized by the prestigious Bilsland Fellowship and grants from IEEE and IUPUI. Industrial collaborations include Adobe Research (meta-learning for time-series forecasting), Principal Financial Group (financial risk prediction using Kalman filters), and RDI Company (deep learning for pronunciation systems, resulting in a US patent). He has published extensively in top venues like IEEE S&P, IEEE TCNS, and ACM AsiaCCS.

Pierre Lermusiauxمشاهده پروفایل

استاد

• Ocean Data Assimilation
• Numerical Ocean Modeling
• Uncertainty Quantification
• +۷ مورد دیگر

Pierre Lermusiaux is the Nam Pyo Suh Professor of Mechanical Engineering and Associate Department Head for Operations Research at MIT. His research focuses on numerical ocean modeling, data assimilation, uncertainty quantification, and applications to ocean dynamics and engineering. He holds a B/M.Eng. from University of Liège, M.Sc. and Ph.D. from Harvard University. Recognized with awards like the MIT Doherty Chair and Spira Teaching Award, his work bridges computational science and marine systems. Education: B/M.Eng., University of Liège, 1992 M.Sc., Harvard University, 1993 Ph.D., Harvard University, 1997 Research Interests: Combines oceanographic modeling with advanced computational methods. Specializes in stochastic ocean prediction, autonomous systems optimization, and interdisciplinary applications of uncertainty quantification. His work enables real-time environmental forecasting and marine robotics navigation strategies. Publications: Focus on developing computational frameworks for probabilistic ocean forecasts, acoustic propagation modeling, and machine learning-based environmental prediction systems. Recent work emphasizes adaptive sampling strategies and energy-efficient path planning for underwater vehicles. Awards: Fulbright Foundation Fellowship (1993-96) Ruth and Joel Spira Award for Teaching (2010) MIT Doherty Chair in Ocean Utilization (2009-2011) Advising & Grants: Leads MIT’s MSEAS group and has secured funding from NSF, ONR, and international collaborations. Advises projects on ocean robotics, climate modeling, and underwater acoustics. Key contributions include the MIT Red Sea Modeling System and real-time forecasting platforms. Labs/Teams: Directs MIT’s multidisciplinary ocean modeling efforts, integrating mechanical engineering, computer science, and environmental science. Co-leads initiatives like the Ocean Predictions with Ensembles (OPEN) project and the METEOR autonomous observatory system.

Andrew Whyteمشاهده پروفایل

استاد

• Life-Cycle Analysis
• Civil Engineering
• Construction Project Management
• +۵ مورد دیگر

Professor Andrew Whyte serves as a faculty member in the School of Civil and Mechanical Engineering within the Faculty of Science and Engineering at Curtin University, Perth. His expertise spans civil engineering, sustainable infrastructure development, and construction management with a particular emphasis on life-cycle assessment methodologies. Professor Whyte maintains an active research profile with numerous international collaborations, especially with Malaysian institutions and industry partners across Southeast Asia. BSc, PhD (formal qualifications) Professor at Curtin University since at least 2000 Extensive international research collaborations Active participation in professional engineering organizations Professor Whyte's research interests focus on life-cycle analysis methodologies (LCA/LCCA) applied to civil infrastructure systems, with particular emphasis on sustainable materials, construction waste management, and transportation systems. His work bridges theoretical engineering principles with practical applications in sustainable construction practices, asset management, and infrastructure development. Recent research has expanded into autonomous vehicle integration, offshore engineering systems, and sustainable urban mobility solutions. Analysis of Professor Whyte's publication record reveals a consistent trajectory toward increasingly sophisticated life-cycle assessment methodologies applied across diverse infrastructure domains. His recent work demonstrates growing integration of computational modeling techniques with environmental and economic analysis, particularly in transportation systems and offshore engineering applications. The research shows strong industry relevance with practical applications in sustainable construction practices and infrastructure asset management. FICE (Fellow of the Institution of Civil Engineers) FIEAust (Fellow of the Institution of Engineers Australia) CPEng (Chartered Professional Engineer) NER (National Engineering Register) APECEngineer IntPE(Aus) (International Professional Engineer - Australia) Professor Whyte has secured substantial research funding from diverse sources including Australian government bodies, Malaysian research councils, and industry partners. His grant portfolio demonstrates expertise in translating academic research into practical engineering solutions, with particular strength in sustainable construction practices, offshore engineering systems, and infrastructure asset management. These projects often involve multi-institutional collaborations that bridge academic research with industry implementation.

• Computer Vision
• Applied Machine Learning
• Computer Graphics
• +۳ مورد دیگر

Fahim Hasan Khan is an Assistant Professor in the Computer Science and Software Engineering Department at California Polytechnic State University, San Luis Obispo (Cal Poly). His research focuses on computer vision, applied machine learning, and citizen science applications, with a special emphasis on environmental monitoring and education. He holds a PhD in Computer Science and Engineering from UC Santa Cruz, where he was advised by Professors Alex Pang and James Davis, and a Master's in Computer Science from the University of Calgary. Key research contributions include real-time rip current detection systems (RipFinder, RipScout), mobile citizen science platforms (SmartCS), and educational tools to engage high school students in STEM research. His work has received media attention for innovations in drowning prevention and environmental safety. Notable awards include the Best Poster Presentation Award at ICIAR 2019 and the Best of the Baskin School of Engineering Award at UC Santa Cruz in 2022. Dr. Khan collaborates extensively with industry and academic partners to develop practical solutions for challenges in marine safety, autonomous systems, and healthcare diagnostics. He actively mentors students and seeks to democratize access to machine learning tools through no-code platforms.

Truong Nghiemمشاهده پروفایل

دانشیار

• Intelligent cyber-physical systems
• Digital twins
• Scientific and physics-informed machine learning
• +۵ مورد دیگر

Truong Nghiem is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Central Florida (UCF), part of the College of Engineering and Computer Science. He holds a Ph.D. in Electrical and Systems Engineering from the University of Pennsylvania and previously served as an Assistant and Associate Professor at Northern Arizona University (2018–2024). His research focuses on intelligent cyber-physical systems, digital twins, physics-informed machine learning, and distributed optimization/control, with applications in smart buildings, autonomous vehicles, and robotics. He leads the intelligent Cyber-Physical Systems (iCPS) Lab, advancing foundational research in these areas. Notable awards include the NSF CAREER Award (2023) for composite physics-informed learning and the NSF ERI Award (2022) for building HVAC system research. He is a Senior Member of the IEEE and a member of the ACM. Recent work emphasizes safe machine learning for control systems, communication-efficient optimization algorithms, and physics-constrained motion prediction for autonomous systems. His publications span journals like IEEE Robotics and Automation Letters and conferences such as the American Control Conference. Grants and research initiatives include projects on HVAC system modeling, distributed trajectory planning for multi-vehicle systems, and adaptive sampling strategies for mobile sensor networks. Collaborations involve industry and academic partners in energy systems, robotics, and control engineering. The iCPS Lab’s work integrates theory, simulation, and real-world validation to address complex cyber-physical challenges.

Nirwan Ansariمشاهده پروفایل

استاد

• 6G Networks
• Wireless Charging
• Machine Learning
• +۵ مورد دیگر

Nirwan Ansari is a Distinguished Professor in the Department of Electrical and Computer Engineering at New Jersey Institute of Technology (NJIT). His research focuses on cutting-edge advancements in 6G networks , wireless charging , machine learning , and Internet of Things (IoT) . He has contributed extensively to AI-driven network optimization and sustainable energy solutions for next-generation communication systems. Ph.D., Electrical Engineering, Purdue University (1988) M.S., Electrical Engineering, University of Michigan-Ann Arbor (1983) B.S., Electrical Engineering, NJIT (1982) His recent work explores AI-native network slicing , UAV-assisted edge computing , and holographic communication . Publications highlight synergies between terrestrial and non-terrestrial networks , digital twin integration, and energy-efficient IoT systems . He serves as an Honorary Chair and contributes to major conferences like IEEE INFOCOM and IWCMC.

Qin Linمشاهده پروفایل

استادیار

• Autonomous Systems
• Control Systems
• Robotics
• +۵ مورد دیگر

Qin Lin is an Assistant Professor in the Department of Engineering Technology at the University of Houston's Cullen College of Engineering. Their research focuses on autonomous systems, control theory, and safety-critical applications. Lin holds a Ph.D. in Computer Science from Delft University of Technology (2015-2019) and completed a postdoctoral fellowship at Carnegie Mellon University's Robotics Institute (2019-2021). Research interests include safe reinforcement learning, fault-tolerant control systems, and cybersecurity for industrial control systems. Lin has published extensively on topics like vehicle autonomy, exoskeleton safety, and disturbance rejection in robotics. Their work emphasizes practical applications of control theory in autonomous driving, robotics, and human-robot interaction. Recent publications highlight advancements in control barrier functions, latency-aware autonomous systems, and data-driven anomaly detection in ICS environments. Lin has been recognized for contributions to curriculum development in engineering technology and maintains active collaborations in automotive and robotics domains.

Babak Mehranمشاهده پروفایل

دانشیار

• Transportation Network Resilience
• Big Data Analytics in Transportation
• Autonomous and Connected Vehicles
• +۴ مورد دیگر

Babak Mehran is an Associate Professor in the Department of Civil Engineering at the University of Manitoba (Price Faculty of Engineering). He holds a PhD in Civil Engineering from Nagoya University (2009). His research focuses on transportation network resilience, big data analytics, and AI-driven solutions for traffic management. He leads the Urban Mobility and Transportation Informatics Group (UMTIG), collaborating with government and industry on applied transportation research. Key research areas include autonomous vehicle integration, cold-region traffic vulnerability, and optimization of public transit systems. Dr. Mehran has advised graduate students on topics like traffic safety, sensor placement, and semi-flexible transit design. His work bridges theoretical models (e.g., reinforcement learning algorithms) with real-world applications such as winter road maintenance strategies and transit demand analysis. Recent publications emphasize AI-driven traffic prediction, climate adaptation for infrastructure resilience, and safety metrics for truck operations in harsh environments. He collaborates internationally on transportation policy and has contributed to methodologies for evaluating congestion relief strategies using travel time reliability analysis. Lab: Urban Mobility and Transportation Informatics Group (UMTIG) Key Partners: Government agencies, transportation industries, academic collaborators Current Focus: Autonomous shared mobility, cold-climate traffic systems, data fusion for traffic monitoring

Wei Shiمشاهده پروفایل

استاد

• Distributed computing
• Cloud computing
• Data center networks
• +۶ مورد دیگر

Professor Wei Shi is a faculty member at the School of Computer Science, Carleton University. His research focuses on distributed computing, cloud networks, algorithm design for sensor/actuator systems, big data analytics, and data privacy. Notable projects include federated learning optimizations, blockchain-enabled edge intelligence for IoT/vehicle networks, and AI-driven cybersecurity solutions. His work addresses challenges in dynamic resource allocation, anomaly detection, and privacy-preserving techniques. Research Interests: Distributed Computing: Optimizing federated learning and client selection algorithms for wireless networks. Blockchain & Edge Intelligence: Developing decentralized systems for IoT and vehicular networks using AI large models. Security & Privacy: Innovating methods to detect AI-generated content, combat cyber-physical attacks, and protect user data privacy. Publications: Recent works emphasize federated learning applications, blockchain integration with edge computing, and cybersecurity for vehicular/IoT ecosystems. Key themes include energy-efficient algorithms, dynamic resource allocation, and intrusion detection in constrained environments. Email: wei.shi@carleton.ca

Tony Whiteمشاهده پروفایل

استاد مدعو

• Artificial Intelligence
• Swarm Intelligence
• Genetic Algorithms
• +۴ مورد دیگر

Dr. Tony White is an Adjunct Professor in the School of Computer Science at Carleton University. He holds a Ph.D. from Carleton (2000), an M.A. from Cambridge, and a B.A. in Theoretical Physics. His research focuses on complex adaptive systems, including influence measurement in social networks and swarm intelligence applications. He leads the Complex Adaptive Systems Group and has extensive industry experience, previously working at Nortel. Education: Bachelor of Theoretical Physics, Cambridge University (1981) Master of Physics, Cambridge University (1981) Master of Computer Science, Carleton University (1993) Ph.D. in Electrical Engineering, Carleton University (2000) Research Interests: Artificial Intelligence Swarm Intelligence Genetic Algorithms Neural Networks Recommender Systems Search Engines His work explores influence dynamics in social networks, adaptive information systems, and evolutionary computation. Recent publications address neural network topologies, distributed control strategies, and embedded systems administration. He has also contributed to trust models, referral networks, and traffic signal optimization. Dr. White’s research bridges theoretical computer science and practical applications in robotics, network management, and autonomous systems. Labs/Teams: Leads the Complex Adaptive Systems Group, focusing on interdisciplinary approaches to complex systems and swarm intelligence.

Munir Nazzalمشاهده پروفایل

استاد

• Transportation Engineering
• Civil Engineering
• Pavement Engineering
• +۴ مورد دیگر

Dr. Munir Nazzal is a Professor of Civil Engineering and Director of the Center for Smart, Sustainable & Resilient Infrastructure (CSSRI) at the University of Cincinnati. His research focuses on sustainable transportation infrastructure, pavement engineering, and innovative materials technology. He leads over $13M in grants from federal and state agencies, specializing in asphalt mixtures, pavement performance, and smart infrastructure. He serves as Principal Investigator (PI) on numerous projects, including optimizing maintenance equipment tracking, evaluating micro-surfacing bond strength, and developing AI-driven pothole detection systems. Nazzal is an editor for the ASCE Journal of Materials in Civil Engineering and Buildings Journal, and a licensed professional engineer in Ohio and Louisiana. His work integrates emerging technologies like IoT and autonomous vehicles for infrastructure monitoring. Key contributions include field validation of robotic crack sealing, analysis of aramid fibers in asphalt, and lifecycle cost studies of winter pothole patching methods. His research emphasizes cost-effective, environmentally friendly solutions for local and state transportation systems. Recent grants include a $600,000 federal project for district highway maintenance research, and a $1.2M study on robotic crack sealing methods. He collaborates with industry partners like Honda on vehicle-based roadway data pilots. Nazzal's lab explores nanoscale asphalt properties, thermal expansion effects, and recycled material utilization in pavements.

• Autonomous Driving
• Machine Learning
• Wireless Communication
• +۱۱ مورد دیگر

Dr. Tao (Kevin) Huang is a researcher at James Cook University's College of Science and Engineering, with expertise spanning autonomous driving, wireless communication systems, and medical imaging applications. His work integrates machine learning, sensor fusion, and multimodal data analysis to address complex challenges in vehicular networks, environmental monitoring, and healthcare technology. Research Interests: Dr. Huang's research focuses on Autonomous driving perception systems IoT-enabled vehicular networks AI for medical diagnostics and environmental sensing Signal processing and privacy-preserving communication protocols Recent Publications: His 2025 work emphasizes advancements in V2X cooperative perception, radar-LiDAR-camera fusion, and diffusion models for medical imaging. Key trends include cross-modal robustness, real-time processing for autonomous systems, and AI applications in sustainability.

Maria K. Michaelمشاهده پروفایل

دانشیار

• Cyber-Physical Systems
• Embedded Systems Security
• AI/ML Edge Intelligence
• +۵ مورد دیگر

Maria K. Michael is an Associate Professor at the Electrical and Computer Engineering Department (ECE), University of Cyprus, and a cofounding faculty member of the KIOS Center of Excellence. She leads the Center’s Education and Training activities and coordinates the MSc program in Intelligent Critical Infrastructure Systems, a collaboration between UCY, KIOS CoE, and Imperial College London. Her expertise spans dependability, security, and reliability in cyber-physical systems, embedded systems, and AI/ML optimization for edge intelligence. Education: BSc in Computer Science MSc in Computer Science Ph.D. in Engineering Sciences (Computer Engineering), Southern Illinois University, USA Research Focus: Hardware-enabled security, cyber-security in intelligent embedded systems, reliability of edge-based accelerators, and applications in smart grids, UAVs, robotics, and autonomous vehicles. Her work emphasizes safety-critical systems and resource-constrained environments. Grants & Team: Leads a 15-member research team (postdocs, PhD/MSc/BSc students). Funded by EU FP7, H2020, Horizon Europe, NSF, Intel Corp., and the Cyprus Research and Innovation Foundation. No scientific awards listed explicitly in provided text. Labs & Initiatives: Director of Education/Training at KIOS CoE; core contributor to the MSc program in Intelligent Critical Infrastructure Systems.

Andreas K Athienitisمشاهده پروفایل

استاد

• Solar Energy Engineering
• Energy Efficiency
• Building Simulation and Optimization
• +۶ مورد دیگر

Andreas K Athienitis is a Professor at Concordia University in the Department of Building, Civil, and Environmental Engineering. He serves as Director of the Centre for Zero Energy Building Studies and has held prestigious roles including NSERC/Hydro Québec Industrial Research Chair (2006-2024) and Scientific Director of two NSERC strategic networks. Education: Ph.D. in Mechanical Engineering (University of Waterloo, 1985), B.Sc. in Mechanical Engineering (University of New Brunswick, 1981) Honors: Fellow of the Canadian Academy of Engineering, ASHRAE, and IBPSA His research focuses on energy-efficient buildings, solar energy integration, and predictive control systems. Key projects include Canada’s first net-zero energy institutional building (Varennes Library) and innovative BIPV/T systems. He has developed internationally unique facilities like the Solar Simulator and Environmental Chamber. Recent publications emphasize energy flexibility, predictive control, and renewable integration. His work bridges theoretical modeling with experimental validation, targeting climate resilience and decarbonization. Scientific Awards: Concordia Research Award (2010) NSERC-ADRIQ Celebrate Partnerships Award (2012) Willis H. Carrier Best Paper Award (1991) Multiple Fellowships and Scholarships Grants: Over $30M as P.I., including $123M CFREF grant (2022-2023)