جست‌وجوی استاد و پژوهشگر

Andrew Kwongمشاهده پروفایل

استادیار

• Computer Security
• Applied Cryptography
• Side-Channel Attacks
• +۴ مورد دیگر

Andrew Kwong is an Assistant Professor at the University of North Carolina at Chapel Hill in the Department of Computer Science. His research focuses on computer security and applied cryptography, particularly side-channel attacks and defenses, including Rowhammer, Spectre, and cache timing vulnerabilities. He teaches courses such as Hardware Security and Side-Channels and Research Topics in Computer Security , covering topics like transient execution attacks, speculative probing, and cryptographic implementation flaws. Department of Computer Science, UNC Chapel Hill Assistant Professor Teaching COMP 790-184 (Hardware Security) and COMP 790-185 (Computer Security Research) His research involves cutting-edge work on hardware vulnerabilities, including Rowhammer-based key recovery in post-quantum cryptography, cache eviction side-channels, and speculative execution attacks. His publications appear at top venues like IEEE S&P, CCS, and USENIX Security. He received a Best Paper Award Honorable Mention at CCS 2022 for his work on FrodoKEM exploitation. Key trends in his publications include leveraging hardware flaws for data leakage, cryptographic protocol breakdowns, and combining transient execution with memory corruption attacks. His work has implications for hardware design security and cryptographic implementation practices. Best Paper Award Honorable Mention, CCS 2022 Contact: andrew@cs.unc.edu

Frank E. Talkeمشاهده پروفایل

استاد

• Medical Device Technology
• Information Storage
• Tribology
• +۳ مورد دیگر

Frank E. Talke is the CMRR Endowed Chair Professor in the Department of Mechanical and Aerospace Engineering at UC San Diego. His research focuses on medical device technology and information storage systems. He has contributed to advancements in hard disk drive tribology, thermal flying height control, and biomedical innovations like intraocular pressure sensors and 3D-printed endoscopes. Talke holds over 350 publications and 11 patents, with honors including the ASME Medal, Tribology Gold Medal, and membership in the National Academy of Engineering. Education: Diplom-Ingenieur (1965, University of Stuttgart), M.S. and Ph.D. in Mechanical Engineering (1966, 1968, UC Berkeley), honorary doctorate from Technical University of Munich (2005). Research interests span interdisciplinary fields combining mechanical engineering, materials science, and precision instrumentation. Current projects include medical device development (e.g., biofilm-resistant catheters, detachable bronchoscopes) and information storage tribology. His work emphasizes translational applications in both engineering and healthcare sectors. Key Awards: ASME Medal (2008), Tribology Gold Medal (2010), Honorary ASME Membership (2018). Grants and Funding: Extensive industry and academic collaborations in disk drive technology and biomedical engineering. Labs/Teams: Leads the Center for Memory and Recording Research (CMRR), fostering interdisciplinary research in data storage and medical devices.

Roy Sterrittمشاهده پروفایل

مدرس

• Autonomic Computing
• Robotics
• Machine Learning
• +۵ مورد دیگر

Roy Sterritt is a Lecturer in Informatics at the School of Computing, Ulster University. His research focuses on autonomic computing, robotics, machine learning, and cybersecurity. He has contributed extensively to decentralized systems and fault management in autonomous environments. Research Interests: Roy’s work spans autonomic computing, robotics, and AI, with applications in cloud systems, space exploration, and drone fleets. He emphasizes self-adaptation, fault tolerance, and security protocols. Scientific Awards: Highly Ranked Scholar in Autonomic Computing (2024) Multiple Best Paper Awards (2016–2023) Recent Trends: His recent publications highlight autonomic solutions in cloud security, robot swarms, and space systems, leveraging machine learning and adaptive communication protocols. Projects & Collaborations: Roy has led projects like SPAAACE-Ware and DEL CAST AWARD, focusing on autonomic analytics and apoptotic computing. He organizes international conferences on autonomous systems and collaborates globally.

Mark Heinrichمشاهده پروفایل

دانشیار

• Parallel Computer Architecture
• Heterogeneous Architectures
• Active Memory and I/O Systems
• +۴ مورد دیگر

Mark Heinrich is an Associate Professor in the Department of Computer Science at the University of Central Florida (UCF), where he also serves as Undergraduate Coordinator for CS and IT, and Senior Design Coordinator. He previously held roles at Cornell University and has industry experience co-founding companies like Phanfare and Flashbase. His research focuses on parallel computer architecture, heterogeneous systems, cache coherence protocols, and multiprocessor simulation. Heinrich holds a Ph.D. in Electrical Engineering from Stanford University (1998) under John Hennessy, and a B.S. in Electrical Engineering and Computer Science from Duke University (1991). Research Interests His work spans parallel architectures, active memory systems, scalable cache coherence protocols, and hardware/software co-design. Recent efforts include innovations in persistent memory technologies and multiprocessor simulation methodologies. Teaching In Spring 2020, he taught CS Senior Design I and II courses (COP 4934/4935), with office hours focused on senior design and undergraduate coordination. Professional Background Associate Professor at UCF since 2003 Past roles: Director of UCF's School of Computer Science (2005), Associate Director of EECS (2005-2007) Co-founder of the Cornell Computer Systems Laboratory Contributed to the FLASH multiprocessor architecture and its simulation tools Labs & Projects He has been involved in projects like Active Memory Clusters and architectural support for multiprocessor systems. His work often bridges theoretical computer architecture with practical hardware implementations.

• Mechanical Engineering
• Metrology
• Biomedical Engineering
• +۵ مورد دیگر

Roman Szewczyk is a Professor at the Institute of Metrology and Biomedical Engineering within the Faculty of Mechatronics at Warsaw University of Technology (Politechnika Warszawska). He also maintains an affiliation with the Łukasiewicz Research Network – Industrial Research Institute for Automation and Measurements PIAP. His academic career spans over two decades since earning his doctorate in 2003. Professor Szewczyk's research interests are highly interdisciplinary, focusing on the intersection of mechanical engineering, materials science, and biomedical applications. His primary expertise lies in magnetic sensors, metrology, and the development of measurement systems. He has made significant contributions to understanding magnetostrictive effects, magnetic permeability in electrical steels, and the application of finite element methods for sensor development. His work bridges theoretical physics with practical engineering applications, particularly in the fields of automation and biomedical instrumentation. An analysis of his recent publications reveals a strong focus on precision measurement systems, magnetic sensor development, and materials characterization. His work spans from fundamental physics of magnetoelastic effects to practical applications in robotics, biomedical devices, and environmental sustainability. The consistent publication output across multiple domains demonstrates his ability to integrate knowledge from diverse fields to solve complex engineering problems. With an impressive record of 342 publications and an h-index of 18 (Scopus) and 17 (Web of Science), Professor Szewczyk has established himself as a significant contributor to his fields of expertise. His work has practical applications across various industries including medical technology, power systems, and precision manufacturing. Professor Szewczyk has supervised 120 promoted theses, indicating his substantial contribution to academic mentoring and the development of future engineers. His involvement in 4 research projects demonstrates his ability to secure funding and lead research initiatives. While specific grant details aren't provided in the available information, his publication record suggests successful acquisition of research funding to support his extensive work. His laboratory work appears to focus on precision measurement systems, particularly those involving magnetic phenomena. The research group likely maintains facilities for materials testing, sensor development, and computational modeling, given the nature of his publications. The connection to the Institute of Metrology and Biomedical Engineering suggests strong capabilities in precision instrumentation and biomedical applications of engineering principles.

• Quantum Computing
• MRAM
• Near-field Microscopy
• +۳ مورد دیگر

David W. Abraham is a senior researcher at IBM Research - Yorktown Heights specializing in quantum computing and advanced materials. His work spans multiple decades with significant contributions to near-field microscopy, thermal imaging, MRAM technology, and most recently quantum processor development. His primary research interests focus on quantum computing hardware , particularly superconducting bump bonds, through-silicon vias (TSVs), and multi-level wiring systems critical for building scalable quantum processors like IBM's 127-qubit Eagle device. Earlier work included pioneering research in magnetic force microscopy (achieving 25 nm resolution) and thermal imaging applications for disk drives. Analysis of his publication history reveals consistent innovation in quantum hardware engineering, with recent work (2021-2024) concentrated on solving practical integration challenges for quantum processors. His research bridges fundamental physics with practical engineering solutions for next-generation computing systems. Dr. Abraham collaborates extensively with IBM Quantum leadership including Jay Gambetta (VP of Quantum), Matthias Steffen (IBM Fellow), and Oliver Dial (CTO, IBM Quantum), reflecting his integral role in IBM's quantum computing initiative. His laboratory work focuses on quantum processor fabrication and characterization, with particular emphasis on developing reliable interconnect technologies and mitigating decoherence sources in superconducting qubit systems. Current projects appear directed toward scaling quantum processors beyond current device limitations through novel packaging and integration approaches.

Lennart Blankenمشاهده پروفایل

استادیار

• Feedforward Control
• Learning Control
• Repetitive Control
• +۴ مورد دیگر

Lennart Blanken is a part-time Assistant Professor at the Mechanical Engineering Department of Eindhoven University of Technology (TU/e) and a researcher at Sioux Technologies (Mechatronics department) since 2019. His work bridges academia and industry, focusing on semiconductor and printing technologies. Education: MSc in Mechanical Engineering (cum laude) from TU/e, 2015 PhD in Mechanical Engineering from TU/e, 2019 His research specializes in advanced feedforward control, learning control, repetitive control, and system identification for mechatronic systems. Recent publications highlight frequency-domain methods, multirate systems, and kernel-based learning approaches to improve tracking performance in industrial applications. Advising & Ancillary Roles: Trainer at High Tech Institute. Grants & Collaborations: Funded by NWO (VIDI program 15698), ECSEL Joint Undertaking (IMOCO4.E), Horizon 2020, and JSPS-NWO programs (JPJSBP220234403, 040.040.060).

• Feedforward Control
• Learning Control
• Repetitive Control
• +۸ مورد دیگر

Lennart LG Blanken is a part-time Assistant Professor in the Control Systems Technology group at the Mechanical Engineering Department of Eindhoven University of Technology (TU/e). He also works at Sioux Technologies in the Mechatronics department since 2019, focusing on applications in the semiconductor and printing industries. His academic background includes a cum laude MSc in Mechanical Engineering (2015) and a PhD (2019) from TU/e, both centered on control systems. Education : MSc (2015) and PhD (2019) in Mechanical Engineering from TU/e. Research Interests : His work spans advanced feedforward control , learning control , repetitive control , and system identification , with applications in mechatronic systems. Key topics include frequency domain analysis , noncausal systems , and nyquist frequency . Article Trends : Recent publications (2024-2025) emphasize frequency-domain methods in multirate systems, kernel-based learning for parameter-varying control, and finite-time iterative learning control. Applications focus on hard disk drives, wafer stages, and industrial printers. Collaborations : He collaborates with institutions like Philips Innovation Services (MSc project) and Canon Production Printing (PhD project), alongside ongoing industry partnerships through Sioux Technologies.

Maciej Norasمشاهده پروفایل

دانشیار

• Electrical Engineering
• Electrostatics
• Power Engineering
• +۴ مورد دیگر

Maciej Noras is an Associate Professor in the Engineering Technology and Construction Management department at the University of North Carolina at Charlotte . His academic background includes a Ph.D. in Engineering Science from Southern Illinois University and an M.S. in Electrical Engineering from UNC Charlotte and Wroclaw University of Technology. Ph.D. in Engineering Science, Southern Illinois University, Carbondale, IL (2000) M.S. in Electrical Engineering, University of North Carolina at Charlotte and Wroclaw University of Technology, Poland (1994) Noras's research focuses on electrostatics , power engineering , and sensor design , with applications in semiconductor manufacturing , actuator technology , and non-contact charge measurement . He has explored Electrostatic voltmeter design for semiconductor wafers Ionizer monitoring in ESD-sensitive environments Charge feedback systems for piezoelectric actuators Surface potential measurement techniques His recent publications highlight advancements in electrostatic sensor technology , actuator control systems , and charge accumulation analysis across semiconductors and data storage devices. Key trends include Development of high-resolution electrostatic voltmeters Optimization of ionizer systems in manufacturing Integration of piezo-driven sensors for precision applications Charge feedback amplifiers for actuator control No scientific awards or honors are mentioned in the provided data. He has submitted multiple research grants , including DOE Grant (2010-2012) for a Net-Zero Energy Building Operator Training Program as Co-PI Unfunded UNC Charlotte Faculty Grant (2008) on Doherty Amplifier feasibility Pending Army Research Laboratories proposal (2008) on geophysical anomaly detection Multiple declined NSF grants (2009-2010) for power engineering and pharmaceutical blend research

• Advanced Feedforward Control
• Learning Control
• Repetitive Control
• +۴ مورد دیگر

Lennart L.G. Blanken is a part-time Assistant Professor in the Control Systems Technology group at the Mechanical Engineering Department of Eindhoven University of Technology (TU/e). He also works at Sioux Technologies in the Mechatronics department since 2019, focusing on projects in the semiconductor and printing industries. His research emphasizes advanced control strategies including feedforward control, learning control, repetitive control, and system identification, with applications in mechatronic systems. Academically, he earned his MSc (cum laude) in Mechanical Engineering from TU/e in 2015 and his PhD in 2019, both under the supervision of Oomen, with a thesis on learning and repetitive control for complex systems applied to large format printers. His work has been published in journals like Meathctronics and Mechanical Systems and Signal Processing , focusing on frequency-domain methods, iterative learning control, and multirate systems. Key collaborations include projects with Philips Innovation Services, Océ Technologies (Canon Production Printing), and international researchers. His contributions span theoretical control development and industrial applications, with a focus on enhancing system performance through innovative control methodologies.

Saeid Bashashمشاهده پروفایل

دانشیار

• Control Systems
• Energy Management
• Mechatronics
• +۴ مورد دیگر

Dr. Saeid Bashash is an Associate Professor in the Department of Mechanical Engineering at San José State University's Charles Davidson College of Engineering. He holds a Ph.D. in Mechanical Engineering from Clemson University (2008), with previous positions including Assistant Professor at SJSU (2015-2021), Senior Engineer at HGST (2013-2015), and postdoctoral fellowships at Pennsylvania State University and University of Michigan. His research focuses on the modeling, optimization, and control of advanced dynamical systems with applications in: Precision motion control at micro/nano scales Energy management in buildings, electric vehicles, and smart grids Battery systems modeling and health-conscious charging Mechatronics and vibration control systems Publication analysis reveals strong emphasis on control theory applications in energy systems (67% of recent works), mechatronics (20%), and battery technology (13%), with evolving focus toward smart grid optimization and data-driven methods since 2017.

• Wireless Sensor Networks
• Computer Engineering
• IoT
• +۷ مورد دیگر

Dr. Uroš Pešović serves as an Associate Professor in the Department of Computer and Software Engineering at the Faculty of Technical Sciences in Čačak, University of Kragujevac, Serbia. With over 15 years of academic service, he has progressed from teaching associate (2007-2018) to assistant professor (2018-2023) and currently holds the position of associate professor for Computer Engineering (2023-2028). Elementary school "Milica Pavlović" Čačak (1989-1997), average grade 5.00 - holder of Vuk's diploma Secondary Technical School Čačak (1997-2001), automation electrical technician, average grade 5.00 - holder of Vuk's diploma Technical Faculty, Čačak, University of Kragujevac (2001-2006), B.Sc. electrical engineer for computer technology, average grade 9.03 Faculty of Electrical Engineering, Computer Science and Informatics, University of Maribor, Slovenia (2007-2010), Master of Electrical Engineering, Major in Telecommunications, average grade 9.75 Faculty of Electrical Engineering, Computing and Informatics, University of Maribor, Slovenia (2010-2016), doctor of technical sciences, doctoral dissertation "Error probability model for IEEE 802.15.4 wireless transmission with co-channel interference and background noise" Dr. Pešović's research spans wireless sensor networks, IoT applications, computer architecture, and reliability engineering. His work demonstrates a strong focus on practical implementations of theoretical models, particularly in IEEE 802.15.4 wireless communication protocols and their applications in precision agriculture, industrial monitoring, and network communication systems. His expertise bridges hardware and software design, with recent work emphasizing machine learning applications for predictive maintenance and anomaly detection in storage systems. Analysis of his recent publications reveals a clear evolution from foundational wireless communication research toward more applied work in precision agriculture, industrial IoT, and educational technology. His current research emphasizes practical problem-solving in agricultural technology using LoRa and other wireless technologies, predictive maintenance of storage systems using machine learning, and innovative approaches to computer engineering education. Dr. Pešović teaches across all academic levels, including undergraduate courses in Computer Architecture, Organization of Computer Systems, Microcontroller Systems, and Computer Networks, as well as graduate courses in Hardware-Software Design, Intelligent Sensors, and Industrial Communication Networks. At the doctoral level, he teaches courses on integrated hardware-software design, disk performance, and telecommunication systems modeling.

Raymond de Callafonمشاهده پروفایل

استاد

• System Identification
• Control Theory
• Adaptive Control
• +۱۳ مورد دیگر

Raymond de Callafon is a Professor in the Department of Mechanical and Aerospace Engineering (MAE) at the University of California, San Diego (UCSD). He is a key faculty member in the Dynamic Systems & Control (DS&C) group, where he conducts research and teaches in system identification, adaptive control, and modeling of mechatronic systems. He directs the System Identification and Control Laboratory (SICL) and manages the CMRR Servo Laboratory, both at UCSD. His work bridges theoretical control with practical applications in data storage, aerospace, and vibration control systems. M.Sc., Mechanical Engineering, Delft University of Technology, 1992 Ph.D., Mechanical Engineering, Delft University of Technology, 1998 Raymond de Callafon's research centers on experiment-based modeling, control-relevant system identification, and recursive/adaptive control. His interests extend to nonlinear and linear parameter varying (LPV) systems, with applications in hard disk drives, tape storage systems, active noise and vibration control, and aeroelastic flutter prediction. He has developed modeling techniques applied to structural damage detection and controller tuning for high-precision systems. His recent publications reflect a strong trend in closed-loop system identification, Hammerstein models, adaptive disturbance rejection, and high-precision motion control in data storage devices. The articles span both theoretical advances and experimental validations, often involving dual-stage actuators and real-time control implementations. Co-authored book: Realtime Controller Tuning for Periodic Disturbance Rejection Developed MATLAB toolboxes: LTSfit, CLOSID, FREQID NASA-funded research on flutter control and aeroservoelastic systems Active collaboration with CMRR and industry partners in data storage Raymond de Callafon has advised multiple graduate students and contributed to significant research projects involving adaptive control, robotic systems, and coordinated ocean sensing networks. His teaching includes both graduate and undergraduate courses in system identification, control theory, and laboratory-based engineering education. He has also established the Undergraduate Control Laboratory (UGCL) and taught in the COSMOS summer program on kinetic sculptures. His laboratories, SICL and CMRR Servo Lab, are equipped with advanced facilities for sound and vibration control, real-time prototyping, and high-precision motion experiments, supporting both academic and industrial research in control engineering.

Anusha Natarajarathinamمشاهده پروفایل

دانشیار

• Physics
• Magnetism
• Pre-Med Education
• +۳ مورد دیگر

Anusha Natarajarathinam is an Associate Professor at the College of Health & Wellness, Northwestern Health Sciences University. She holds a PhD in Electrical Engineering & Materials Science from The University of Alabama, along with additional degrees in Electrical Engineering. Her research focuses on applying physics principles to pre-health education, particularly in MCAT physics preparation and modern physics for pre-medical/dental students. She also investigates magnetic materials and their applications in healthcare technologies. Dr. Natarajarathinam has published extensively on magnetic materials, including studies on magnetic tunnel junctions, spintronics, and nanomaterials. Her work often addresses challenges in data storage and spin-based memory technologies. She serves as an advisor for the Minority Association of Pre-medical Students (MAPS) club and actively participates in institutional committees, including the Faculty Senate and Diversity, Equity, and Inclusion initiatives. Education: PhD, MS in Electrical Engineering & Materials Science, University of Alabama M.S. in Electrical & Computer Engineering, University of Alabama B.E. in Electrical and Electronics Engineering, Anna University Her teaching philosophy emphasizes applied learning and hybrid pedagogical approaches, as reflected in her courses like General Physics and Physics for Pre-Health Professions. In 2019–2020, she was recognized as the Teacher of the Year for Undergraduate and Post-Baccalaureate programs. Dr. Natarajarathinam’s research bridges fundamental physics with healthcare education and advanced materials science, contributing to both academic and applied domains.

Tom Oomenمشاهده پروفایل

استاد

• Control Systems
• System Identification
• Machine Learning
• +۷ مورد دیگر

Tom Oomen is a full professor in the Department of Mechanical Engineering at Eindhoven University of Technology. He specializes in control systems, system identification, and mechatronics, with applications in precision engineering, semiconductor technology, and healthcare. His research focuses on data-driven control strategies, integrating machine learning and artificial intelligence to enhance system performance. He has held academic positions at KTH Royal Institute of Technology, The University of Newcastle, and Delft University of Technology. Recipient of the 7th Grand Nagamori Award and NWO Veni/Vidi grants. Editor roles: Senior Editor of IEEE Control Systems Letters and Co-Editor-in-Chief of IFAC Mechatronics. Research interests include advanced motion control, iterative learning control, and fault detection. He teaches courses like Advanced Motion Control and organizes post-academic courses through the Mechatronics Academy. Collaborates with industries in semiconductor equipment, printing, space technology, and healthcare. Recent articles explore topics such as random learning in ILC, nonlinear control for ventilators, and gravitational wave detection systems. Advises PhD students including Max van Meer, Max van Haren, and Koen Classens.