جست‌وجوی استاد و پژوهشگر

• Cyber-Physical Systems
• System Safety Assurance
• Model-Based Engineering
• +۲ مورد دیگر

Sohag Kabir is an Associate Professor in the School of Computer Science, Artificial Intelligence, and Electronics at the University of Bradford. He leads the MSc Big Data Science and Technology, MSc Artificial Intelligence and Machine Learning, and MSc Applied Computer Science and Artificial Intelligence programs. He holds a Ph.D. in Computer Science from the University of Hull (2016), an M.Sc. in Embedded Systems, and a B.Sc. in Computer Science and Engineering. Dr. Kabir's research focuses on safety, reliability, and security assurance of cyber-physical autonomous systems. His work includes model-based safety analysis, probabilistic risk assessment, dynamic reliability analysis, and stochastic modeling. Current projects address IoT security, machine learning certification for automotive systems, and dependability frameworks for complex systems. His publications demonstrate consistent focus on developing integrated frameworks for system dependability, with recent work emphasizing IoT security, autonomous vehicle safety, and AI certification challenges. Dr. Kabir has contributed to multiple EU-funded projects including DEIS (Dependability Engineering Innovation for Cyber-Physical Systems) and MAENAD (Model-based Analysis & Engineering of Novel Architectures for Dependable Electric Vehicles).

Paul Scherzمشاهده پروفایل

استاد

• Moral Theology
• Christian Ethics
• Bioethics
• +۷ مورد دیگر

Paul Scherz is the Our Lady of Guadalupe Professor of Theology at the University of Notre Dame, holding appointments in the Department of Theology within the College of Arts and Letters. His interdisciplinary work bridges theology, science, medicine, and technology, focusing on virtue ethics—particularly Stoic ethics—in moral theology. Dr. Scherz earned a BA in molecular and cell biology from UC Berkeley (2001), a PhD in genetics from Harvard (2005), and completed a postdoctoral fellowship at UCSF. He later obtained an MTS and PhD in moral theology from Notre Dame (2010, 2014). Prior to his current role, he taught at the Catholic University of America and the University of Virginia. His research interests include bioethics (genetic technologies, end-of-life ethics), technology ethics (AI governance, algorithmic risk), and the historical influence of Stoic philosophy on Christian ethics. Notable publications include The Ethics of Precision Medicine (2024) and Tomorrow’s Troubles (2022), exploring risk ethics and algorithmic governance. He co-edits the Encountering Artificial Intelligence series with the Holy See’s Dicastery for Culture. Current projects address AI ethics, particularly virtue ethics frameworks for military AI and the anthropological implications of algorithmic systems. He critiques depersonalization in healthcare AI and advocates for ethical integration of scientific advancements with moral prudence. His work examines intersections between science and theology, including Laudato Si’-inspired ecological ethics and the moral formation of scientists in big data contexts. He has contributed to debates on CRISPR technology, brain death criteria, and the commodification of human tissue in vaccine development.

Md Noor-A-Rahimمشاهده پروفایل

استادیار

• Intelligent Transportation Systems
• Machine Learning
• Internet of Things
• +۴ مورد دیگر

Dr. Md Noor-A-Rahim is an Assistant Professor (Lecturer-Above the Bar) at the School of Computer Science and Information Technology, University College Cork (Ireland). He previously served as a Senior Researcher and Marie Curie Fellow at the same institution. His academic journey includes a PhD from the University of South Australia (2015) and the prestigious Michael Miller Medal for his outstanding thesis on wireless communication systems. His research focuses on Intelligent Transportation Systems, Machine Learning, IoT, Wireless Networks, and DNA-based data storage. He has published extensively on topics like 6G-V2X systems, time-sensitive networking, and error characterization in DNA storage. His work integrates cutting-edge technologies such as intelligent reflecting surfaces (IRS), federated learning, and ultra-reliable low-latency communication (URLLC). Research Interests : Dr. Rahim's research bridges theoretical advancements and real-world applications in vehicular networks, smart manufacturing, and next-generation communication systems. He explores challenges in autonomous driving, edge computing, and bio-constrained data storage. His contributions include novel coding schemes for anytime transmission and frameworks for mitigating big vehicle shadowing in V2X communications. Key Publications : His recent work includes a comprehensive survey on wireless TSN (2025), analysis of 6G-V2X systems (2022), and breakthrough studies on DNA data storage error modeling (2023). These publications highlight his expertise in both foundational research and industry-relevant solutions. Awards : Recipient of the Michael Miller Medal (2015) for doctoral research excellence. Grants & Labs : While specific grants are not listed in the text, his research portfolio suggests involvement in collaborative projects with industry partners and funding bodies. He leads interdisciplinary efforts in smart manufacturing and vehicular communication systems.

Patrick W. C. Hoمشاهده پروفایل

مدرس

• Memristor
• Non-volatile memories
• VLSI
• +۷ مورد دیگر

Dr. Patrick W. C. Ho is a Lecturer in the Department of Electrical & Computer Systems Engineering (ECSE) at Monash University Malaysia School of Engineering. He holds a PhD in Electronics Engineering from the University of Nottingham Malaysia Campus (2016), with research focusing on non-volatile FPGA architectures using memristors. His academic journey includes roles as a Scholarly Teaching Fellow and unit coordinator for courses like ECE2131 Electrical Circuits and ECE4063 Large Scale Digital Design. He has industry experience with Intel Microelectronics and Altera Corporation, alongside teaching A-level Physics at Methodist College Kuala Lumpur. Education: BEng (First Class Honours) in Engineering (2009) MSc in Science (2012) PhD in Electronics Engineering (2016) Research Interests: Dr. Ho specializes in memristor-based non-volatile memory systems, VLSI design, and FPGA architectures. His work bridges hardware design with emerging materials, as seen in his Q1 journal article on memristive LUTs. Collaborations with CAD-IT expand his focus into AI, image processing, and object recognition. Recent projects include studies on memristor substrate performance (2023–2026) and UAV communication reliability (2021–2024). Teaching and Industry Engagement: As ECSE’s Industrial Training Advisor and IAP representative, he actively connects academic curricula with industry needs. His teaching spans foundational engineering courses and advanced digital design modules. Labs and Collaborations: Active in CAD-IT partnerships for student FYP co-sponsorship. Research groups focus on nanotechnology, machine learning integration in UAV systems, and memristor material analysis.

Mehrdad Moallemمشاهده پروفایل

استاد

• Control Systems
• Power Electronics
• Energy Harvesting
• +۳ مورد دیگر

Dr. Mehrdad Moallem is a Professor and Graduate Student Supervisor in the Department of Mechatronic Systems Engineering at Simon Fraser University (SFU). He holds a Ph.D. in Electrical & Computer Engineering from Concordia University (1997), an M.Sc. from Sharif University (1988), and a B.Sc. from Shiraz University (1986). His research focuses on control systems in sustainable energy, power electronics, energy harvesting, robotics, and embedded systems. He has authored/co-authored four technical books and serves on editorial boards for journals like IEEE/ASME Transactions on Mechatronics. Dr. Moallem has held academic roles at Duke University and the University of Western Ontario. His teaching includes courses on real-time control systems, mechatronics design, and microprocessors. Research interests span embedded control systems, nonlinear dynamics, and applications in renewable energy and robotics. Recent work includes IoT-enabled lighting systems for agriculture, RF cavity control, and smart energy harvesting. He emphasizes hands-on student projects and industry collaboration, such as the Siemens Certification Program and Industry 4.0 bootcamps. Dr. Moallem's lab develops innovative solutions for energy efficiency and automation, with a focus on sustainable systems and smart manufacturing. He actively advises graduate students on advanced topics like grid-connected inverters, motor drives, and vibration control.

Michael Everettمشاهده پروفایل

استادیار

• Robotics
• Motion Planning
• Control Theory
• +۶ مورد دیگر

Michael Everett is an Assistant Professor at Northeastern University with a joint appointment in the Department of Electrical & Computer Engineering and the Khoury College of Computer Sciences. He directs the Autonomy & Intelligence Laboratory, focusing on certifiable learning machines at the intersection of robotics, deep learning, and control theory. His research emphasizes safety, reliability, and efficiency in robotics applications like off-road navigation and social environments. Education: PhD in Mechanical Engineering, Massachusetts Institute of Technology (2020) SM in Mechanical Engineering, MIT (2017) SB in Mechanical Engineering, MIT (2015) Research Interests: Robotics and motion planning Control theory and neural network verification Reinforcement learning applications Certifiable safety guarantees for autonomous systems Navigation in dynamic/human environments Awards: Runner-Up: Best Paper Award (ICML 2022) Winner: Best Student Paper (IROS 2017/2023) Editors’ Top 5 Published Articles (IEEE Access 2021) Lab & Contributions: The Autonomy & Intelligence Lab develops algorithms for high-speed off-road autonomy, socially aware navigation, and neural feedback verification. His work includes the RAMP planning pipeline and Evora traversability learning framework. He collaborates with Google’s PAIR team on trustworthy AI.

Dimitrios Koutsonikolasمشاهده پروفایل

دانشیار

• Wireless Networking
• Mobile Computing
• Millimeter Wave Networking
• +۵ مورد دیگر

Dr. Dimitrios Koutsonikolas is an Associate Professor in the Electrical and Computer Engineering Department at Northeastern University, leading the WiNS Lab. Previously, he held a tenured position at the University at Buffalo. His research focuses on experimental wireless networking and mobile computing, particularly millimeter-wave systems, 5G/6G networks, energy-efficient protocols, and high-bandwidth applications like VR/AR. He has published over 80 papers in top venues (e.g., MobiCom, INFOCOM), received NSF CAREER and IEEE awards, and led major grants including an NSF-funded $3M project for an open 5G/6G testbed. His lab explores cutting-edge technologies like O-RAN, beam management, and edge computing for latency-critical applications. Education: PhD in Electrical and Computer Engineering from Purdue University (2010). Research Interests: Experimental validation of wireless protocols, mmWave networking, latency-optimized edge computing, and cross-layer design. Current projects include TARGET (5G/6G latency solutions) and the X5G testbed for open spectrum utilization. Recent Trends in Articles: Focus on 5G deployment maturity, mmWave beam management, and 6G-ready technologies like autonomous space networks. Work bridges theoretical contributions with practical implementations, leveraging testbeds for real-world validation. Awards: Notable honors include IEEE Region 1 Innovation (2019), NSF CAREER (2016), and multiple best paper awards at MobiCom, WCNC, and Globecom. Recognized for both research and teaching excellence. Grants & Labs: Principal investigator on NSF grants ($3M+), leading collaborations with IMDEA Networks and industry partners. WiNS Lab develops open-source tools for 5G testing and explores sub-THz channels. Advises over 15 students, many advancing to top tech firms (e.g., Apple, HP Labs).

Changsheng Wuمشاهده پروفایل

استاد

• Wireless Bioelectronics
• Energy Harvesting
• Advanced Manufacturing
• +۴ مورد دیگر

Dr. Changsheng Wu is a Professor at the National University of Singapore (NUS), leading the Lab for Intelligent Sensing, Harvesting and Actuation (LISHA). He holds a Bachelor's from NUS and a PhD from Georgia Tech, with postdoctoral research at Northwestern University. His work focuses on wireless wearables, bioelectronics, energy harvesting, and advanced manufacturing for sustainable solutions. Education: Bachelor in Engineering Science (First Class Honours), NUS PhD in Materials Science and Engineering, Georgia Institute of Technology Postdoctoral Research, Querrey Simpson Institute for Bioelectronics, Northwestern University Research Interests: Wireless bioelectronics for clinical health monitoring Energy harvesting via nanogenerators Soft skin-electronics interfaces using metastructures Programmable materials for adaptive systems Advanced manufacturing techniques for wearable devices Key Achievements: Over 50 publications and 5 patents Recipient of TechConnect 2018 Innovation Award and 56th R&D 100 Award Developed wireless implantable sensors for tissue monitoring and bioresorbable medical devices Teaching: MLE5220: Finite Element Method in Materials MLE5238: Bioelectronics Laboratory: His LISHA lab pioneers innovations in self-powered systems, wearable health monitoring, and biohybrid robots. Current projects include metamaterial-based sensors and sustainable energy conversion materials.

Keyvan Hashtrudi-Zaadمشاهده پروفایل

استاد

• Haptics
• Telerobotics
• Tele-rehabilitation
• +۵ مورد دیگر

Keyvan Hashtrudi-Zaad is a Professor in the Department of Electrical and Computer Engineering at Queen's University, affiliated with the Smith School of Engineering and the Ingenuity Labs Research Institute. His expertise spans robotics and control systems, with a focus on haptics, telerobotics, tele-rehabilitation, autonomous vehicles, and medical robotics. He holds the email addresses keyvan.hashtrudi-zaad@queensu.ca and khz@queensu.ca, and his office is located in Walter Light Hall, Room 427. Research Interests: His research emphasizes human-robot interaction, haptic interfaces, autonomous systems, and mechatronics. Key areas include kinesthetic haptics, collaborative teleoperation systems, energy storage systems for electric vehicles, and medical robotics applications such as needle deflection estimation and rehabilitation robotics. His work bridges theoretical control systems with practical applications in healthcare and autonomous technologies. Publications: His recent work addresses challenges in haptic system stability, energy-efficient inverters for electric vehicles, and teleoperation networks. Notable projects include a cable-driven parallel robot for stroke rehabilitation and a study comparing DC/BLDC actuators for haptic feedback. His research often integrates sensor fusion, nonlinear control, and dynamic modeling to solve real-world problems. Awards and Recognition: While specific awards are not listed, his extensive publication record and leadership in interdisciplinary robotics initiatives highlight his contributions to the field. He is part of the Interactive Robotics and Intelligent Systems (IRIS) Laboratory, advancing innovations in medical robotics and autonomous systems. Grants and Collaborations: His work likely involves collaborations across engineering and medical disciplines, supported by grants focused on robotics, control systems, and healthcare technologies. The IRIS Lab serves as a hub for developing cutting-edge solutions in haptic training systems and assistive robotics.

Chris Leeمشاهده پروفایل

استاد

• Transportation Engineering
• Traffic Safety
• Driver Behavior Analysis
• +۵ مورد دیگر

Professor Chris Lee is a faculty member in the Department of Transportation Science and Engineering at the University of Windsor's Faculty of Engineering. His research focuses on advancing transportation safety through the analysis of driver behavior, traffic flow dynamics, and the integration of emerging technologies like autonomous vehicles and machine learning. Key areas include collision risk prediction, driver vigilance assessment, and the development of advanced car-following models. He has contributed to initiatives such as the Transportation Science and Engineering scholarship program, supporting student research in innovative technologies like driving simulators for lane change behavior studies. His work bridges engineering and human factors, addressing challenges such as driver response to autonomous systems, heavy vehicle traffic management, and cross-cultural automotive design. Lee's interdisciplinary approach leverages data analytics, physiological signals, and machine learning to solve real-world transportation problems. His research has implications for policy-making, infrastructure design, and vehicle safety standards. Lee has collaborated extensively on projects analyzing crash precursors, variable speed limits, and the impact of ITS (Intelligent Transportation Systems) on safety. His publications span over two decades, demonstrating a commitment to both academic rigor and practical applications in transportation engineering. Notable contributions include refining car-following models, studying driver aggression, and evaluating the effectiveness of traffic management strategies.

Yuebing Zhengمشاهده پروفایل

استاد

• Nanophotonics
• Optical Nanotechnologies
• Advanced Materials Science
• +۷ مورد دیگر

Yuebing Zheng is a Professor of Mechanical Engineering & Materials Science and Engineering at the University of Texas at Austin, holding the Cullen Trust for Higher Education Endowed Professorship. He leads a research group innovating optical nanotechnologies for applications in health, energy, and manufacturing. His work focuses on light-matter interactions, optically active materials, and interdisciplinary training. Key roles include Graduate Advisor for the Materials Science Program and past leadership as Associate/Assistant Professor since 2013. Education: PhD in Engineering Science and Mechanics (2010), Penn State University Postdoctoral Researcher (2010-2013), UCLA (Chemistry and Biochemistry) MSc in Physics (2003), National University of Singapore BSc in Physics (2001), Nankai University Research Interests: Optical manipulation technologies (e.g., optothermal tweezers) Nanophotonics and metamaterials Machine learning for materials discovery Biomedical applications (e.g., cell analysis, chiral sensing) Clean energy systems Recent Article Trends: Focus on AI-driven materials design, optothermal microrobotics, and advanced optical systems for energy and biomedical applications. Key innovations include photonic batteries, graphene moiré systems, and steerable active particle swarms. Awards: 2025 SPIE Fellow 2024 Optica Fellow 2017 NIH New Innovator Award 2014 Beckman Young Investigator Multiple best paper awards (2019–2023) Advising & Grants: Supervised over 20 PhD students/postdocs. Active grants from NIH, NSF, ONR, NASA, and industry partnerships. Current lab focuses on optical manipulation, metamaterials, and AI-integrated nanotechnology. Labs/Teams: Director of the Zheng Research Group, affiliated with the Texas Materials Institute. Collaborates on projects merging nanoscience with machine learning and biomedical engineering.

Eric Frewمشاهده پروفایل

استاد

• Autonomous Systems
• Robotics
• Unmanned Aircraft Systems
• +۳ مورد دیگر

Eric Frew is a Professor in the Department of Aerospace Engineering Sciences at the University of Colorado Boulder. He holds leadership roles including Director of the Autonomous Systems Interdisciplinary Research Theme (ASIRT) and former Director of the Research and Engineering Center for Unmanned Vehicles (RECUV). His research focuses on autonomous systems, heterogeneous unmanned aircraft systems, and optimal distributed sensing. He earned his PhD from Stanford University in 2003, and has been a faculty member at CU Boulder since 2004. Education: PhD, Aeronautics and Astronautics, Stanford University, 2003 MS, Aeronautics and Astronautics, Stanford University, 1996 BS, Mechanical Engineering, Cornell University, 1995 Research Interests: Networked unmanned systems Optimal distributed sensing Controlled mobility in sensor networks Miniature self-deploying systems Guidance and control of unmanned aircraft in complex atmospheric phenomena Notable Awards: Outstanding Mentor Award (2023) AIAA Associate Fellow (2013) NSF CAREER Award (2009) Grants and Labs: Leads the Center for Autonomous Air Mobility and Sensing (CAAMS), and has conducted field campaigns such as TORUS (Targeted Observation by Radars and UAS of Supercells). His work integrates theoretical research with practical deployment of autonomous systems for environmental monitoring and severe weather studies. Labs/Teams: Active in CAAMS and RECUV, collaborating with industry/government on pre-competitive research in autonomous air mobility and sensing.

Gareth Pierceمشاهده پروفایل

استاد

• Robotics
• Non-Destructive Testing & Evaluation (NDT&E)
• Ultrasonics
• +۷ مورد دیگر

Professor Gareth Pierce is a leading academic at the University of Strathclyde, serving as Co-Director of the Centre for Ultrasonic Engineering and Academic Director of the UK Research Centre in Non-Destructive Evaluation (RCNDE). He specializes in robotics, autonomous systems, and non-destructive evaluation (NDT&E), with a focus on structural health monitoring (SHM) and advanced manufacturing. His work integrates robotics, AI, and ultrasonics to address challenges in aerospace, energy, and healthcare sectors. He holds a Spirit Aerosystems/Royal Academy of Engineering Research Chair and leads the £50M SEARCH (Sensor Enabled Automation, Robotics & Control Hub), which spans manufacturing and asset management applications. Education: BSc (Hons) in Pure and Applied Physics from the University of Manchester (1989), PhD in Fibre-Optic Interferometers for Laser-Generated Ultrasound from UMIST (1993). Additional qualifications include City & Guilds certifications in electrical installations and a PGDip in Psychological Wellbeing. Research Priorities Autonomous robotic inspection for manufacturing and asset management Integration of AI/machine learning with NDT&E systems In-process inspection for additive manufacturing and welding Ultrasonic and guided wave technologies for defect detection Key Achievements 2023 Anne Birt Award for NDT innovation Leadership roles in SRPe Robotics & UK HVM Catapult initiatives Over 270 research outputs, 86 projects, and a £50M research portfolio Teaching Course organiser for EE312 (Instrumentation & Microcontrollers) and contributes to advanced systems engineering education. Supervises student projects across engineering disciplines. Labs & Collaborations SEARCH Hub operates from Royal College R2.41 (manufacturing applications) and Technology Innovation Centre TIC 7.14 (asset management). Collaborates with global industry partners like Spirit Aerosystems and Högskolan Väst (Sweden).

Gustav Henterمشاهده پروفایل

استادیار

• Deep Generative Models
• Speech Synthesis
• 3D Character Animation
• +۳ مورد دیگر

Gustav Henter is an Assistant Professor in Intelligent Systems at KTH Royal Institute of Technology, specializing in Machine Learning. He is affiliated with the Division of Speech, Music and Hearing (TMH) within the School of Electrical Engineering and Computer Science. His research focuses on deep generative models for applications like speech synthesis, 3D character animation, and human-computer interaction. He holds a Docent degree from KTH and has held post-doctoral positions at the University of Edinburgh and the National Institute of Informatics in Tokyo. Education: PhD in Electrical Engineering (KTH, 2013), MSc in Engineering Physics (KTH, 2007). He supervises doctoral students in areas like gesture synthesis and multimodal interaction. His work is supported by grants from the Wallenberg AI, Autonomous Systems, and Software Program (WASP) and South Korea's MOTIE. He co-founded Motorica AB to commercialize motion synthesis research. Awards include Best Paper Awards at ICMI 2020 and IVA 2020, and recognition for student theses. His research spans generative AI, perceptual evaluation, and robust statistical models. He organizes the GENEA Challenge and Workshop series for gesture generation benchmarking.

Eric TOTELمشاهده پروفایل

استاد

• Network Security
• Intrusion Detection Systems
• Data Confidentiality
• +۳ مورد دیگر

Eric TOTEL is a Professor at Telecom SudParis, specializing in cybersecurity and network security. His research focuses on intrusion detection systems, graph-based anomaly detection, machine learning applications in security, and data confidentiality in distributed systems. He has contributed to projects such as DAMS (DDoS mitigation using deep reinforcement learning), Sec2Graph (novelty detection on graph-structured data), and DAEMON (dynamic autoencoder-based anomaly detection). His work emphasizes scalable solutions for multi-step attack detection and privacy-preserving infrastructure for encrypted DNS logs. Key contributions include developing correlation engines for distributed systems, formalizing invariant-based attack detection in web applications, and exploring static analysis for information flow control. He has authored over 50 peer-reviewed publications and served on program committees for conferences like RAID, CRiSIS, and EuroS&P. His HDR (2012) formalized error-detection techniques applied to intrusion detection. Advising and grants: He collaborates on projects funded by French national research agencies and has mentored students in cybersecurity, AI for defense (CAID conferences), and cloud infrastructure security. His research often bridges theoretical models and practical implementations, with tools like STARLORD for 3D graph visualization of security data.