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Kevin LynchView profile

Professor

• Robotic Manipulation
• Robot Locomotion
• Physical Human-Robot Interaction
• +4 more

Kevin Lynch is a Professor of Mechanical Engineering and Director of the Center for Robotics and Biosystems at Northwestern University. He holds a Ph.D. in Robotics from Carnegie Mellon University and a B.S.E. in Electrical Engineering (with honors) from Princeton University. His research focuses on robotic manipulation, robot locomotion, physical human-robot interaction, and distributed control of robot swarms. He has pioneered advancements in exoskeleton control, swarm formation algorithms, and haptic interaction frameworks. Professor Lynch has received significant recognition, including the IEEE Fellow distinction (2010), the Harashima Award (2017), and the Charles Deering McCormick Professor of Teaching Excellence award (2007–2010). He serves as Editor-in-Chief of the IEEE Transactions on Robotics and has authored over 150 peer-reviewed publications. Key contributions include the development of safety-aware human-robot collaboration systems and self-healing swarm control algorithms. He created the ME 333 Introduction to Mechatronics course and the Mechatronics Design Laboratory, fostering interdisciplinary robotics education. His lab, the Center for Robotics and Biosystems, integrates biomechanics with advanced robotics to address challenges in rehabilitation and autonomous systems.

David GarlanView profile

Professor

• Software Engineering
• Software Architecture
• Self-Adaptive Systems
• +4 more

David Garlan is a Professor at the Software and Societal Systems Department within the School of Computer Science at Carnegie Mellon University , where he also serves as Associate Dean for Master’s Programs . He received his Ph.D. from Carnegie Mellon in 1987 after working in industry as a software architect. His research focuses on controlling complexity in large software systems through formalized architectural design, self-adaptive systems, and cyber-physical systems. He developed AcmeStudio , a widely used architecture design environment, and pioneered formal representation and analysis of software architecture. Education : Ph.D. in Computer Science (Carnegie Mellon, 1987) Research Interests include: Software Architecture: Formal methods for architectural design, end-user composition, and architectural styles Self-Adaptive Systems: Stochastic planning, model checking, security adaptation, and uncertainty reduction Cyber-Physical Systems: Multi-view design methods, consistency checking, and automotive systems Recent Article Trends address microservice resiliency, hybrid planning (combining formal methods and ML), simulation-augmented robotics, and sustainable machine translation. Themes include stochastic modeling , probabilistic verification , and adaptive decision-making . Scientific Awards : Stevens Award Citation (2005) ACM SIGSOFT Outstanding Research Award (2011) Allen Newell Award for Research Excellence (2016) IEEE TCSE Distinguished Education Award (2017) Nancy Mead Award (2017) Fellow of IEEE and ACM Advising and Grants : He has advised 25+ graduate students and collaborated on projects with Toyota and the Software Engineering Institute. His work includes model-based adaptation, automated planning, and formal verification of adaptive systems. Labs & Teams : Affiliated with the Institute for Software Research and works on tools like AcmeStudio, Rainbow, and IPL for architectural modeling and self-adaptation.

Martin HenzView profile

Associate Professor

• Programming Languages
• Software Engineering
• Artificial Intelligence
• +8 more

Martin Henz is an Associate Professor at the National University of Singapore , affiliated with the School of Computing and its Department of Computer Science . His academic journey includes an M.Sc. in Computer Science from Stony Brook University (1993) and a Dr.rer.nat. in Computer Science from Saarland University (1997). He has also worked as a Research Scientist at the German Research Centre for Artificial Intelligence. Research Focus : Scalable Experiential Learning, Systems for Teaching/Learning, AI in Education, Programming Languages, Algorithms, and Constraint Programming. Key Projects : Source Academy (immersive programming environment), Deep Teaching (LMS enhancements), and NUS Seafarers (maritime experiential learning). Publications span education technology, programming languages, and sustainable engineering, with recent works focusing on JavaScript-based pedagogy, automated question generation, and electric vehicle conversions. He supervised Rahul Singhal 's PhD, leading to the educational startup Cerebry, and co-founded Workforce Optimizer Pte Ltd with Alan Sevugan. Awards : NUS Annual Digital Education Award (2021) NUS Annual Teaching Excellence Award (2016/17) Fulbright Scholarship (1990) Startup @ Singapore Champion (2001)

• Structural Health Monitoring
• Civil Engineering
• IoT/Edge Computing
• +5 more

Dr. Zhen Peng is a Research Fellow at Curtin University's School of Civil and Mechanical Engineering, part of the Faculty of Science and Engineering. He holds an ARC Early Career Industry Fellowship (2025–2028), focusing on developing cost-effective bridge monitoring systems using computer vision and edge computing in collaboration with Main Roads WA. His work bridges structural engineering, IoT/edge computing, and machine learning to enhance infrastructure safety. Dr. Peng earned his PhD from Curtin University (Chancellor's Commendation, 2022). His research emphasizes structural dynamics, nonlinear damage detection, and mobile crowdsensing frameworks for infrastructure monitoring. He has published extensively in top journals like Engineering Structures and Structural Control and Health Monitoring , receiving notable awards such as the 2023 Best Paper Award and a Gold Medal in the China Postdoctoral Innovation Competition. His current projects include deploying IoT-driven systems for real-time bridge condition assessment and training students via available 2025 PhD scholarships. Dr. Peng teaches courses in civil engineering and structural analysis, contributing to both academia and industry through innovation in smart infrastructure technologies.

Joshua MarshallView profile

Professor

• Field Robotics
• Autonomous Vehicles
• Control Systems Engineering
• +7 more

Joshua Marshall is a Professor of Electrical & Computer Engineering at Queen’s University, Canada, and Director of the Offroad Robotics research group. He holds a PhD from the University of Toronto and has cross-appointments in Mechanical & Materials Engineering and the Robert M. Buchan Department of Mining. His expertise spans field robotics, autonomous systems, control engineering, and harsh-environment applications in mining, space, and marine domains. He led the Ingenuity Labs Research Institute (2018–2024) and served as a Visiting Professor at Örebro University (2016–17). Dr. Marshall’s work focuses on autonomous vehicle navigation, robotic excavation, and spatiotemporal mapping. He has received the 2025 OPEA Engineering Medal and has commercialized technologies through partnerships with companies like Epiroc and RockMass Technologies. Education: PhD, Electrical & Computer Engineering, University of Toronto (2005) MSc(Eng), Mechanical Engineering, Queen’s University (2001) BSc (Hons), Engineering, (details not specified) Research Interests: Autonomous robotics in mining, space, and marine environments Data-driven control systems and model predictive control Proprioceptive sensing and terrain classification Multi-robot coordination and task planning Underground navigation and SLAM Professional Activities: Senior Member, IEEE Editorial roles: International Journal of Robotics Research , IEEE Transactions on Mechatronics Co-founded the NSERC Canadian Robotics Network (NCRN) Contributions to the IEEE Medal for Environmental & Safety Technologies Committee Labs/Teams: Offroad Robotics Group (Queen’s University) Ingenuity Labs Research Institute (founding Director) Advisor to Queen’s AutoDrive Challenge II Team and aQuatonomous ASV Design Club

Nora AyanianView profile

Associate Professor

• Robotics
• Artificial Intelligence
• Multi-Agent Systems
• +4 more

Nora Ayanian is an Associate Professor of Computer Science and Engineering at Brown University, leading the Automatic Coordination of Teams Lab. She holds a PhD and M.S. in Mechanical Engineering from the University of Pennsylvania, followed by postdoctoral research at MIT’s CSAIL. Her work focuses on multi-robot systems, integrating task assignment, path planning, and control to enable coordinated teams of robots for applications in manufacturing, environmental monitoring, and emergency response. Affiliations: Brown University School of Engineering, Department of Computer Science. Former roles include Andrew and Erna Viterbi Associate Professor at USC and WiSE Gabilan Chair holder. Research Interests: Aerial robotics, multi-agent systems, swarm intelligence, and control systems. Notable projects include the Crazyswarm nano-quadcopter swarm and downwash dynamics research for large-scale UAV teams. Awards: 2016 MIT TR35 Innovator, NSF CAREER Award, Okawa Foundation Grant, and recognition as one of IEEE's 'AI’s 10 to Watch'. Teaching: Courses on coordinated robotics and robotics as an artistic medium. Active mentorship with awards for inspiring students and fostering diversity in STEM. Grants & Labs: Director of the Automatic Coordination of Teams Lab, with funding from NSF and industry partnerships. Research has been featured in USA Today, Discovery Channel, and Tech Insider.

Fernando CamelliView profile

Associate Professor

• Computational Fluid Dynamics (CFD)
• Urban Environmental Modeling
• Contamination Dispersion Modeling
• +3 more

Fernando Camelli is an Associate Professor in the Physics & Astronomy Department at George Mason University, holding dual roles as Instructional Faculty and Faculty. His research focuses on computational fluid dynamics (CFD), urban environmental modeling, and high-performance computing. He specializes in simulating complex fluid flows in urban environments, subway systems, and industrial applications, with particular emphasis on turbulence modeling, fluid-structure interaction, and GPU-accelerated algorithms. Key research areas include: CFD for urban airflow and contamination dispersion Meshless and immersed boundary methods Integration of geographic information systems (GIS) with CFD Large-scale simulations using parallel computing His work addresses practical challenges such as subway ventilation optimization, emergency contaminant dispersion prediction, and urban infrastructure design. Recent studies emphasize scalability improvements for fluid-structure interaction simulations and GPU-based code modernization.

Weiwen JiangView profile

Assistant Professor

• Quantum Computing
• AI Accelerators
• Hardware-Software Co-Design
• +3 more

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.

Amit MoreyView profile

Associate Professor

• Food Safety
• Poultry Science
• Meat Quality Analysis
• +5 more

Amit Morey is an Associate Professor in the Department of Poultry Science at Auburn University's College of Agriculture. His research focuses on food safety, poultry meat quality, and advanced sensing technologies. He leads projects involving biosensor development, microbial pathogen detection, and spoilage prediction using machine learning and spectral imaging. His work bridges laboratory innovations with industry applications, addressing challenges in poultry processing, packaging, and supply chain management. Education details are not explicitly listed, but his extensive publications suggest advanced training in food science, microbiology, and engineering. Research interests include antimicrobial biopolymer films, texture analysis of catfish and chicken fillets, and the application of functional ice in seafood preservation. He has pioneered methods for rapid Salmonella detection using microfluidics and fiber optics-based SERS sensors. Notable contributions include developing predictive models for spoilage using near-infrared spectroscopy and exploring cyclic temperature abuse impacts on poultry safety. His interdisciplinary approach integrates artificial intelligence with traditional food science techniques to enhance food safety and reduce waste. While no specific grants or awards are listed, his active publication record (over 100 papers from 2005–2025) indicates sustained research funding. He collaborates on projects addressing global food safety inequities, such as sensor-enabled decision support systems (SENS-D) for vulnerable communities. Lab activities include the Auburn Poultry Science Lab, focusing on meat quality assessment, microbial interventions, and smart packaging solutions. His work has direct industry impact, with applications in poultry processing plants and retail cold chain management.

Fei LiuView profile

Assistant Professor

• Robotics
• Surgical Robotics
• Medical Robotics
• +3 more

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.

Ajay PillarisettiView profile

Assistant Professor

• Household Energy Use
• Air Pollution Exposure
• Human Health Impacts
• +5 more

Ajay Pillarisetti is an Assistant Professor at the University of California, Berkeley's School of Public Health, Department of Environmental Health Sciences. His research focuses on the interplay between household energy use, air pollution exposure, health outcomes, and climate change in low- and middle-income countries. A graduate of UC Berkeley (PhD) and Emory University (MPH, BS), he has led global projects in India, Mongolia, Nepal, Guatemala, Peru, and Rwanda. PhD – Environmental Health Sciences, UC Berkeley MPH – Global Environmental Health, Emory University BS – Biology, Emory College His work employs low-cost air quality sensors, longitudinal surveys, and randomized controlled trials like the HAPIN study to assess health impacts of clean fuel interventions. Key subfields include exposure assessment, implementation science, pollution's metabolic effects, and policy-driven energy transitions. He collaborates with teams across four continents and has published extensively on household air pollution's multi-scale health burdens. Recent articles (2023–2025) highlight trends in quantifying PM2.5's health effects, optimizing sensor networks, and evaluating LPG interventions for maternal/child health. His studies span Guatemala's RESPIRE cohort, Rwanda's HAPIN trial, and India's community monitoring systems, addressing gaps in exposure-response modeling, biomarker analysis, and policy advocacy.

Ebenezer FanijoView profile

Assistant Professor

• Sustainable Construction
• Civil Engineering
• Materials Science
• +3 more

Ebenezer Fanijo is an Assistant Professor at the School of Building Construction, part of the College of Design at Georgia Institute of Technology. He joined in Spring 2023 and specializes in sustainable and smart-resilient infrastructure, focusing on low-carbon construction materials and alternative energy sources. His work addresses carbon emissions in building materials and processes through advanced research on cementitious composites, recycled materials, and green technologies. Dr. Fanijo holds a B.S. in Building Construction (Obafemi Awolowo University, Nigeria), M.S. in Civil Engineering (University of Idaho, 2019), and a Ph.D. in Civil Engineering with a concurrent MEng in Materials Science and Engineering from Virginia Tech (2022). He is also a Professional Engineer (P.E.) and LEED Green Associate with over five years of construction sector experience. Education: B.S. Building Construction, Obafemi Awolowo University, Nigeria (First Class Honours) M.S. Civil Engineering, University of Idaho (2019) Ph.D. Civil Engineering & MEng Materials Science, Virginia Tech (2022) Research Interests: His research spans sustainable construction materials, concrete durability, green technologies using recycled/by-product materials, 3D-printed cementitious materials, and advanced sensing for structural monitoring. He emphasizes decarbonizing infrastructure and developing innovative composites to reduce lifecycle emissions. Awards: NSBE Golden Torch Award (2022) – Recognized as Graduate Student of the Year National/international awards for research excellence Teaching & Advising: Dr. Fanijo teaches courses on construction materials, green technologies, and sustainable practices. He developed core curricula such as Construction Materials and Methods and Green Construction Technology . His advising focuses on student mastery of material properties and their integration into environmental performance frameworks. Professional Contributions: He has led funded research projects, published widely in peer-reviewed journals, and pioneered work on alkali-silica reactivity mitigation, asphalt mix design optimization, and corrosion monitoring. His lab integrates AI and nanoscale techniques for material analysis.

Taylor JohnsonView profile

Associate Professor

• Formal Verification
• Cyber-Physical Systems (CPS)
• Artificial Intelligence
• +7 more

Taylor Johnson is an Associate Professor of Computer Science and Electrical and Computer Engineering at Vanderbilt University's School of Engineering. He directs the Verification and Validation for Intelligent and Trustworthy Autonomy Laboratory (VeriVITAL) and serves as a Senior Research Scientist in the Institute for Software Integrated Systems. Previously, he was an Assistant Professor at the University of Texas at Arlington from 2013 to 2016. His research focuses on formal verification techniques for cyber-physical systems (CPS), emphasizing safety, reliability, and security through hybrid systems, formal methods, and control theory. He has published extensively on neural network verification, earning best paper awards and recognition from IEEE, IFIP, and ACM. Education: Ph.D., Electrical and Computer Engineering (University of Illinois at Urbana-Champaign, 2013) M.Sc., Electrical and Computer Engineering (University of Illinois at Urbana-Champaign, 2010) B.S.E.E., Electrical and Computer Engineering (Rice University, 2008) Research Interests: Formal verification of neural networks and CPS, safety-critical systems, autonomous systems, and AI/ML security. His work bridges theoretical foundations (e.g., hybrid systems) with practical applications in aerospace, energy systems, and robotics. Key Contributions: Developed the NNV tool for neural network verification, led the Verification of Neural Networks Competition (VNN-COMP), and pioneered techniques for robust federated learning and malware detection. Awards: AFOSR YIP Award (2016), NSF CRII Award (2015), and multiple best paper honors. His research is funded by AFRL, NSF, Intel, NVIDIA, and industry partners. Labs & Collaborations: VeriVITAL Lab (Vanderbilt), collaborations with United Technologies Research Center, Boeing, and Toyota.

Raja JurdakView profile

Professor

• Distributed Systems
• Blockchain Technology
• Network Modeling
• +7 more

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.

Cagdas OnalView profile

Associate Professor

• Soft Robotics
• Printable Robotics
• Bio-inspiration
• +3 more

Cagdas Onal is an Associate Professor of Robotics Engineering at Worcester Polytechnic Institute (WPI). He holds a BS and MS from Sabanci University (2003, 2005) and a PhD in Robotics from Carnegie Mellon University (2009). His research focuses on soft robotics, bio-inspired systems, and control theory , emphasizing the development of flexible robotic components for healthcare, industry, and sustainable applications. He leads the Soft Robotics Lab and the Future of Robots in the Workplace (FORW-RD) initiative, advancing human-centric robotics solutions. Research interests include designing bio-inspired soft robots (e.g., origami-inspired snake robots), developing modular actuation systems with embedded sensors, and exploring applications in medical devices and assistive technology. His work aligns with UN Sustainable Development Goals, particularly in healthcare access (SDG 3), quality education (SDG 4), and innovation (SDG 9). Recent projects include origami-based robotic arms for wheelchair users , self-contained underwater robots, and haptic interfaces for teleoperation. His lab collaborates on国家级 grants like the NSF-funded NRT Program and has secured patents for actuator designs (e.g., Hydro Muscle). Labs/Teams: Soft Robotics Lab, FORW-RD, NRT Program. Notable media coverage includes Worcester Telegram & Gazette and Spectrum News for innovations in human-friendly robotics.