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Chien-Chung ShenView profile

Professor

• Computer Networks
• Cybersecurity
• Mobile Ad Hoc Networks
• +7 more

Chien-Chung Shen is a Professor and Associate Chair for Undergraduate Studies in the Department of Computer and Information Sciences at the University of Delaware. His expertise spans mobile ad hoc networks, sensor networks, blockchain technology, federated learning, and cybersecurity. He holds a PhD from UCLA and MS/BS degrees from National Chiao Tung University, Taiwan. Education: PhD in Computer Science, UCLA MS & BS in Computer Science, National Chiao Tung University, Taiwan Research Interests: Next-generation wireless networks (e.g., 5G/6G, underwater acoustic networks) Cybersecurity frameworks for autonomous systems and metaverse Blockchain-based distributed systems and trust management Federated learning for edge computing and traffic prediction Grants & Collaborations: National Science Foundation (NSF): Projects on federated learning, secure education, and network protocols Army Research Lab: Tactical network management and bio-inspired protocols Cisco, MITRE, NASA, and industry partnerships for applied research Advising & Education: Current PhD advisees: Ehsan Memary, Hang Chen, Syed Ali Asif Over 25 former students placed in academia (e.g., universities in China, Thailand, South Korea) and industry (Google, Meta, Amazon) Teaching courses on networks, cybersecurity, blockchain, and distributed systems Labs & Teams: Leading interdisciplinary research on edge computing, vehicular networks, and metaverse security Collaborations with international institutions like Korea Aerospace University and National Cheng Kung University

• Power Electronics
• Electric Vehicles
• Electromechanical Systems
• +3 more

Arijit Banerjee is an Associate Professor in the Department of Electrical and Computer Engineering and Mechanical Science and Engineering at the University of Illinois at Urbana-Champaign, with a Grainger Associate appointment. His research focuses on advanced power electronics, electric drives, and renewable energy systems. Key areas include variable-pole induction machines, electromechanical actuators, and condition monitoring for power devices. He holds a Ph.D. in Electrical Engineering and has authored over 75 publications. His work bridges academic theory and industrial applications, addressing challenges in electric vehicle propulsion, offshore wind energy, and bio-inspired robotics. Research interests span: Electromechanical systems design High-efficiency power converters Reluctance machine optimization SiC MOSFET condition monitoring Recent articles emphasize variable-pole motor control, bioinspired actuators, and electro-thermal co-design. His NSF CAREER Award (2020) supports innovative electric propulsion research. Advising and grants include collaborations on EV drives, wind turbine systems, and fault detection algorithms. He leads interdisciplinary projects involving robotics and renewable energy integration.

Zjenja DoubrovskiView profile

Assistant Professor

• Additive Manufacturing
• Materials Science
• Mechatronics
• +3 more

Zjenja Doubrovski is an Assistant Professor at the Faculty of Industrial Design Engineering, Delft University of Technology. They hold an MSc in Integrated Product Design (Cum Laude, 2010) and a PhD in Additive Manufacturing (2016). Their research focuses on multi-material Additive Manufacturing (AM), meta-materials, and bio-inspired design, with applications in mechatronics and robotics. They collaborate closely with the 3D printing industry and supervise graduation projects expanding this field. Education includes teaching courses like Computational Fabrication , Computer-Aided Design , and Digital Materials . Awards include the 2023 Best Paper Honourable Mention and the 2013 Best Young Presenter Award at eCAADE. Research interests span soft robotics, 4D printing, sustainable materials, and biohybrid systems. Their work bridges design methodologies with advanced manufacturing technologies, emphasizing innovation and practical collaboration. Research Highlights: Biomimetic composites, smart mechanics, and living materials for carbon absorption. Key Collaborations: Industry partnerships for AM applications, EU-funded projects on sustainable design.

Mohsen ImaniView profile

Assistant Professor

• Artificial Intelligence
• Machine Learning
• Computer Architecture
• +3 more

Mohsen Imani is an Assistant Professor at the Donald Bren School of Information and Computer Sciences, University of California, Irvine, and director of the Bio-Inspired Architecture and Systems Lab (BIASLab) . His research bridges neuroscience, machine learning, and embedded systems to develop hyperdimensional computing (HDC) as a neuro-symbolic AI technique. PhD in Computer Science and Engineering from UC San Diego Led 35+ member team with 17 PhD students Received $750,000 ONR YIP award and $1M DARPA grant Research focuses on: Hyperdimensional computing for real-time cognitive systems Energy-efficient edge AI with brain-inspired architectures Privacy-preserving federated learning frameworks Security monitoring with interpretable reasoning His 15+ most recent publications span: 2025 work on quantum HD factorization and uncertainty-robust cognitive maps 2024 breakthroughs in photonic neuro-symbolic computing and genome matching 2023 foundational work on DNN hardware acceleration Awards include: DARPA Young Faculty Award SRC Young Faculty Award ONR Young Investigator Award Eight best paper awards/nominations Teaching CS 151: Digital Logic Design and CS 257: Brain-Inspired Learning Systems in Winter 2025. His lab released the first open-source library for brain-inspired HD computing.

• Robotics
• Biomedical Engineering
• Exoskeleton Design
• +3 more

Gijs van Oort is a Research Professor at the University of Twente's TechMed Centre, Department of Robotics and Mechatronics. His work focuses on advanced robotic systems, particularly exoskeletons for mobility enhancement and rehabilitation. He holds a PhD (dr.ir.) in Engineering. Key research areas include human-robot interaction, neuromuscular control systems, and assistive technologies for spinal cord injuries. Education: Dr.ing. (PhD) in Robotics and Mechatronics, MSc in Mechanical Engineering (inferred from academic title dr.ir.). Research emphasizes exoskeleton design, gait assistance, and modular robotics. Notable contributions include the Symbitron exoskeleton project, aiming to improve mobility for paraplegics. His work bridges biomechanics and control engineering, with applications in clinical rehabilitation and wearable robotics. Publications highlight interdisciplinary collaboration, such as integrating bio-inspired reflexive control systems with trajectory-based approaches. His research aligns with UN Sustainable Development Goals, particularly improving health and well-being (SDG 3) and advancing technology (SDG 9). No scientific awards explicitly listed, but his h-index of 341 and 200+ citations reflect significant academic impact. Active in international conferences (e.g., WeRob2018) and collaborative projects involving institutions like École Polytechnique Fédérale de Lausanne (EPFL).

• Evolutionary Algorithms
• Swarm Intelligence
• Computational Intelligence
• +1 more

Carlos Miguel da Costa Fernandes is an Assistant Researcher specializing in evolutionary computation and swarm intelligence. His work focuses on developing bio-inspired algorithms for optimization problems.

Robert HewsonView profile

Professor

• Multidisciplinary Design Optimization
• Structural Metamaterials
• Computational Mechanics
• +2 more

Professor Robert Hewson leads the Multidisciplinary Design Optimization research group at Imperial College London's Department of Aeronautics. His work develops computational methods for designing optimized structures across multiple scales. Hewson's research integrates topology optimization, additive manufacturing constraints, and multiphysics modeling to create novel metamaterials and aerospace components. Recent work focuses on multiscale lattice structures with tailored mechanical, thermal, and dynamic properties for aerospace applications. His publications demonstrate expertise in computational mechanics, tribology modeling, and design automation. Hewson collaborates with aerospace industry partners to translate optimization methods into practical engineering solutions.

Dipankar DasguptaView profile

Professor

• Cybersecurity
• Artificial Intelligence
• Machine Learning
• +6 more

Dipankar Dasgupta is the William Hill Professor in Cybersecurity and Director of the Center for Information Assurance at the University of Memphis. He holds a PhD in Computer Science from the University of Strathclyde (1994) and has been a faculty member since 1997, advancing to Full Professor in 2004. His research focuses on cybersecurity, artificial intelligence, and bio-inspired computing, particularly in artificial immune systems and evolutionary computation. He has authored/co-authored over 300 publications, including influential books like *Immunological Computation* and *Advances in User Authentication*. Dr. Dasgupta is an IEEE Fellow, ACM Distinguished Speaker, and recipient of the 2014 ACM SIGEVO Impact Award and 2011-2012 Willard R. Sparks Eminent Faculty Award. He leads the Center for Information Assurance, a nationally recognized academic excellence hub in cybersecurity education and research. His work includes pioneering contributions to negative authentication systems, cybersecurity frameworks, and AI-driven threat detection. His research spans adversarial machine learning, federated learning security, and generative AI. He has collaborated widely, with an h-index of over 58 and collaborations with 106 co-authors. He also contributes to educational initiatives, such as cybersecurity summer camps for high school students, and chairs like the MIT Geospatial Data Center Advisory Board.

Shan ZhongView profile

Professor

• Flow Control
• Aerodynamics
• Fluid Mechanics
• +4 more

Shan Zhong is a Professor in the School of Mechanical, Aerospace and Civil Engineering at The University of Manchester. She holds a BEng and MEng from Tsinghua University and a PhD from the University of Cambridge. As the Head of the Aerodynamics Research Group, her work focuses on experimental fluid mechanics, flow control, and biofluid dynamics. Her research spans aerodynamics, turbulence, and low-Reynolds-number propulsion, aiming to enhance aerodynamic efficiency in turbomachinery and transportation systems. Supported by grants from EPSRC, Royal Society, and industry partners like Airbus and BAE Systems, her contributions include over 140 publications and the supervision of 23 PhD students. Research interests include boundary layer transition, flow separation control, fluid mixing enhancement, and bio-inspired surface patterns. Prof. Zhong is a Fellow of the Royal Aeronautical Society and leads the Laser Processing Research Centre. Her work aligns with UN Sustainable Development Goals related to clean energy and industrial innovation. Education: BEng/MEng (Tsinghua University), PhD (University of Cambridge) Affiliations: Aerodynamics Research Group, Laser Processing Research Centre Grants: EPSRC, Royal Society, Leverhulme Trust, Airbus, BAE Systems Her research employs advanced techniques like PIV and synthetic jet actuators to study complex fluid phenomena. Current projects explore flow control strategies for reducing drag and improving propulsion efficiency in aerospace and land-based systems.

• Artificial Intelligence
• Reinforcement Learning
• Multi-Agent Systems
• +3 more

Daniel Jarne Ornia is a Researcher at the University of Oxford's Department of Computer Science, located in Room 213 of the Wolfson Building on Parks Road, Oxford. His work focuses on artificial intelligence, multi-agent systems, and reinforcement learning, with particular emphasis on risk-aware decision-making, robust learning algorithms, and autonomous agent coordination. Research interests include developing methods for efficient and reliable coordination in multi-agent environments, exploring bounded rationality in resource-constrained systems, and advancing techniques for predictable reinforcement learning dynamics. His recent publications address topics such as contingency planning with multi-modal predictions, entropy rate minimization in learning systems, and navigation strategies for robotic swarms. No academic awards or grants are explicitly mentioned in the provided information. Daniel’s research often intersects with robotics, distributed control systems, and theoretical foundations of autonomous decision-making.

Farshad ArvinView profile

Professor

• Swarm Robotics
• Bio-inspired Systems
• Multi-agent Systems
• +1 more

Farshad Arvin is a Professor in the Department of Computer Science at Durham University, with affiliations to the Wolfson Research Institute for Health and Wellbeing. He holds a BSc in Computer Engineering (2004), MSc in Computer Systems Engineering (2010), and PhD in Computer Science (2015). His research focuses on swarm robotics, bio-inspired systems, and multi-agent autonomous systems. Research interests include biohybrid robotics, swarm intelligence algorithms, and applications in extreme environments. His recent publications demonstrate strong focus on underwater robotics, UAV coordination, and federated learning for swarm navigation. He directs the Swarm & Computational Intelligence Laboratory (SwaCIL) and leads major EU projects including RoboRoyale (€3.27M), Sensorbees (€3.2M), and BioDiMoBot (€8M). His team includes 4 Post-Doctoral researchers and 6 PhD students.

Kheng Cher YeoView profile

Senior Lecturer

• Security
• Networking
• Image Processing
• +2 more

Dr. Kheng Cher Yeo is a Senior Lecturer in Information Technology at the Faculty of Science and Technology. His research focuses on interdisciplinary areas including cybersecurity, networking, image processing, control systems, and machine learning. He explores innovative solutions for IoT security frameworks, healthcare technology, and privacy-preserving systems. His work integrates machine learning with healthcare diagnostics, cybersecurity forensics, and smart city accessibility. Key research interests include: IoT Security & SDN Integration Medical Imaging & AI-Driven Diagnostics Privacy in Healthcare Systems Malware Analysis & Forensic Techniques Bio-inspired Authentication Systems Recent publications highlight advancements in: Automated respiratory disease diagnosis via lung ultrasound Cybersecurity frameworks for IoT and DDoS mitigation Privacy-by-design healthcare record management Smart city accessibility through crowdsourcing His research demonstrates a strong focus on practical applications of AI and cybersecurity in healthcare, smart infrastructure, and data protection. No scientific awards are noted in the provided texts.

• Computer Engineering
• Machine Learning
• Radar Signal Processing
• +2 more

Piotr Łuczak is a Researcher at the Institute of Applied Computer Science, Faculty of Electrical, Electronic, Computer and Control Engineering, Lodz University of Technology. His work bridges computer engineering, machine learning, and biomedical applications. Research spans VLSI systems for radar-based health monitoring, thermal imaging for industrial control, hyperdimensional computing frameworks, and neuromorphic approaches. Recent publications demonstrate strong interdisciplinary focus on hardware-efficient AI implementations. Article analysis shows consistent evolution in: (1) Radar-based biomedical sensing with novel signal processing; (2) Thermal imaging for industrial automation; (3) Hybrid AI models combining neural networks with symbolic methods; (4) Neuromorphic computing for edge devices; (5) Optimization techniques for efficient neural architectures; (6) Human-machine interaction systems.

Jeremy HollemanView profile

Associate Professor

• Low-power Circuits
• Analog/Mixed-Signal Design
• Neuromorphic Computing
• +3 more

Dr. Jeremy Holleman is an Associate Professor and Program Coordinator of Electrical Engineering at the University of North Carolina at Charlotte. He directs the assessment efforts within the Electrical and Computer Engineering department. His research focuses on low-power analog/mixed-signal circuits, biomedical interface design, neuromorphic computation, and machine learning hardware for resource-constrained systems. He holds a Ph.D. (2009) and M.S. (2006) from the University of Washington and a B.S. (1997) from Georgia Institute of Technology. Dr. Holleman's work emphasizes energy-efficient computing architectures and hardware implementations of machine learning, including contributions to MLPerf Power benchmarks and TinyML standards. His academic background includes over 20 years of experience in analog circuit design, neuromorphic systems, and biomedical signal processing. Notable projects include a 1 Tera-OPS/Watt analog deep learning engine and ultra-low-power neural amplifiers for bio-potential recording. He has published extensively across IEEE journals and conferences, with over 50 peer-reviewed articles. His research has been applied in medical implants, wireless neural interfaces, and energy-harvesting systems. Current initiatives include advancing analog deep learning architectures and sustainable AI hardware optimization. Dr. Holleman’s lab collaborates on hardware-software co-design for embedded machine learning and neuromorphic systems.

Jonas KucklingView profile

Research Fellow

• Artificial Life
• Swarm Robotics
• Artificial Intelligence
• +3 more

Jonas Kuckling is a postdoctoral researcher at the Department of Computer and Information Science, University of Konstanz, and a fellow at the Zukunftskolleg. His research focuses on artificial life and swarm robotics, particularly open-endedness in embodied collectives, integrating disciplines including biology, chemistry, physics, computer science, philosophy, and art. Dr. Kuckling obtained his doctoral degree in April 2023 from the Artificial Intelligence research laboratory (IRIDIA) at the Université Libre de Bruxelles, Belgium. His doctoral work established foundations for his current investigations into emergent collective behaviors in robotic systems. His primary research interests center on artificial life and swarm robotics, with emphasis on open-ended evolution in embodied collectives. He explores how interdisciplinary approaches can generate autonomous systems capable of continuous novelty without external direction, bridging computational models with biological principles of self-organization and adaptation. This work addresses fundamental challenges in scalability, robustness, and emergent complexity in multi-robot systems. Analysis of his recent publications reveals a concentrated focus on automatic modular design of robot swarm control software, particularly through behavior trees and optimization techniques like simulated annealing. His work progresses from theoretical frameworks (e.g., manifestos on off-line design) to practical implementations (AutoMoDe tools), with increasing integration of learning, communication, and edge computing in large-scale swarm deployments. No scientific awards are documented in available sources. Dr. Kuckling currently leads an interdisciplinary research project at the Zukunftskolleg, collaborating with experts in complex systems, artificial life, AI, and robotics to advance open-endedness in embodied collectives. No information is available regarding student advising or specific grant funding beyond his fellowship appointment.