جست‌وجوی استاد و پژوهشگر

Jie Fuمشاهده پروفایل

استادیار

• Autonomous Systems
• Control Theory
• Game Theory
• +۴ مورد دیگر

Dr. Jie Fu is an Assistant Professor at the Department of Electrical and Computer Engineering , University of Florida , within the Herbert Wertheim College of Engineering. She holds the Nelms Rising Star Endowed Professorship . Her research focuses on synthesizing correct-by-construction autonomous systems through formal methods, machine learning, control theory, and game theory. Education: M.Sc. in Electrical Engineering & Automation, Beijing Institute of Technology (2009) Ph.D. in Mechanical Engineering, University of Delaware (2013) Research Interests: Dr. Fu’s work spans preference-aware decision-making with human-in-the-loop systems, adaptive control under temporal logic constraints, and game-theoretic design of secure autonomous systems. Key applications include cyber-physical system security, human-autonomy collaboration, and deception-resistant cyber defense. Awards & Grants: NSF CAREER Award (2022) DARPA Young Faculty Award (2021) AFOSR Young Investigator Award (2021) $1.3M ARL Grant (2025) for hierarchical game planning $550K NSF CAREER Award (2022) Advising & Collaborations: Advises PhD students in robotics, control systems, and cybersecurity Collaborates with Raytheon BBN, UT Austin, and Purdue University Leads projects on tactical autonomous systems and proactive cyber defense Labs & Teams: Her lab develops trustworthy autonomous systems , emphasizing security, adaptability, and human collaboration. Projects include soft robot locomotion, semantic SLAM, and deception-aware planning.

Larissa Novelinoمشاهده پروفایل

استادیار

• Origami Engineering
• Metamaterials
• Deployable Structures
• +۵ مورد دیگر

Larissa Novelino is an Assistant Professor of Civil and Environmental Engineering at Rice University, where she leads the Novelino Research Group. Her work bridges art and engineering through origami-inspired innovations, focusing on deployable structures, metamaterials, and tunable systems. She holds a Ph.D. from Georgia Institute of Technology (2021) and an M.S. from Pontifical Catholic University of Rio de Janeiro (2015). Her research explores origami's potential in creating shape-changing structures for space exploration, emergency infrastructure, and robotics. Key areas include auxetic metamaterials, magnetic control of origami microrobots, and computational modeling of origami mechanics. Recent projects address imperfection effects in metamaterials and untethered robotic actuation. Education: B.S., Federal University of Para, Brazil (Civil Engineering) M.S., Pontifical Catholic University of Rio de Janeiro, Brazil (Civil Engineering) Ph.D., Georgia Institute of Technology, USA (Civil Engineering) Her work spans computational methods, additive manufacturing, and geometric mechanics. Current opportunities include Ph.D. positions in origami engineering, deployable systems, and metamaterial design. Labs and collaborations emphasize interdisciplinary approaches, integrating mechanical analysis, robotic systems, and advanced manufacturing techniques. Her group actively seeks students passionate about applying origami principles to solve real-world engineering challenges.

Chew Chee Mengمشاهده پروفایل

پژوهشگر

• Robotics
• Humanoid Robotics
• Industrial Robotics
• +۷ مورد دیگر

Dr. Chew Chee Meng is a faculty member at the Department of Mechanical Engineering, National University of Singapore (NUS). He holds a PhD from MIT and has contributed extensively to robotics research, particularly in humanoid robots, biomimetics, and autonomous systems. His work spans both theoretical and applied domains, including the design of force-control actuators, manta ray-inspired underwater robots, and assistive devices for rehabilitation. PhD (MIT) SM (MIT) M.Eng. (NUS) B.Eng. (1st Class Honours, NUS) Dr. Chew's research interests include Industrial Robotics , Humanoid Robotics , Biomimetic Systems , and Autonomous Vehicles . His publications focus on bipedal locomotion, control algorithms, and actuator design. He has supervised student teams in competitions like RoboCup and Maritime RobotX Challenge, achieving notable awards. As a Lead PI in the Keppel-NUS Corp Lab, he works on productivity enhancement in robotics. He is an Associate Editor for the International Journal of Humanoid Robotics and actively involved in IEEE societies. First Prize, RoboCup 2010 Adult-Size Humanoid League Fifth Prize, Maritime RobotX Challenge 2014 Dr. Chew has taught modules such as Advanced Robotics and Robot Mechanics and Control since 2001, demonstrating his long-term commitment to robotics education and innovation.

• Monte Carlo radiation transport simulation
• Medical physics
• Radiation protection
• +۴ مورد دیگر

Professor Susanna Guatelli is a leading academic in radiation physics and medical applications at the University of Wollongong (UOW), affiliated with the School of Physics within the Faculty of Engineering and Information Sciences. She is currently the Interim Head of the School of Physics and Theme Leader for 'Monte Carlo simulations' in the Centre for Medical Radiation Physics at UOW. Her research focuses on Monte Carlo simulation techniques for radiation protection, medical physics, and space exploration, with significant contributions to Geant4 software development and benchmarking. Guatelli obtained her Master's and PhD in Physics from the University of Genova (Italy) and INFN Genova, with early career work at CERN on radiation effects in space missions. She has held key roles in international collaborations, including the Geant4 International Collaboration Steering Board and leadership of medical physics benchmarking groups. Her research interests span radiation protection for astronauts, medical radiation therapy optimization, and advanced imaging techniques. Notable recognitions include the Australian Institute of Physics' Women in Physics Award (2021) and inclusion in the UOW Women of Impact (2016). She actively participates in public outreach to inspire youth in physics and serves as an Associate Editor for journals like Physica Medica . Guatelli has secured over 30 grants since 2012, focusing on medical radiation research, space radiation monitoring, and machine learning in therapy planning. Her current projects include DoseGAN for microbeam radiation therapy and Space RAdiation Monitoring System (SRAMS) for lunar missions.

Vladimir Wojcikمشاهده پروفایل

دانشیار

• Computer Vision
• Parallel Computing
• Artificial Intelligence
• +۲ مورد دیگر

Dr. Vladimir Wojcik was an Associate Professor in the Department of Computer Science at Brock University. He held an MSc from Warsaw University and specialized in computer vision, parallel computing, simulation, visual machine learning, and artificial intelligence. His interdisciplinary work included collaborations on vertebrate vision systems and biologically inspired parallel computing architectures. He taught courses including Software Engineering, Parallel Computing, and Discrete Event Simulation, emphasizing challenging projects to build student capability. Administrative roles included coordinating the CAST Programme and contributing to Brock's integration into the SHARCnet supercomputing consortium.

Alessandro Di Stefanoمشاهده پروفایل

مدرس ارشد

• Game Theory
• Network Science
• Machine Learning
• +۴ مورد دیگر

Dr. Alessandro Di Stefano is a Senior Lecturer in Computer Science at Teesside University's Department of Computing & Games within the School of Computing, Engineering & Digital Technologies. He holds a PhD in Systems Engineering from the University of Catania (2015) and has held academic and research positions at King’s College London, the University of Cambridge, and the University of Catania. His research focuses on interdisciplinary methodologies combining game theory, network science, and machine learning to study socio-technological systems, human cooperation, and complex dynamics. Education: BSc (2009) and MSc (2012) in Telecommunications Engineering from the University of Catania; PhD in Systems Engineering (2015). Professional Qualifications: Postgraduate Certificates in Learning & Teaching in Higher Education (FHEA, 2022). Research Interests: Game Theory, Network Science, Machine Learning, Human Cooperation, Social Dynamics, Homophily, Epidemic Spreading. He collaborates globally, including with the University of Cambridge, Missouri S&T, and King’s College London. Grants/Projects: Lead PI on projects such as KTP - TaperedPlus (AI-driven design systems) and KTP - CSX Carbon (peatland restoration via deep learning). Active in conferences like CCS, ALIFE, and IJCAI, and serves as a reviewer for top journals (IEEE Transactions, Nature Scientific Reports). Labs/Teams: Part of the Interpretable & Beneficial AI group at Teesside, focusing on AI ethics, regulatory frameworks, and complex network modeling. Collaborates with industry partners on AI applications in construction, healthcare, and environmental monitoring.

Jundong Liuمشاهده پروفایل

دانشیار

• Machine Learning
• Deep Learning
• Reinforcement Learning
• +۷ مورد دیگر

Jundong Liu is an Associate Professor in the School of Electrical Engineering and Computer Science (EECS) at Ohio University's Russ College of Engineering and Technology, with an affiliation to the Biomedical Engineering program. He directs the Learning & Intelligent Systems Lab (LiSL) and focuses on machine learning, deep learning, neuromorphic computing, and their applications in medical imaging, speech processing, and autonomous systems. Education: Ph.D., Computer Information Science and Engineering, University of Florida M.S., Computer Science, Peking University B.S., Computer Science, Wuhan University Research Interests: Machine learning, deep learning, and reinforcement learning Medical image analysis (brain tumor segmentation, Alzheimer’s disease modeling) Computer vision (neuroimaging analysis, radar signal processing) Neuromorphic computing and spiking neural networks Key Contributions: Developed segmentation-assisted image registration methods for neuroimaging Advanced spiking neural networks for low-power computing Contributed to biotesting using plasmonic nanoparticles Labs/Teams: Leads the Learning & Intelligent Systems Lab (LiSL), collaborating on AI-driven solutions for medical, autonomous systems, and signal processing challenges.

Soha Hassounمشاهده پروفایل

استاد

• Machine Learning
• Systems Biology
• Metabolic Engineering
• +۵ مورد دیگر

Soha Hassoun is a Professor at Tufts University with primary appointment in the Department of Computer Science and secondary appointments in the Department of Electrical and Computer Engineering and the Department of Chemical and Biological Engineering. Her interdisciplinary work bridges computer science, engineering, and biology to develop computational tools for biological systems analysis and design. Education: Ph.D. from University of Washington (1997) M.S. from Massachusetts Institute of Technology (1988) B.S. from South Dakota State University (1986) Soha Hassoun's research focuses on the intersection of Machine Learning and Biology, with particular emphasis on developing ANALYSIS + DESIGN tools to advance (RE-)DESIGNING BIOLOGY. Her work spans Systems Biology, Metabolic Engineering, and computer-aided design for integrated circuits. She develops MACHINE LEARNING models specifically tailored for biological data, drawing inspiration from her prior experience in circuit design and design automation for electronic systems where she contributed seminal ideas for FinFET devices and power grids for 3D integrated circuits. Her recent publications demonstrate a strong trend toward applying advanced machine learning techniques, particularly graph neural networks and transformer models, to biological problems including metabolite annotation, enzyme-substrate interaction prediction, and metabolic network analysis. Her work increasingly focuses on creating standardized benchmarks and frameworks for evaluating computational methods in metabolomics. Soha leads the Hassoun Lab, which is dedicated to developing computational tools that provide insight into complex biological systems and enable building novel biological components to produce useful chemicals and therapeutics. The lab's research spans from fundamental machine learning algorithm development to practical applications in biotechnology.

• Neuroscience
• Artificial Intelligence
• Machine Learning
• +۷ مورد دیگر

Prof. Jochen Triesch is a Senior Fellow and Johanna Quandt Research Professor at the Frankfurt Institute for Advanced Studies (FIAS), with concurrent professorships in Physics and Computer Science at Goethe University Frankfurt. His research bridges theoretical neuroscience, machine learning, and medical applications, focusing on cognitive processes, spiking neural networks, and developmental AI. He leads a lab investigating how intelligent systems emerge through self-organization and learning, with applications in healthcare and robotics. Education and affiliations include a physics background and roles at UC San Diego before joining FIAS. His lab offers open thesis topics in machine learning, neuroscience, and medical diagnostics, with notable work on epilepsy prediction and brain tumor detection via AI. Research interests span neural coding, unsupervised learning, and embodied vision. Key awards include the EU’s Marie Curie Excellence Center Award (2006). His lab collaborates extensively, with projects on neural dynamics, computational pathology, and virtual reality applications for vision disorders. Teaching includes courses on theoretical neuroscience, reinforcement learning, and complex systems. Over 30 students have graduated under his mentorship, many contributing to AI, healthcare, and neuroscience fields. Labs/Teams: Triesch Lab (FIAS) focuses on interdisciplinary approaches to brain-inspired AI, combining experimental and computational methods to understand learning and perception.

Thomas Wennekersمشاهده پروفایل

دانشیار

• Neural Networks
• Cognitive Modeling
• Computational Neuroscience
• +۲ مورد دیگر

Thomas Wennekers is an Honorary Associate Professor at the University of Plymouth's School of Engineering, Computing and Mathematics. His research focuses on developing biologically constrained neural network models to understand cognitive functions such as language processing, memory formation, and sensory integration. He specializes in hierarchical temporal memory systems and spiking neural networks. Wennekers investigates neural mechanisms underlying semantic processing, cognitive impairments like dementia, and cross-modal plasticity in sensory systems. His work combines computational neuroscience with robotics to create bio-inspired cognitive systems, examining how neural constraints shape learning and perception. His publications explore neurobiological models of language, visual processing, and memory, with applications in neuromorphic computing and cognitive robotics. Recent work simulates neural reorganization in blind individuals and models cognitive disorders using brain-constrained architectures.

Hossein Haj-Haririمشاهده پروفایل

استاد

• Computational Mechanics
• Theoretical Applied Mechanics
• Fluid Mechanics
• +۷ مورد دیگر

Hossein Haj-Hariri is the Dean of the Molinaroli College of Engineering and Computing at the University of South Carolina (since 2016) and holds the title of USC Educational Foundation Distinguished Professor. Previously, he spent 27 years at the University of Virginia, serving as Chair of Mechanical and Aerospace Engineering (2005–2015) and co-Director of the K-12 Engineering Design Laboratory. He earned his Ph.D., S.M., and S.B. in Mechanical and Civil Engineering from MIT. His research focuses on computational and theoretical applied mechanics, including fluid mechanics of swimming, thermal management systems, and interfacial phenomena. He has secured over $30M in research funding, published over 100 papers, and holds patents in thermal management and carbon-fiber composites. Key areas of expertise include aero-acoustics, hydrodynamic stability, and fluid-structure interactions. Education: S.B. in Civil Engineering, MIT S.M. and Ph.D. in Mechanical Engineering (Applied Mechanics), MIT His work bridges fundamental science and applied engineering, with recent emphasis on biomimetic robotics (e.g., manta ray-inspired designs) and high-heat-flux thermal systems. He has mentored over 35 researchers and 50+ undergraduates. Awards: USC Educational Foundation Distinguished Professor Grants and leadership: Spearheaded strategic initiatives to advance engineering education and research at USC. His lab collaborations include projects on microfluidics, flow control, and sustainable energy systems. Current initiatives focus on transforming healthcare through engineering innovation, advanced manufacturing, and smart infrastructure.

Dimitrios Makrisمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Video Analysis
• +۳ مورد دیگر

Dimitrios Makris is a Professor in Computer Vision and Machine Learning at Kingston University's Department of Computer Science, within the Faculty of Engineering, Computing and the Environment. He holds a PhD in Computer Vision from City University London and an MEng in Electrical and Computer Engineering from Aristotle University of Thessaloniki. As Faculty Director of PGR Studies, he oversees postgraduate research programs and leads investigations into video analysis, motion tracking, and neuromorphic vision systems. His research focuses on: Multi-dimensional time-series analysis for human motion tracking Neuromorphic vision sensors for robotic grasping applications Medical video analysis using contrast-enhanced ultrasound Scene semantic modeling and multi-camera systems He has secured multiple research grants from national and international organizations to advance these areas. Publication analysis reveals consistent focus on computer vision fundamentals with growing emphasis on healthcare applications and neuromorphic computing. Recent works demonstrate increased integration of machine learning with sensor technologies for real-time robotic and medical systems. Awards and leadership roles include: Deputy Editor-in-Chief for Special Issues, IET Image Processing Journal Member of Steering Committee, IET Vision and Imaging Network He actively contributes to academic communities through editorial responsibilities and steering committee membership for major vision and imaging networks.

Chinwe Ekennaمشاهده پروفایل

دانشیار

• Robotics
• Machine Learning
• Computational Biology
• +۴ مورد دیگر

Chinwe Ekenna is an Associate Professor in the Department of Computer Science at the University at Albany, State University of New York (SUNY) and directs the Robotics, Algorithm and Computable Systems (RACS) Laboratory . She serves as a faculty advisor for UAlbany's ACM-W chapter , promoting women in robotics and STEM. PhD in Computer Science from Texas A&M University (2016) MSc in Computer Science from Covenant University, Nigeria (2008) BSc in Computer Science from Covenant University, Nigeria (2006) Her research focuses on intelligent motion planning for robotics and proteins, integrating machine learning to enhance planning efficiency and accuracy. Key areas include computational biology , robotic navigation , and topological modeling . Her recent publications explore transformer-based motion planning , attention mechanisms for molecular analysis , and discrete Morse theory for robotics . These works bridge artificial intelligence , robotics , and biomedical applications . As a leader, she organized the Meet the Women in Robotics Workshop at RSS 2019, funded by the National Science Foundation. Her teaching includes courses in theory of computation and algorithms . At the RACS Laboratory , her team investigates path planning , adversarial robustness , and robotics in dynamic environments , emphasizing interdisciplinary collaboration and innovation.

Nobuaki Mizumotoمشاهده پروفایل

استادیار

• Behavioral Ecology
• Insect Social Behavior
• Collective Animal Behavior
• +۳ مورد دیگر

Nobuaki Mizumoto is an Assistant Professor in the Department of Entomology & Plant Pathology at Auburn University's College of Agriculture. His research focuses on termite behavior, collective animal behavior, and evolutionary biology, with a particular emphasis on understanding social interactions, communication mechanisms, and ecological adaptations in insects. Key research areas include: Collective behavior in termites and ants, including tandem running and swarming patterns Evolutionary and genetic aspects of termite classification and phylogeny Behavioral ecology of mating systems and predator-prey dynamics Applications of genomic data to resolve taxonomic relationships Recent work highlights innovative approaches such as amber fossil analysis for behavioral reconstruction and development of tools like TManual for measuring animal-built structures. His lab's research bridges field observations with computational modeling to uncover principles underlying complex social behaviors. Publications span topics from termite tunneling strategies to the molecular basis of caste determination, demonstrating interdisciplinary integration of entomology, genomics, and behavioral ecology.

Samaneh Berenjianمشاهده پروفایل

مدرس ارشد

• Cybersecurity
• Network Security
• Peer-to-Peer Networks
• +۴ مورد دیگر

Samaneh Berenjian is a Senior Lecturer in the Department of Computer Science at New Jersey Institute of Technology (NJIT). Her academic journey includes a Ph.D. from Stevens Institute of Technology (2022), and M.S. degrees from Stevens (2018) and Amirkabir University of Technology (2013), alongside a B.S. from the University of Isfahan (2011). Her research focuses on cybersecurity, network security, and peer-to-peer systems, with contributions to secure protocol design, intrusion response mechanisms, and privacy-preserving technologies. She has also explored navigation models in AI and wireless sensor networks. Her research interests span cybersecurity frameworks, P2P network anonymity, and intelligent systems. Notable work includes encryption-based protocols, incentive models for secure P2P fairness, and fuzzy logic-based intrusion detection systems. Her 2020 GridCell navigational model highlights interdisciplinary AI contributions. Her publications reflect expertise in secure communication, network architecture, and optical fiber error control. While no awards are listed, her work demonstrates consistent engagement with cutting-edge topics in computer science and information security.