جست‌وجوی استاد و پژوهشگر

• Neuromorphic Computing
• Organic Electronics
• Bioelectronics
• +۳ مورد دیگر

Paschalis Gkoupidenis is an Associate Professor in the Department of Electrical and Computer Engineering at North Carolina State University (since August 2024) and a Group Leader at the Department of Molecular Electronics at the Max Planck Institute for Polymer Research. His research focuses on developing organic neuromorphic devices for neuro-inspired information processing, learning, sensing, and bio-interfacing. Research Interests Dr. Gkoupidenis specializes in hardware-based implementation of neuromorphic architectures, which offer efficient ways of data manipulation and processing, especially in data-intensive applications. His work explores how organic materials and devices can be used for neuro-inspired devices and bioelectronics, leveraging their attractive characteristics such as ability to operate in electrolytes, spatiotemporal response, analogue memory phenomena, tunability via chemical synthesis, low-cost fabrication processes, and biocompatibility. His research group investigates various concepts for inducing neuroplasticity, learning forms, and spatiotemporal information processing functions at a single-device level, as well as new paradigms of neuromorphic architectures at circuit level. These neuro-inspired functions are essential for trainable/adaptable circuits in energy-restricted environments and for local signal processing in bioelectronics. Scientific Contributions Development of organic neuromorphic devices for neuro-inspired information processing Research on synaptic plasticity functions in organic electrochemical transistors Exploration of neuromorphic device architectures with global connectivity through electrolyte gating Investigation of functional connectivity of organic neuromorphic devices by global voltage oscillations Advancement of organic neuromorphic devices for adaptive sensing and novel computing paradigms in bioelectronics Affiliations Associate Professor, Department of Electrical and Computer Engineering, North Carolina State University (since August 2024) Group Leader, Organic Neuromorphic Electronics, Max Planck Institute for Polymer Research (since 2017) Postdoctoral Researcher, Department of Bioelectronics, EMSE, France (2015-2017)

James C. Davisمشاهده پروفایل

استادیار

• Empirical software engineering
• Security
• Safety
• +۷ مورد دیگر

James C. Davis is an Assistant Professor in the Elmore Family School of Electrical and Computer Engineering at Purdue University. He leads the Duality Lab, which focuses on the engineering of software-intensive computing systems with particular interest in how these systems fail and how those failures can be mitigated. His research takes a socio-technical approach, considering both human and technical perspectives in system engineering. Dr. Davis received his PhD in Computer Science from Virginia Tech, where he was advised by Dongyoon Lee. His research interests span empirical software engineering, security, safety, testing, and web technologies, with a strong emphasis on practical impact and measurement. He applies a socio-technical philosophy to his work, believing high-quality systems must be engineered considering both human and technical perspectives. His recent research focuses on software supply chain security, regular expression vulnerabilities (particularly ReDoS), pre-trained model security, and failure analysis in software systems. His work often involves empirical studies of real-world software systems and security practices, with a strong emphasis on practical impact and measurable results. Dr. Davis has received significant funding from the National Science Foundation, Google, Cisco, and Rolls Royce for his research. His publications appear in top-tier venues including ICSE, FSE, ASE, and USENIX Security. He has served on program committees for many major software engineering and security conferences. Among his notable achievements are being elevated to IEEE Senior Member in 2022, receiving the Ruth and Joel Spira Outstanding Teacher Award from ECE@Purdue in 2022, and multiple Best Paper and Best Poster awards. He has successfully mentored numerous PhD and Master's students, with several completing their theses on topics related to software security and engineering. Dr. Davis actively recruits graduate and undergraduate research assistants for his Duality Lab, which has produced influential work on software failure analysis, regular expression security, and machine learning supply chain security. His lab is supported by multiple federal and industry grants focused on improving the security and reliability of software systems.

Li Yangمشاهده پروفایل

استادیار

• Cybersecurity
• Machine Learning
• Deep Learning
• +۱۲ مورد دیگر

Li Yang is an Assistant Professor in the Department of Information Technology , part of the Faculty of Business and Information Technology at Ontario Tech University. His research focuses on applying AI and machine learning to cybersecurity, particularly in intrusion detection and anomaly detection for 5G/6G networks and IoT systems. He holds a PhD in Electrical and Computer Engineering from Western University (2022), and has held roles such as Vice Chair of IEEE Computer Society, London Section (2022–2023). Education: PhD in Electrical and Computer Engineering, Western University (2022) Master of Science, University of Guelph (2018) Bachelor of Engineering, Wuhan University of Science and Technology (2016) Research Interests: His work spans cybersecurity, machine learning, deep learning, AutoML, model optimization, network automation, IoT security, intrusion detection, and adversarial machine learning. He develops frameworks for concept drift adaptation and online learning to enhance cybersecurity measures, with a focus on trustworthy AI and defense strategies against adversarial attacks. Awards: Graduate Student Award for Excellence in Research (2022) Graduate Symposium Award for Best Presentation (2022) Mitacs Accelerate Fellowship (2021) OC2 Lab Industrial Research Excellence Award (2020) Ranked in Stanford/Elsevier's Top 2% Scientists (2024) Grants & Involvement: Li Yang has contributed to conferences like IEEE GlobeCom and IEEE CCECE, and authored patents such as 'Convenient primary-secondary barrels' (2009). His work has garnered thousands of citations and GitHub stars, emphasizing practical applications of AI in cybersecurity.

Tim Oatesمشاهده پروفایل

استاد

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

Dr. Tim Oates is a Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County . His research spans machine learning, artificial intelligence, and brain-machine interfaces, with a focus on weakly supervised methods, human-in-the-loop reinforcement learning, and grounded policy development for robotics. Ph.D., Computer Science, University of Massachusetts, Amherst, 2000 M.S., Computer Science, University of Massachusetts, Amherst, 1997 B.S., Computer Science and Electrical Engineering, 1989 Current research threads include: Developing non-invasive brain injury severity assessment via medical time series Modeling human brain development through computational frameworks Designing algorithms for autonomous robotic learning Recent publications highlight AI security mechanisms (backdoor detection via tensor decomposition, matrix factorization) Medical applications (3D artery reconstruction, skin lesion diagnosis, EEG denoising) Neuro-symbolic integration (holographic representations, language-guided reinforcement learning) Mathematical reasoning (schema-based problem solving, subitizing algorithms) Contact: oates@cs.umbc.edu | Office: 336 Information Technology and Engineering (ITE) Building

• Materials Science
• Nanotechnology
• Photonics
• +۴ مورد دیگر

Dr. Keng-Te Lin is a Research Fellow at RMIT University's School of Science, specializing in advanced materials for energy, photonics, and biomedical applications. His work focuses on metamaterials, radiative cooling, graphene-based technologies, and nanophotonic devices. He supervises research projects on topics like spectral selective radiative cooling, electro-optically tunable waveguides, and machine learning for thermal-photovoltaic systems. Key research interests include developing high-performance materials for thermal management, energy conversion, and biomedical therapies. His recent publications highlight innovations in flexible radiative cooling films, ultrafast heat transfer mechanisms, and scalable manufacturing methods for sustainable cooling solutions. Dr. Lin collaborates on projects involving structured metamaterials for solar thermal energy, plasmonic nanostructures for photodetection, and nanocomposite materials for enhanced catalytic activity. He actively supervises students exploring topics such as photonic topological insulators, perovskite solar cells, and AI-driven material optimization. His research bridges fundamental materials science with applied engineering solutions, targeting applications in renewable energy, environmental sustainability, and healthcare technologies.

Pooya Davariمشاهده پروفایل

استاد

• Harmonic and EMI analysis and mitigation in grid-tied converters
• Electromagnetic interference and compatibility
• High power density power electronic systems
• +۲ مورد دیگر

Pooya Davari is a Professor and Head of the Section for Applied Power Electronic Systems at Aalborg University , Denmark. He leads the EMI/EMC in Power Electronics Research Group and serves as Vice Chair of the Energy Efficiency Mission. His research focuses on electromagnetic interference (EMI) and harmonic mitigation in power electronic systems, with over 200 publications and significant contributions to renewable energy integration. Education: B.Sc. and M.Sc. in Electronic Engineering (2004, 2008), Ph.D. in Power Electronics from Queensland University of Technology (2013) Prior Roles: Lecturer at QUT (2013–2014), Postdoc at AAU (2014) Research Interests: Harmonic and EMI analysis in grid-tied converters High power density converter design Signal processing for converter modeling Reliability of power electronic systems Article Trends: Recent work emphasizes EMI/EMC in renewable energy systems, wide bandgap semiconductors (SiC/GaN), and reliability modeling for EVs and hydrogen production via electrolysis. Sub-fields include converter topologies, grid integration challenges, and AI-driven diagnostics. Scientific Awards: Equinor 2022 Prize (Denmark’s oldest engineering award) IEEE EMC Society Young Professional Award (2020) World’s Top 2% Highly Cited Scientist (Stanford, 2021–2025) Multiple best paper awards (IEEE, Applied Sciences, etc.) Grants & Editorial Roles: Recipient of grants from Innovation Fund Denmark (Supra-EMC project), Horizon Europe (SOLARIS), and industry partnerships. Serves as Area Editor for IEEE Transactions on Transportation Electrification , Associate Editor for IEEE Transactions on Power Electronics , and Editor-in-Chief of Circuit World Journal (2020–2025). Labs & Standards: Coordinator of the EMC Laboratory at Aalborg University. Member of IEC standardization Working Groups 6 and 8 (TC77A), focusing on EMC strategies for power grids.

• Energy-Efficient Systems
• Wireless Power Transfer
• IoT Infrastructure
• +۳ مورد دیگر

Ankit Mittal is a Research Fellow in the Department of Electrical and Computer Engineering at Northeastern University. His research focuses on energy-efficient systems, wireless power transfer, IoT infrastructure, analog circuit design, and biomedical applications such as neural implants. He is based at 360 Huntington Ave, Boston, MA 02115, and can be reached at a.mittal@northeastern.edu. Mittal's work emphasizes secure analog circuit design, energy harvesting techniques for ultra-low power applications, and the integration of magnetoelectric antennas for medical and IoT devices. His research bridges electronics, signal processing, and biomedical engineering, with a particular emphasis on practical implementations for precision agriculture and neural monitoring systems. His publications highlight advancements in IoT security, RF rectifier optimization, and the development of compact, efficient energy harvesting systems. The articles collectively reflect a trend toward low-power, high-efficiency solutions for wireless communication and biomedical engineering challenges. No scientific awards or grants are explicitly mentioned in the provided information. Mittal currently has no listed advisees or students. Labs or collaborative teams associated with his work are not detailed in the available text.

Brenna D. Argallمشاهده پروفایل

دانشیار

• Robotics
• Rehabilitation Engineering
• Human-Robot Interaction
• +۳ مورد دیگر

Brenna D. Argall is an Associate Professor of Computer Science, Mechanical Engineering, and Physical Medicine & Rehabilitation at Northwestern University, and a Faculty Research Scientist at the Shirley Ryan AbilityLab. Her research focuses on assistive and rehabilitation robotics, with an emphasis on human-robot interaction, shared autonomy, and intelligent control systems. She holds a PhD in Robotics from Carnegie Mellon University and has held postdoctoral fellowships at EPFL (Switzerland) and the NIH. Education: PhD in Robotics, Carnegie Mellon University (2009) Postdoctoral Fellow, EPFL (2009–2011) B.S. in Mathematics, Carnegie Mellon University (2002) Affiliations: Director, Argallab (Assistive & Rehabilitation Robotics Laboratory) Member, Northwestern Center for Robotics and Biosystems Advisor, Northwestern MS in Robotics Program Her research explores dynamic autonomy allocation , shared control systems , and interface-aware robotics , with applications in rehabilitation and assistive devices. Key projects include wheelchair automation, robotic arm control, and body-machine interfaces for users with motor impairments. Research Highlights: NSF CAREER Award (2016) AIMBE Fellow (2020) "40 under 40" Innovator (Crain’s Chicago Business) Publications emphasize human-centered robotics, including over 50 peer-reviewed articles on topics like intent inference, assistive autonomy, and teleoperation assistance. Current lab efforts prioritize interface-aware systems and customizable shared control to enhance accessibility for users with disabilities.

Christoph Leitnerمشاهده پروفایل

پژوهشگر ارشد

• Convergent Technologies
• Ultrasonics
• Machine Learning
• +۳ مورد دیگر

Dr. Christoph Leitner is a Research Fellow at ETH Zurich's Integrated Systems Laboratory under Prof. Luca Benini, focusing on biomedical and IoT applications. His work integrates printed piezoelectric transducers and flexible electronics with energy-efficient systems. He holds a PhD in Biomedical Engineering from TU Graz (2022) and has collaborated with institutions like Sant'Anna School of Advanced Studies and KTH Stockholm. Notable achievements include the Josef Krainer Young Researcher Award and Motorik Scholarship. Leitner's research spans ultrasonics, machine learning, and wearable devices, with contributions to muscle-tendon dynamics and real-time biofeedback systems. Education: PhD in Biomedical Engineering, TU Graz (2022), Advisor: Prof. Christian Baumgartner Previous roles: University Assistant (2006–2011) and R&D Engineer at Virtual Vehicle GmbH Research Interests: Convergent technologies merging biomedical engineering and IoT Ultrasound-based monitoring for musculoskeletal systems Energy-efficient embedded systems for wearable applications Collaborations & Awards: Recipient of Josef Krainer Young Researcher Award (2023) and Motorik Scholarship (2018) Active collaborations with University of Zurich, Veterinary University of Vienna, and Queensland University of Technology Labs & Projects: Integrated Systems Laboratory at ETH Zurich Developed a patented ultrasound-transparent tattoo-based SEMG system with Prof. Francesco Greco

Michael Thompsonمشاهده پروفایل

استاد

• Semiconductor Physics
• Materials Science
• Laser Processing
• +۷ مورد دیگر

Professor Michael Thompson is a tenured faculty member in the Department of Materials Science and Engineering at Cornell University's College of Engineering. He holds the Dwight C. Baum Professorship in Engineering and specializes in advanced materials processing, particularly semiconductor materials under pulsed laser exposure. His research focuses on transient thermal processing (nanosecond to sub-second timescales) for material property modification and characterization, with applications in semiconductors, EUV lithography, and photonic materials. Thompson has authored over 120 papers and 20 patents, emphasizing industrial challenges like front-end junction formation and flexible electronics. Education: B.S. in Physics (CalTech, 1979), M.S./Ph.D. in Physics (Cornell, 1982/1984). He has received prestigious awards including the North American Award for Technical Contribution to the Semiconductor Industry (2009), multiple Cornell Excellence in Teaching Awards, and the Stephen H. Weiss Presidential Fellow designation (2021). His teaching focuses on thermodynamics and electronic properties, with a commitment to making abstract concepts accessible through real-world examples. Service: Leads curriculum development, ABET accreditation, and industry outreach. His lab develops novel methods for autonomous materials discovery using AI-driven approaches. Current projects include laser spike annealing for semiconductor doping and high-throughput synthesis of metastable materials.

Patrick Gaudreauمشاهده پروفایل

استاد

• Social Psychology
• Personality Psychology
• Perfectionism
• +۷ مورد دیگر

Patrick Gaudreau is a Full Professor in the School of Psychology at the University of Ottawa, where he specializes in social and personality psychology. His research focuses on the determinants and consequences of achievement in educational, sport, and artistic domains, particularly through the lens of his Model of Excellencism and Perfectionism (MEP). The MEP distinguishes between healthy pursuit of excellence and harmful perfectionism, emphasizing how these motivations affect performance, psychological adjustment, and social behaviors. Gaudreau's work highlights the benefits of excellencism, such as reduced distress and ethical attitudes compared to perfectionism. He also investigates motivational dynamics, coping strategies, and the impact of digital devices on learning. Education: Ph.D. in Psychology, Université de Montréal (2004) M.Sc. in Psychology, Université de Montréal (2000) B.Sc. in Psychology, Université de Montréal (1999) Research Interests: Perfectionism vs. excellencism, achievement goals, self-determination theory, performance anxiety, sport psychology, health psychology, and quantitative methods. His laboratory, LAMRA (Laboratory for Research on Achievement, Motivation, and the Regulation of Action), explores interactionist perspectives on how social environments and individual traits shape achievement outcomes. Recent Articles: Recent work examines psychological needs in the context of excellencism, perfectionism's impact on social disconnection, and the motivational roles of fear of failure. His findings advocate for interventions to transform perfectionism into excellencism to enhance both performance and well-being. Awards: None explicitly listed, but recognized as editor of Anxiety, Stress, and Coping and for over 100 scientific publications. Active in applied settings, including coaching youth baseball and advising on athlete well-being. Advising & Grants: Supervises numerous graduate students and collaborates on grants focusing on perfectionism, excellencism, and motivational interventions. His research has been supported by studies on procrastination, academic transitions, and the psychological effects of sport participation. Labs/Teams: Leads the LAMRA, a multidisciplinary team investigating achievement-related processes. Engaged with the Student-athlete Well-being and Achievement Project (SWAP), examining sport and academic outcomes for student-athletes.

Abubakar Belloمشاهده پروفایل

مدرس ارشد

• Cyber Security
• Cyber Crime
• Cyber Criminology
• +۳ مورد دیگر

Dr. Abubakar Bello is a Senior Lecturer in Criminal Justice and Program Leader at Edge Hill University's School of Law, Policing, and Criminal Justice. Previously, he held roles at Western Sydney University, including Academic Program Advisor and Lecturer in Cyber Security and Behaviour. He holds a PhD in Cyber Criminology, an MBA in Business Law and Technology, and degrees in Computer Science. His research focuses on interdisciplinary approaches to cyber security risks, threat intelligence models, and behavioral aspects of cyber crime. Education: PhD (Cyber Criminology, Murdoch University), MBA (Business Law & Tech, Western Sydney University), MSc & BSc (Computer Science, University of Wolverhampton). Research Interests: Combating cyber crime through AI and machine learning, secure systems design, and behavioral cybersecurity. Key areas include ransomware defenses, social engineering, and cybersecurity frameworks for diverse populations. Grants & Projects: Awarded funding for initiatives such as 'Social Engineered Payment Diversion Fraud' (NSW Cyber Security Network), 'Brain-Inspired Algorithm for Network Anomaly Detection' (DST Group), and 'Cyber Security Awareness Framework' (ECR Grant). Awards: 'Award for Teaching and Learning Contributing to Public Good.' Active in professional networks like the International Centre on Racism and Centre for Applied Criminal Justice Research. Labs & Collaboration: Engages in cyber investigations, forensics, and community outreach through initiatives like Western Cyber Aid. Serves as a consultant for corporate espionage cases and a speaker on ransomware and AI in law enforcement.

• Computer Networks
• Internet of Things (IoT)
• Sensor Networks
• +۷ مورد دیگر

Jorge Garcia Vidal is a Professor in the Department of Computer Architecture at the School of Computer Science, Universitat Politècnica de Catalunya (UPC). He is a key member of the CNDS - Computer Networks and Distributed Systems research group, with a sustained record of research activity from the late 1980s to the present, including publications projected into 2025. His work bridges theoretical network performance analysis and applied IoT systems, particularly in environmental monitoring. His research interests center on Computer Networks , Internet of Things (IoT) , Sensor Networks , and Data Quality in IoT . He has made significant contributions to ATM network performance, medium access control, and traffic modeling. More recently, his focus has shifted to air quality monitoring using low-cost sensor networks, employing techniques in Graph Signal Processing , Machine Learning , and Anomaly Detection to improve data reliability and estimate pollutants like black carbon. The recent article trends show a strong emphasis on developing data-driven frameworks, virtual sensors, and robust models for environmental IoT platforms. His work integrates advanced signal processing and machine learning to address the challenges of heterogeneous, low-cost sensor data in urban settings. His scientific achievements have been recognized with awards including the Premio Extraordinario de Doctorado and the Premio Mejor Tesis Doctoral . He has advised several doctoral students, including Pau Ferrer-Cid, David Fusté Vilella, Steluta Iordache, and Julian David Morillo Pozo. He is actively involved in numerous competitive and non-competitive R&D projects, such as those related to digital twins, IoT platforms for smart cities, and nature-based urban solutions, often funded by state and regional programs. He collaborates extensively within UPC and with external partners. His research is conducted primarily within the CNDS research group at UPC, a collaborative environment focused on computer networks and distributed systems, with connections to broader initiatives in smart cities and environmental monitoring.

Roozbeh Razavi-Farمشاهده پروفایل

استادیار

• Machine Learning
• Cybersecurity
• Federated Learning
• +۵ مورد دیگر

Roozbeh Razavi-Far is an Assistant Professor at the Faculty of Computer Science and the Canadian Institute for Cybersecurity at the University of New Brunswick. His research focuses on machine learning, big data analytics, and cybersecurity of cyber-physical systems and IoT devices. He has authored/co-authored over 150 publications and is listed by Stanford as among the top 2% of most cited researchers (2022). His work spans federated learning, transfer learning, quantum machine learning, and dependable AI systems. He serves as an Associate Editor for Neurocomputing, Machine Learning with Applications, and IEEE Transactions on Industrial Cyber-Physical Systems, among others. As an IEEE Senior Member, he chairs IEEE Computational Intelligence and Systems, Man, and Cybernetics Societies. Previously, he directed the Learning System and Cybernetics Group at the University of Windsor (2016–2022). His research interests emphasize security in non-stationary environments, adversarial machine learning defenses, and real-time analytics for smart grids. Awards include NSERC-DG, NSERC-ECR, and USRG grants. He has mentored students who received NSERC Alexander G. Bell, MITACS, and Ontario Graduate Scholarships. His recent publications highlight advancements in privacy-preserving split learning, blockchain-based federated learning security, and graph-based malware detection. He also explores quantum computing applications in AI and cybersecurity frameworks for cyber-physical systems.

NICOLA PESERICOمشاهده پروفایل

استاد پژوهشی

• Integrated Optical Circuits
• Silicon Photonics
• Hardware for Machine Learning
• +۴ مورد دیگر

Nicola Peserico is a Research Professor in the Department of Electrical & Computer Engineering at the University of Florida, affiliated with the College of Engineering. His primary research focus is on Integrated Optical Circuits and Silicon Photonics, with an emphasis on heterogeneous integration, hardware for Machine Learning/Neural Networks, and biosensing applications using integrated photonics. Education: Ph.D. (2018), M.S. (2014), and B.S. (2011) in Telecommunication Engineering from Politecnico di Milano. His research explores cutting-edge photonic technologies for accelerating neural networks, including Fourier-based convolution operations, reconfigurable circuits for solving PDEs, and energy-efficient optical interconnects. Recent work highlights advancements in photonic-electronic ICs, thermal management in photonic systems, and overcoming bottlenecks in memory and compute architectures. His publications emphasize photonic tensor cores, joint transform correlators, and silicon photonics integration for AI acceleration. Notable contributions include roadmap analyses for neuromorphic photonics and innovative packaging strategies for photonic neural network accelerators. No scientific awards or grants are explicitly listed in the provided texts. His advising record is not documented here. Labs/Teams: His work is part of broader efforts in photonic computing and AI hardware acceleration at the University of Florida, leveraging silicon photonics for next-generation computing systems.