جست‌وجوی استاد و پژوهشگر

• Digital Signal Processing (DSP)
• Field-Programmable Gate Arrays (FPGA)
• Machine Learning Hardware Acceleration
• +۱۳ مورد دیگر

Gian Carlo Cardarilli is a researcher specializing in digital hardware design and machine learning acceleration. His work focuses on FPGA implementations, Residue Number System (RNS) architectures, and reconfigurable computing for applications in wireless communication, edge AI, and fault-tolerant systems. Key collaborations with institutions like IEEE and ACM through publications. Active in translating theoretical algorithms into practical hardware solutions for real-time systems. Research interests include: Optimizing deep learning models for heterogeneous platforms. Developing radiation-hardened memory systems. Creating energy-efficient signal processing architectures. Advancing reconfigurable functional units for embedded processors. His article analyses span fields like Quantum Cellular Automata , Variable Fractional Delay Filters , and RNS-Based Position Estimation , reflecting a trend toward adaptive, low-power, and domain-specific hardware.

• Neuromorphic Engineering
• Compute-in-Memory Architectures
• Dynamic Vision Sensors
• +۴ مورد دیگر

Rajkumar Kubendran is an Assistant Professor at the University of Pittsburgh's Department of Electrical and Computer Engineering within the Swanson School of Engineering. His research focuses on neuromorphic engineering, low-power analog circuits, and biomedical hardware design. He holds a PhD from the University of California San Diego (2014–2020), an MS from Purdue University (2009–2012), and a B.Tech from the National Institute of Technology (2004–2008). His work includes prototypes like dynamic vision sensors (DVS) and in-memory compute architectures, with applications in event-driven computer vision and medical devices. Research interests span brain-machine interfaces, compute-in-memory systems, and neuromorphic computing for robotics and biomedical applications. Notable projects include retina-inspired cameras, custom AI hardware, and programmable stimulators for neural interfaces. His team emphasizes energy-efficient architectures and bio-inspired designs, with recent publications in areas like event-based sensorimotor control and neuromorphic benchmarking frameworks. Professional experience includes internships at Intel, IMEC Belgium, MaxLinear, and Qualcomm. He is an IEEE Senior Member. Though no awards are explicitly listed, his contributions to neuromorphic systems reflect significant technical impact. Current work integrates hardware-software co-design for scalable neuromorphic systems and biomedical device startups.

Erika Coviمشاهده پروفایل

استادیار

• Neuromorphic Engineering
• Electronic Engineering
• Materials Science
• +۳ مورد دیگر

Erika Covi is an Assistant Professor at the University of Groningen, affiliated with the Faculty of Science and Engineering and the Bio-inspired Circuits & Systems group within the Zernike Institute for Advanced Materials. Her research focuses on neuromorphic engineering, leveraging emerging materials like ferroelectric and memristive devices to design bio-inspired circuits and systems. Key areas include ferroelectric tunnel junctions (FTJs), spiking neurons, and neuromorphic edge computing. She collaborates on compact modeling for efficient circuit simulations and explores applications in energy-efficient neural networks. Her work integrates interdisciplinary approaches from materials science, electrical engineering, and computational neuroscience. Research interests span device physics of ferroelectric materials, analog neuromorphic hardware, and neuromorphic computing architectures. She has contributed to studies on coincidence detection in spiking neurons using ferroelectric polarization and tunable synaptic working memory with memristive devices. Current projects emphasize bridging device-level innovations with system-level neuromorphic applications, aiming to advance bio-inspired computing technologies.

• Natural Language Processing
• Multimedia Networking
• Software Defined Systems
• +۶ مورد دیگر

Jason Quinlan is a Lecturer in the Department of Computer Science at University College Cork (UCC), Ireland. He holds a PhD in Computer Science and has extensive experience in teaching undergraduate modules such as Introduction to Programming (CS1117), Problem-Solving (CS1022), and Team Software Project (CS3305). His current role includes coordinating the CSIT SOLAS support hub for first-year students. Previously, he served as a Senior Post-Doc Researcher focusing on Intelligent Video Delivery at the Edge for 5G networks with the SFI iVID Project and CONNECT institute. Research interests span Natural Language Processing , Video Streaming Optimization , Software Defined Networking , and 5G Infrastructure . He led the development of frameworks like D-LiTE (DASH performance evaluation) and GoDASH (Go-based HAS framework). His work emphasizes QoE/QoS metrics, adaptive streaming algorithms, and network simulation tools. Key achievements include publishing over 30 peer-reviewed articles (e.g., on DASH streaming, 5G dataset analysis), securing €21,744 in research grants, and supervising 2 PhD, 15 Master’s, and numerous undergraduate students. Collaborations span institutions like UC Riverside (USA) and Université Clermont Auvergne (France). He actively contributes to conferences like ACM Multimedia Systems and IEEE LANMAN. Teaching and outreach activities include the MISL Summer of Code initiative mentoring over 60 students since 2018, and completing certifications in Project Management (PRINCE2, Scrum) and Higher Education Teaching. He has reviewed for top journals including Multimedia Systems Journal and IEEE Transactions on Multimedia, and serves on program committees for ACM MM and NetSoft conferences.

• Machine Learning
• Sustainable Technology
• Neural Networks
• +۳ مورد دیگر

Monika Farsang is a PreDoc Researcher at the Institute of Computer Engineering, Vienna University of Technology, focusing on sustainable and bio-inspired machine learning solutions. She is actively involved in advancing neural network architectures for autonomous systems and computational efficiency. Research Interests : Machine Learning, Sustainable Technology, Neural Networks, Autonomous Agents, Computer Vision, Biologically-Inspired Computing Her recent work emphasizes the development of biologically-inspired recurrent neural networks (NCPs, LTCs) to reduce computational demands while maintaining interpretability, aligning with global efforts in sustainable AI. She has supervised two 2025 diploma theses on modeling partially observable environments and multimodal autonomous agents. Advising : Monika has guided students Stanusoiu, M.-T. and Clement, M.-L. in their research on biologically-inspired models and autonomous systems.

Rahul Panatمشاهده پروفایل

استاد

• Additive Manufacturing
• Micro/Nano Manufacturing
• 3D Printing
• +۱۲ مورد دیگر

Rahul Panat is a Professor in the Department of Mechanical Engineering at Carnegie Mellon University’s College of Engineering. He is affiliated with the Manufacturing Futures Institute, NextManufacturing Center, and the Wilton E. Scott Institute for Energy Innovation, where his research bridges advanced manufacturing, materials science, and biomedical engineering. Ph.D., Theoretical and Applied Mechanics, University of Illinois at Urbana-Champaign (2004) M.S., Mechanical Engineering, University of Massachusetts Amherst (1999) B.S., Mechanical Engineering, Pune University (1997) His research focuses on micro-scale additive manufacturing, particularly aerosol jet 3D nanoprinting, to develop high-performance biosensors, brain-computer interfaces, and energy storage systems. His lab pioneers techniques for 3D-printed ceramics, stretchable electronics, and ultra-sensitive pathogen detection platforms, including a rapid 3D-printed COVID-19 antibody test. The recent articles highlight a strong trend in additive manufacturing of functional microarchitectures , with applications in biomedical sensing , energy storage (3D batteries) , and ceramic nanostructures . Keywords span materials science, nanotechnology, and mechanical reliability, emphasizing scalable, high-precision fabrication methods. His scientific recognition includes an award for developing the world’s first fully green IC chip at Intel. Additional honors stem from groundbreaking work in sustainable electronics and high-performance sensors. Panat mentors students in the Panat Laboratory, where they work on printed electronics, flexible sensors, and battery architectures. He has secured grants from ARPA-H and the Scott Institute for Energy Innovation to advance implantable cancer detection and energy research. His work often involves interdisciplinary collaborations across engineering and healthcare. The Panat Laboratory focuses on solving fundamental challenges in printed microelectronics, flexible sensors, and Li-ion batteries, aiming to enable next-generation wearable devices, IoT systems, robotic skins, and bio-patches.

Reinhard Heckelمشاهده پروفایل

استاد

• Machine Learning
• Deep Learning
• Medical Image Processing
• +۳ مورد دیگر

Reinhard Heckel is a Professor of Machine Learning at the Department of Computer Engineering, Technical University of Munich (TUM). His career includes positions as a Tenure-Track Assistant Professor at Rice University (2017–2019) and postdoctoral fellow at UC Berkeley's Berkeley Artificial Intelligence Research Lab. He holds a PhD from ETH Zurich (2014) and conducted doctoral research at Stanford University’s Statistics Department. Recognitions include being named one of Germany's 'Top 40 under 40' (2022) and the Werner von Siemens Ring Foundation Award (2022). Education & Professional Background: PhD in Computer Science, ETH Zurich (2014) Visiting Doctoral Fellow, Stanford University (Statistics Department) Postdoctoral Fellowship, UC Berkeley (EECS Department) Research Focus: His work bridges theoretical foundations and practical applications in machine learning, including: Algorithm development for deep learning and medical image processing Mathematical foundations of machine learning DNA data storage technology (error correction, synthesis methods) Computational imaging and inverse problem solutions Awards & Highlights: 2022: Capital 40 under 40, Werner von Siemens Ring Foundation Award 2015: ETH Zurich Medal for Doctoral Thesis, IBM Invention Achievement Award Grants & Collaboration: His research has been supported by grants focusing on DNA storage scalability and MRI reconstruction. He collaborates with institutions like IBM Research and the Berkeley AI Lab. Key projects include developing DNA synthesis methods and AI-driven medical imaging tools. Labs & Teams: Leads TUM's machine learning initiatives in computational imaging and biological data storage systems. Active in interdisciplinary teams bridging computer science, bioengineering, and statistics.

Todd Griffithمشاهده پروفایل

دانشیار

• Mechanical Engineering
• Wind Energy
• Renewable Energy
• +۴ مورد دیگر

Dr. Todd Griffith is an Associate Professor of Mechanical Engineering at the University of Texas at Dallas (UTD), affiliated with the Erik Jonsson School of Engineering and Computer Science . He leads the Griffith Lab and focuses on advancing wind energy technologies, particularly floating offshore turbines and large-scale rotor systems. His research integrates structural dynamics, aerodynamics, and control engineering to enhance energy efficiency and reduce costs in renewable energy systems. Key areas of expertise include wind turbine design , additive manufacturing , and floating platform systems . He has secured significant grants, including a $3.3 million award from the U.S. Department of Energy's ARPA-E program to develop scalable floating offshore wind turbines. His work emphasizes bio-inspired design principles, such as mimicking natural structures (e.g., palm trees) to improve turbine resilience in extreme conditions. Dr. Griffith’s research also explores active flow control using plasma actuators and advanced materials for lightweight, durable components. His contributions span experimental validation, computational modeling, and field prototyping, with a focus on deep-water offshore wind energy systems. He has advised numerous projects funded by federal agencies and industry partners, contributing to the development of next-generation wind energy infrastructure. His lab collaborates on interdisciplinary initiatives, including turbine blade manufacturing, structural health monitoring, and cost-effective energy solutions.

Mien Vanمشاهده پروفایل

مدرس ارشد

• Robotics and Control Engineering
• Autonomous Systems
• Human-Robot Interaction
• +۵ مورد دیگر

Dr. Mien Van is a Senior Lecturer (a.k.a. Associate Professor) in Robotics and Control Engineering at Queen's University Belfast, UK. He leads multiple research projects in autonomous systems, human-robot collaboration, and underwater robotics. His work spans resilient control for autonomous vehicles, in-process manufacturing quality control, and bio-inspired robotics design. Education: Research Fellowships at National University of Singapore (2015-2017) and University of Exeter (2018-2019). Research Interests: Resilient Autonomy, Human-Robot Interaction, Underwater Vehicles, Fault Diagnosis. Awards: IET Premium Award (2017), Best Paper Awards from BK21 and ICROS. Key Projects: ORCA (Dstl/MOD-funded), Digital Twins for Underwater Operations (EPSRC), Offshore Wind Turbine Blade Monitoring (Innovate UK). Dr. Van has authored/co-authored over 75 journal papers with an h-index of 34 and >3,700 citations. He serves as Associate Editor for multiple top-tier journals including IEEE Transactions on Automation Science and Engineering.

• Aeronautics
• Fluid Dynamics
• Machine Learning
• +۷ مورد دیگر

Rodrigo Castellanos Garcia de Blas is an Assistant Professor in the Aerospace Engineering Department at Universidad Carlos III de Madrid (UC3M). His research spans interdisciplinary domains including fluid dynamics, machine learning, and thermal engineering, with applications in aerospace systems. Affiliation: Universidad Carlos III de Madrid Research Areas: Aeronautics, Turbulent Flow Control, Machine Learning Research Focus : Investigates aerodynamic surrogate modeling, convective heat transfer enhancement, and plasma actuator-based flow control in turbulent boundary layers. His work integrates computational methods with experimental validation. Publications Trends : Recent works emphasize machine learning for fluid flow control, aerothermal optimization, and experimental analysis of turbulent flows using advanced manufacturing techniques. Contact : rcastell@ing.uc3m.es | ORCID

Rongjie Laiمشاهده پروفایل

استاد

• Computational Mathematics
• Machine Learning
• Applied Geometry
• +۴ مورد دیگر

Rongjie Lai is a Professor of Mathematics at Purdue University's Department of Mathematics, part of the College of Science. His research focuses on computational mathematics, machine learning, and applied geometry, with contributions to manifold learning, operator learning, and partial differential equations. He holds a position in the Department of Mathematics and is affiliated with the College of Science's broader computational and mathematical initiatives. His research interests include developing mathematical frameworks for geometric and topological data analysis, optimization algorithms for high-dimensional data, and applications in scientific computing. Notable work involves advancing neural network architectures for complex systems and developing efficient methods for solving PDEs on manifolds. Recent publications emphasize interdisciplinary applications, such as mean-field games, adversarial training in neural networks, and bio-inspired computing. His work bridges theoretical foundations and practical applications, impacting fields like computational biology and materials science. Despite his extensive output, no specific awards or grants are explicitly listed in the provided text.

Michael Rubensteinمشاهده پروفایل

دانشیار

• Multi-Robot Systems
• Swarm Robotics
• Modular Self-Reconfigurable Robots
• +۴ مورد دیگر

Michael Rubenstein is an Associate Professor with joint appointments in the Computer Science and Mechanical Engineering departments at Northwestern University's McCormick School of Engineering. He holds the Lisa Wissner-Slivka and Benjamin Slivka Professorship. His research focuses on multi-robot systems, swarm robotics, and bio-inspired robotics, emphasizing scalable control and design for large robotic collectives. Ph.D. in Computer Science from University of Southern California (2009) M.S. in Electrical Engineering from University of Southern California (2005) B.S. in Electrical Engineering from Purdue University (2003) Research interests include swarm intelligence, self-assembly, and fault-tolerant systems. He has pioneered platforms like Kilobot and FireAnt, enabling affordable, large-scale robotic swarms. His work bridges robotics with biology, addressing challenges in distributed control and collective behavior. Key publications highlight advancements in swarm formation control, self-healing algorithms, and modular robotics. Recent trends emphasize environmental adaptation and decentralized systems. He has received awards such as the Sloan Fellowship and holds patents in robotic connectivity and sensing. Advises PhD students including Hanlin Wang and Petras Swissler Recipient of grants from DARPA and NSF Develops courses like 'Applied Mechatronics' and 'Special Topics in Swarms' Labs/Teams: Lead researcher in the Self-Organizing Systems Group, contributing to open-source robotics tools and educational platforms.

Graham Taylorمشاهده پروفایل

استاد

• Biomechanics
• Neurophysiology
• Animal Flight Dynamics
• +۷ مورد دیگر

Professor Graham Taylor is a Professor of Mathematical Biology at the University of Oxford and a Senior Research Fellow at Jesus College. He leads the Oxford Flight Group, focusing on biomechanics, neurophysiology, and bio-inspired engineering. His research combines experimental methods (e.g., virtual reality flight simulators) with computational models to understand animal flight dynamics and translate findings into robotics and AI. He holds a Royal Society University Research Fellowship and has received €1.95M from the ERC. His work spans Harris’ hawks, peregrine falcons, planthoppers, and insects, with applications in drone design and emergency response technology. Education: BA (Zoology, Pembroke College, Oxford), DPhil (Jesus College, Oxford) Key Roles: Deputy Head of MPLS Division, Director of John Krebs Field Station, Wytham Woods Research interests include evolutionary tuning of flight systems, flight control algorithms, and the intersection of physics and physiology. His lab collaborates with industry on spinouts like Animal Dynamics and engages the public through documentaries (e.g., Sky Nature’s Airborne ) and outreach programs. Notable achievements include the Thomas Henry Huxley Medal and ERC grants. Advising & Grants: Supervises doctoral students in biomechanics and robotics. Leads projects funded by the ERC, BBSRC, and industry partnerships. His lab hosts UNIQ program visits and public engagement activities, including a 2022 Oxford Science Festival exhibit.

Amanda Chicoliمشاهده پروفایل

مدرس

• Systems Neurobiology
• Neuroethology
• Collective Behavior
• +۳ مورد دیگر

Amanda Chicoli is a Lecturer in the Psychology Department at the University of Maryland, College Park. She serves as the research coordinator for the neuroscience major, faculty advisor for the neuroscience minor, and course director for NEUR305: Neural Systems and Circuits. Her roles include teaching multiple courses such as PSYC300 (Research Methods in Psychology), PSYC409 (Topics in Neuroscience), and PSYC489R (Human & Animal Intelligence). Previously, she was a postdoctoral fellow at the Carnegie Institution for Science, where she studied zebrafish dorsal habenulae using molecular, genetic, and whole-brain imaging techniques. Chicoli holds a PhD in Neuroscience and Cognitive Science (2016) from the University of Maryland and a BS in Biology and Psychology from Brooklyn College (2010). Her research focuses on systems neurobiology, neuroethology, and collective behavior, with applications to bio-inspired engineering. She is deeply committed to science education and curriculum development, particularly for neuroscience programs. Her work integrates computational modeling, experimental neuroscience, and immersive VR technology to explore animal behavior and decision-making in groups. Her research interests emphasize understanding how individual and collective behaviors emerge from neural and environmental interactions. Key projects include analyzing rheotaxis (current-following) in fish schools, modeling group decision-making, and investigating predator avoidance strategies. She has contributed to studies using zebrafish as a model organism to explore brain connectivity and function. Chicoli’s work bridges theoretical models with empirical observations, offering insights into both fundamental neuroscience and applied engineering challenges.

• Biomechanics
• Medical Robotics
• Neuromechanics
• +۳ مورد دیگر

Manish Narsipura Sreenivasa is a Senior Lecturer at the School of Mechanical, Materials, Mechatronic and Biomedical Engineering, University of Wollongong (since 2018). Previously, he held postdoctoral roles at the University of Heidelberg (Germany) and University of Tokyo (Japan), focusing on neuromuscular system modeling. He earned his Ph.D. in Systems Engineering from the University of Toulouse-Jean Jaurès (France). His research integrates computational neuroscience, biomechanics, and robotics to develop assistive devices like exoskeletons and prosthetics. Key areas include patient-specific orthosis design, neuromusculoskeletal modeling for clinical interventions, and spinal exoskeleton optimization. He leads projects funded by the EU H2020 (Spexor) and Australian grants. Fields of Expertise: Biomechanics, Medical Robotics, Wearable Technologies Awards: Hengstberger Award (2015), Leopold Escande Thesis Prize (2010), IEEE Best Paper (2010) Supervision: Active advisor for 6 Ph.D./Master’s students in biomechanics and robotics His recent work emphasizes human-device interaction in exosuits, sensory feedback systems for prosthetics, and ergonomic solutions for construction workers. He collaborates with orthopedic departments and industry partners to translate research into clinical applications.