جست‌وجوی استاد و پژوهشگر

Prabha Sundaravadivelمشاهده پروفایل

استادیار

• Internet of Things (IoT)
• Smart Healthcare
• IoT Architectures
• +۴ مورد دیگر

Dr. Prabha Sundaravadivel is an Assistant Professor in the Department of Electrical Engineering at the University of Texas at Tyler (UT Tyler). She joined UT Tyler in Fall 2018 and holds a Ph.D. in Computer Science and Engineering from the University of North Texas (2018), an M.Tech in VLSI Design from Vellore Institute of Technology (2015), and a B.Tech in Electronics and Communication from SRM Institute of Science and Technology (2011). Her research focuses on IoT-driven smart healthcare systems, low-power VLSI design, and embedded systems for IoT applications. As Director of the Computer Engineering Research Laboratory (CERL), her team explores smart healthcare and smart cities initiatives, leveraging IoT technologies to enhance quality of life. Current projects include UAV-based agricultural monitoring, bio-inspired robotics, and edge-intelligent wearables for health monitoring. Dr. Sundaravadivel is an IEEE member and Faculty Advisor for the IoT Student Club. Her work emphasizes interdisciplinary innovation, integrating machine learning, hardware design, and environmental intelligence into practical solutions. Recent research highlights include autonomous UAV navigation systems, low-power memristor emulators, and FPGA-based intrusion detection for aerial robots. Her teaching philosophy incorporates project-based learning (PBL) to integrate sustainability and entrepreneurial skills into engineering education. Notable educational initiatives include video creation for developing entrepreneurial mindsets and blending entrepreneurship into senior-level courses.

Stavrou Michalisمشاهده پروفایل

پژوهشگر ارشد

• Nonlinear Optics
• Photonics
• 2D Nanomaterials
• +۳ مورد دیگر

Dr. Stavrou Michalis serves as a Research Fellow at the Institute of Electronic Structure and Laser (IESL), part of the Foundation for Research and Technology - Hellas (FORTH) in Greece. His work centers on advanced photonic materials research within FORTH's multidisciplinary scientific ecosystem, focusing on next-generation optical technologies. His research expertise spans Nonlinear Optics and Photonics , with pioneering investigations into 2D Nanomaterials including MXenes, hematene, magnetene, and transition metal dichalcogenides. He examines ultrafast carrier dynamics, saturable absorption, and optical limiting phenomena across UV-NIR spectra, enabling breakthroughs in ultrafast laser systems and multiphoton lithography . His methodology combines green synthesis of mineral-derived nanomaterials with precise femtosecond laser characterization to optimize material responses for photonic applications. Analysis of his 15 most recent publications (2023-2026) reveals three dominant research thrusts: (1) Discovery of exceptional nonlinear optical properties in non-van der Waals 2D materials like hematene exfoliated from iron ores; (2) Development of novel carbazole and indane-dione photoinitiators for high-resolution 3D microfabrication; and (3) Fundamental studies of carrier dynamics in MXene nanosheets for ultrafast photonic switching. His work consistently demonstrates broadband (450-2300 nm) optical limiting performance exceeding conventional materials, with recent focus on Ta 4 C 3 MXenes and magnetene nanoplatelets.

Patricia Navaمشاهده پروفایل

استاد

• Artificial Intelligence
• Deep Learning
• Machine Learning
• +۱۰ مورد دیگر

Patricia Nava is a Professor in the Department of Electrical and Computer Engineering at the University of Texas at El Paso (UTEP), with affiliations in Computational Science. Her work bridges theoretical and applied domains across Artificial Intelligence, Deep Learning, Digital Design, and Computer Architecture. Primary Research Areas: AI, Deep Learning, Computer Architecture, STEM Education Key Collaborations: UTEP Distributed Computing Lab, H-PIPE (High-Performance Computing Pipeline) project Her research explores Deep Learning Networks through analogies to biological systems, focusing on their implementation via programmable hardware. She has pioneered educational strategies in engineering pedagogy, particularly for Signals and Systems instruction, while maintaining a strong technical focus on neural network algorithms and hardware acceleration. Recent publications highlight her dual emphasis on STEM student success (e.g., graduate transition pathways) and technical innovations such as GPU clusters , quantized neural networks , and multi-core architectures . Her work spans biomedical applications like asthma classification and respiratory impedance modeling, demonstrating interdisciplinary breadth. Featured Scientific Support: $1M grant to increase graduate engineering participation She contributes to distributed computing infrastructure through projects like the Virgo 3-GPU upgrade and has developed fuzzy logic systems for sleep-stage and asthma classification. Her educational initiatives focus on transfer student integration and diversity in engineering.

• Ultrafast Optics
• Laser Physics
• Nonlinear Optics
• +۵ مورد دیگر

Prof. Guenter Steinmeyer is a leading academic in ultrafast optics and nonlinear optics, serving as Department Head of C2 'Solid State Light Sources' at the Max Born Institute in Berlin. He also held a Full Professorship at Humboldt Universität zu Berlin (2017). His research focuses on ultrafast laser physics, femtosecond pulse characterization, carrier-envelope phase stabilization, and optical filamentation. Notable contributions include the patented feed-forward technique for CEP stabilization, now commercially used in lasers. His career includes roles as a Senior Staff Scientist at the Max Born Institute (2002-present), Finland Distinguished Professor (2008-2013), and postdoctoral research at MIT (1995-1997). He earned his PhD in Physics (1995) and Habilitation (2002) from Hannover University. Steinmeyer's research explores cutting-edge topics like rogue wave dynamics in multifilament systems, quantum noise limits in CEP measurements, and plasmonic nanolithography. He holds prestigious fellowships from APS, OSA, and URSI, and has served on editorial boards for Physical Review A and Optics Letters. Current projects investigate nonlinear pulse propagation, acoustic gigawatt laser deflection, and parametric combs with quantum-limited phase noise. His work bridges fundamental physics with technological applications in ultrafast laser systems.

• Information Systems
• Intelligent Agent Systems
• E-Learning
• +۵ مورد دیگر

Dongming Xu is a Professor at Sun Yat-sen University's School of Data and Computer Science, Department of Information Systems, with an extensive publication record spanning over two decades in the field of Information Systems. His scholarly contributions demonstrate expertise in intelligent agent systems, e-learning environments, digital innovation, and knowledge management, with recent work expanding into healthcare informatics, 5G technology, and FPGA design. Xu's research interests focus on the intersection of technology and human behavior, particularly examining how digital systems can enhance learning, financial management, healthcare delivery, and disaster response. His work employs both theoretical frameworks and practical implementations, often utilizing intelligent agents, machine learning techniques, and socio-technical perspectives to address complex information system challenges. Analysis of Xu's 15 most recent publications reveals a strategic evolution in research focus, beginning with foundational work in intelligent agent-supported systems and virtual learning environments, expanding into knowledge management and digital disruption theory, and most recently incorporating advanced technical implementations in wireless communications and hardware design. This progression demonstrates both theoretical depth and practical application across multiple domains. Multiple publications in top-tier Information Systems journals including Information Systems Journal, Journal of Global Information Management, and Decision Support Systems Regular contributions to premier conferences such as PACIS, ICIS, HICSS, and AMCIS Interdisciplinary research connecting computer science, business, healthcare, and social sciences Xu has established productive research collaborations with scholars across multiple institutions, particularly working with Huaiqing Wang, Jun Shen, Tingru Cui, and Geng Sun. His research has received consistent funding support, enabling sustained investigation into evolving information technology challenges. Current work shows increasing emphasis on AI applications in healthcare, advanced communication technologies, and digital platform ecosystems.

Luca Pezzarossaمشاهده پروفایل

دانشیار

• Real-Time Systems
• Digital Microfluidics
• Compiler Optimizations
• +۷ مورد دیگر

Luca Pezzarossa is an Associate Professor in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU). His research focuses on real-time systems, embedded computer systems, digital microfluidics, compiler optimizations, and hardware accelerators. He leads projects such as the Edu4Chip: Joint Education for Advanced Chip Design in Europe initiative and supervises PhD students in areas like compiler optimizations for neural networks and speech enhancement algorithms. His academic journey includes contributions to interdisciplinary fields, combining computer engineering with biomedical applications such as biochip design and PCR optimization. He actively engages in open-source tool development, particularly using the Chisel framework for hardware design education and research. Key research themes include: Real-time systems and time-predictable architectures Compiler-driven optimizations for constrained devices Digital microfluidics for lab-on-a-chip systems Edge computing and TinyML applications Recent publications highlight innovations in microplastic detection on edge devices, dynamic channel pruning for speech enhancement, and parallel execution engines for digital microfluidics. His work aligns with sustainable development goals through environmental applications and energy-efficient technologies. Current projects involve: PhD Supervision: Andrea Cerioli (Compiler Optimizations), Riccardo Miccini (AI-to-Neural Network Mapping), Ehsan Khodadad (Time-predictable Systems) Research Grants: EU-funded Edu4Chip (2023–2025), multiple industry-academia collaborations Labs and teams: Leads the Embedded Systems Engineering group at DTU, focusing on interdisciplinary hardware-software co-design for real-world applications. Active in developing open-source frameworks for education and research.

• Dark Matter Detection
• Particle Physics
• Xenon Detectors
• +۴ مورد دیگر

Joao Manuel Cardoso is an Associate Professor at the University of Coimbra's Department of Physics, affiliated with the Faculty of Sciences and Technology. His research spans dark matter detection (via the XENON and DARWIN collaborations), biomedical engineering instrumentation, and advanced data acquisition systems. He holds leadership roles in LIBPhys's biomedical engineering group and has contributed to groundbreaking experiments like the CREMA collaboration (Nature, 2010; Science, 2013). Education: PhD in Physics (2006), University of Coimbra MSc in Physics (2001), University of Coimbra BSc in Engineering Physics (1996), University of Coimbra Research Interests: Cardoso’s work bridges particle physics and biomedical engineering. In physics, he focuses on dark matter detection using liquid xenon detectors (e.g., XENON1T/nT and DARWIN) and ultra-sensitive spectroscopy. In biomedical engineering, he develops non-invasive hemodynamic monitoring, cochlear implant optimization, and sleep apnea diagnostics via machine learning. His lab also pioneers optical coherence elastography for retinal imaging. Articles: His publications span high-impact journals like Nature, Science, and Physical Review Letters, emphasizing interdisciplinary contributions to particle physics and biomedical engineering. Recent work includes advancements in detector design for dark matter searches and entropy-based analysis for medical imaging. Awards: University Ignite fund for cochlear implant research, multiple grants (FCT, SAICT, etc.), and recognition for interdisciplinary innovation. Grants & Labs: PI of projects on optical coherence elastography and XENON detector scaling. Collaborates with CITEUC and VIBSonCancer initiatives. Teams: Leads LIBPhys’s biomedical strand and co-supervises PhD students in computer science and biomedical engineering.

Alireza David Anisiمشاهده پروفایل

دانشیار

• Autonomous Systems
• Robotics
• Agri-tech
• +۷ مورد دیگر

Alireza David Anisi is an Associate Professor at the Department of Engineering Sciences , University of Agder. With a PhD in Optimization and Systems Theory and an M.Sc. in Engineering Physics, he specializes in autonomous systems and robotics , particularly in agri-tech and harsh environments . His industrial experience spans 15+ years in defense and oil & gas sectors. Academic Background: PhD: Optimization and Systems Theory M.Sc.: Engineering Physics Research Interests include formal verification and learning for autonomous systems, combinatorial optimization for multi-robot task/path planning, computational optimal control for trajectory optimization, and nonlinear observer design. His work bridges academic research with industrial R&D. Selected Publications highlight trends in robotics safety assurance, formal verification methods, and industry-specific applications (defense, oil & gas, agriculture). Recent works focus on runtime verification in ROS 2 and RoboStar technology integration. Patents: Power system optimization (EP18162642.5, 2018) Mechanical grip system (SE1300179, 2013) Sensor arrangement for machine vision (WO2014026711, 2012) Tool changer for explosive environments (WO2012007188, 2011) Industrial robot control method (EP2466404, 2010) Harsh environment mobile robot (WO2011107137, 2010) Anisi contributes to the Robotics and Automation research group, focusing on real-world applications in agriculture, energy, and industrial sectors. He teaches MAS221 Industrial IT and Robotics and emphasizes collaboration between academia and industry.

• Mechanical Engineering
• Materials Science
• Manufacturing Processes
• +۷ مورد دیگر

Dr. hab. Eng. Radosław Maruda is a Professor at the University of Zielona Góra, serving as Director of the Institute of Mechanical Engineering and Chairman of the Council of the Scientific Discipline of Mechanical Engineering. His research focuses on advanced machining techniques, surface engineering, and eco-friendly manufacturing processes. He specializes in material behavior under extreme conditions, with emphasis on surface integrity, tribology, and nanotechnology applications in cutting fluids. Research interests include: non-contact surface measurement methods, tool wear analysis, minimum quantity lubrication (MQCL/MQL), and sustainable machining of difficult-to-cut materials like titanium alloys and stainless steel. His work integrates metrology, thermal analysis, and computational modeling to optimize manufacturing processes. Publications emphasize innovative cooling/lubrication strategies, nanoparticle-enhanced cutting fluids, and energy-efficient machining systems. His contributions address both theoretical and applied aspects of mechanical engineering, particularly in precision machining and surface characterization. No scientific awards are listed in the provided information. Advising/Grants: No student advising or grant information is explicitly mentioned. Lab affiliations include the Institute of Mechanical Engineering's Materials Science and Machining Technology research groups.

Yun-Sheng Chenمشاهده پروفایل

استادیار

• Photoacoustic Imaging
• Nanoparticles
• Biomedical Engineering
• +۵ مورد دیگر

Yun-Sheng Chen is an Assistant Professor at the University of Illinois at Urbana-Champaign, with affiliations in the Department of Electrical and Computer Engineering, Bioengineering, Biomedical and Translational Sciences, Micro and Nanotechnology Laboratory, and the Beckman Institute for Advanced Science and Technology. His research focuses on photoacoustic imaging, nanotechnology, and biomedical engineering, with applications in cancer diagnosis, therapeutic nanomaterials, and wireless power transfer. Chen’s work integrates optical, acoustic, and nanoscale technologies to develop innovative diagnostic and therapeutic tools. Key areas include dual-modal imaging techniques (photoacoustic/ultrasound), plasmonic nanostructures for tumor detection, and mechanochemical nanoparticles for targeted therapy. He also explores reconfigurable metasurfaces for wireless power systems and wearable technology. Recent contributions include advancements in sparsity-constrained photoacoustic imaging, biomimetic membrane-protected contrast agents, and injectable nanoparticles for deep-tissue therapy. His research bridges engineering and medicine, addressing challenges in precision imaging and therapy guidance.

• Computer Science
• Electrical Engineering
• Circuits and Systems
• +۴ مورد دیگر

David Blaauw is the Kensall D. Wise Collegiate Professor of Electrical Engineering and Computer Science (EECS) at the University of Michigan. He has been on the faculty since August 2001. His research focuses on ultra-low-power wireless sensors, near-threshold computing, cognitive computing using analog neural networks, and genomics for precision health. He directs the Michigan Integrated Circuits Lab and has contributed to seminal work in subthreshold circuit design and energy-efficient semiconductor systems. Education: B.S. in Physics and Computer Science, Duke University, 1986 Ph.D. in Computer Science, University of Illinois at Urbana-Champaign, 1991 Professional Experience: Prior to academia, Blaauw worked at Motorola (1986–2001), managing the High Performance Design Technology group and winning the Motorola Innovation Award. He has published over 600 papers, holds 65 patents, and received numerous best-paper awards. Awards & Recognition: 2016 SIA-SRC Faculty Award IEEE Fellow MIT Technology Review’s Top Innovation (201X) Leadership Roles: 曾 served as general chair of the IEEE International Symposium on Low Power and on the ISSCC analog program subcommittee. His research has significantly influenced semiconductor design practices, particularly in energy efficiency.

Angela Gamourasمشاهده پروفایل

استاد مدعو

• Quantum Metrology
• Optical Radiometry
• Single-Photon Detection
• +۳ مورد دیگر

Dr. Angela Gamouras is an Adjunct Professor affiliated with the University of Ottawa's Department of Physics and the Joint Center for Extreme Photonics (JCEP). She is a physicist at the National Research Council of Canada's (NRC) Metrology Research Centre, where she focuses on optical radiometry traceable to the International System of Units (SI). Her research emphasizes few-photon metrology, including single-photon detector efficiency measurements and characterization of quantum dot-based single-photon sources. Dr. Gamouras' work bridges quantum metrology, novel material optical properties, and high-precision measurement techniques. She holds a PhD in Physics from Dalhousie University (2014) and previously worked in the fibre optics industry. Her current projects address Canada’s primary scale realizations for optical power and spectral irradiance, ensuring SI compatibility. Collaborations include the National Research Council and government research labs in Ottawa. Her research interests span quantum metrology applications, entangled photon experiments, and advancing optical measurement standards. Though no specific awards are mentioned, her contributions to quantum measurement science position her at the forefront of her field.

Robert Apsimonمشاهده پروفایل

مدرس ارشد

• High power RF electronics
• Radiotherapy
• Nonlinear & off-axis beam dynamics
• +۳ مورد دیگر

Dr. Robert Apsimon is a Senior Lecturer in Electronic Engineering at Lancaster University's School of Engineering. He previously conducted postgraduate research at CERN from 2012 to 2014 before joining Lancaster in 2014 as a Postdoctoral Research Associate (PDRA). His current affiliations include the RF Engineering of Accelerators at Lancaster (REAL) research group. He has held teaching positions at the LU/BJTU joint campus in Weihai, China since 2018. Robert earned his MPhys degree from Balliol College, University of Oxford in 2007, followed by a D.Phil. in feedback electronics at the same institution. His research interests focus on advanced RF engineering applications in particle accelerators and medical physics, including high-power RF systems, radiotherapy optimization, nonlinear beam dynamics, and broadband acceleration techniques. His projects span foundational and applied research: as Principal Investigator for CERN's AWAKE experiment (2020-2027), he explores proton-driven plasma wakefield acceleration. He leads the JLab-funded EIC project (2023-2027), mentors students in quantum engineering, and collaborates on the STELLA initiative (2024-2025) to develop high-reliability radiotherapy linear accelerators. Notable collaborations include STFC Impact Acceleration Account projects (2021-2022) and contributions to Cockcroft Phase 4 (2021-2025), enhancing accelerator technology for medical and scientific applications. Robert supervises 9 postgraduate research students, including Alexander Spelling. His work emphasizes practical solutions for accelerator design challenges, beam instability mitigation, and medical application advancements. No scientific awards are explicitly listed in the provided information.

Kevin Lederمشاهده پروفایل

استاد

• Stochastic Modeling
• Cancer Evolution
• Rare Event Simulation
• +۲ مورد دیگر

Kevin Leder is Professor and Director of Graduate Studies in the Department of Industrial and Systems Engineering at the University of Minnesota. His research spans stochastic modeling of cancer evolution and rare event simulation methodologies. His cancer research develops mathematical frameworks to understand evolutionary dynamics in tumors, including mechanisms of treatment resistance, recurrence patterns, and intratumoral heterogeneity. He applies optimization techniques to design improved therapeutic regimens and develops statistical methods for inferring tumor parameters from clinical data. A second research focus involves rare event analysis for stochastic systems including queuing networks and reflecting diffusions. Leder's publications demonstrate expertise in developing probabilistic models for cancer recurrence timing, inferring cellular dynamics from drug screen data, and optimizing treatment schedules using Bayesian approaches. His interdisciplinary work integrates methods from applied probability, statistics, and operations research. He has received research funding from NSF, NCI, and Fulbright Foundation. As Graduate Studies Director, he oversees academic programs and mentors students in mathematical oncology and stochastic processes.

Mircea Lazarمشاهده پروفایل

دانشیار

• Constrained Control
• Model Predictive Control
• Hybrid Systems
• +۴ مورد دیگر

Mircea Lazar is an Associate Professor in the Control Systems group at Eindhoven University of Technology. His research spans constrained control, model predictive control (MPC), and stability analysis of hybrid systems, with applications in power systems, smart grids, and precision mechatronics. Research highlights include: Development of data-driven predictive control methods Stability guarantees for nonlinear and hybrid systems Applications in water networks, power converters, and mechatronics He has received the EECI PhD Award and NWO VENI grant. Recent publications focus on real-time MPC implementations, physics-guided neural networks, and optimization for large-scale systems. Collaborations include ASML, DAF, Philips, and Ford. He chairs the IEEE CSS Technical Committee on Hybrid Systems and has supervised 9 PhD students.