جست‌وجوی استاد و پژوهشگر

• Quantum Communication
• Quantum Computing
• Dynamics of Classical Networks
• +۵ مورد دیگر

Daniel J. Gauthier is a Professor in the Department of Physics at The Ohio State University, affiliated with the College of Arts and Sciences. He leads the QuantInfo Laboratory and serves as Deputy Editor of Optica . His work focuses on quantum communication, quantum computing, and classical network dynamics. Education: Ph.D. in Optics, University of Rochester (1989) M.S. in Optics, University of Rochester (1983) B.S. in Optics, University of Rochester (1982) Research Interests: Dr. Gauthier develops quantum key distribution systems for secure communication, superconducting nanowire detectors for quantum optics, and photonic approaches to quantum computing and machine learning. He also explores classical information processing using FPGAs and neural networks. Awards & Honors: 2009 Outstanding Referee (Physical Review) Fellow of APS (2002) and OSA (2006) Multiple Young Investigator Awards (NSF, U.S. Army) Grants & Collaborations: Collaborates with Prof. Gregory Lafyatis on quantum detector technology. Funded by NSF, U.S. Army, and Duke University grants. His research bridges quantum and classical systems, with applications in security and AI. Labs & Resources: Directs the QuantInfo Laboratory at Ohio State, advancing quantum technologies and photonics.

Jeremy Buhlerمشاهده پروفایل

استاد

• Cyberphysical Systems
• Internet of Things
• Parallel Computing
• +۵ مورد دیگر

Jeremy Buhler is a Professor of Computer Science & Engineering at Washington University in St. Louis, with secondary appointments in the Genetics Department (Division of Biological and Biomedical Sciences) and the Biology Department (College of Arts & Sciences). He joined the faculty in 2001 and focuses on advancing computational methods for analyzing large-scale biological data. Education: PhD, University of Washington, 2001 MS, University of Washington, 1998 BA, Rice University, 1996 His research bridges Cyberphysical Systems and Parallel Computing , addressing challenges in genomic, metagenomic, and proteomic analysis. He develops algorithms to accelerate searches of massive biological sequence databases, leveraging probabilistic methods and hardware accelerators like FPGAs and GPUs. Recent work includes optimizing dynamic programming for systolic arrays and deadlock-free dataflow applications. In collaboration with researchers, he has contributed to projects such as a gamma-ray astronomy mission (co-investigator, 2021). His lab explores computational infrastructure for next-generation sequencing, emphasizing scalability and efficiency. For more details, visit his lab website or Google Scholar . Jeremy advises students in computational biology and engineering, though specific advisee names are not listed here. His work aligns with interdisciplinary goals at the McKelvey School of Engineering and the broader university.

Ed Richterمشاهده پروفایل

استاد

• Biomedical Engineering
• Signal Processing
• Digital Circuit Design
• +۳ مورد دیگر

Ed Richter is a Professor of Practice in the Department of Electrical & Systems Engineering at Washington University in St. Louis’s McKelvey School of Engineering. He joined the university in 1998 as a full-time research associate, focusing on commercializing the Magneprint project and collaborating across disciplines. Education: MS, Washington University, St. Louis, MO, 2001 BS, Virginia Tech, Blacksburg, VA, 1985 His expertise spans biomedical signal processing systems, analog instrumentation, FPGA design, and digital circuits. Richter teaches lab courses in FPGA development and signal processing, emphasizing hands-on engineering. He collaborates with faculty in Electrical & Systems Engineering, Computer Science, Physics, and Psychiatry, focusing on signal processing applications across platforms like ASIC, FPGA, and desktop computers. Richter has been involved in projects such as light-based brain-imaging technology, supported by an NIH grant. His work bridges academia and industry, advancing medical imaging and technology commercialization. Notable collaborations include partnerships with physicians and engineers to improve health outcomes through imaging science. He has no listed scientific awards but has secured grants for interdisciplinary research.

Shuo Wangمشاهده پروفایل

استاد

• Power Electronics
• Electromagnetic Interference (EMI)
• Electric Vehicles
• +۵ مورد دیگر

Shuo Wang is a Professor and Michael Hsing Faculty Fellow at the University of Florida's Department of Electrical & Computer Engineering, part of the College of Engineering. His research focuses on power electronics, electromagnetic interference (EMI), electric vehicles, hardware security, and IoT/cyber security. He holds an IEEE Fellowship (2019) and has received the NSF CAREER Award (2012). His work spans EMI modeling/reduction in power systems, secure wireless charging, and hardware security tools like HT-EMIS and GAZEploit. Education : Ph.D., Virginia Tech MSEE, Zhejiang University BSEE, Southwest Jiaotong University Research Highlights : - Developed novel inductor designs (e.g., 2D-core/origami-winding) to reduce EMI - Pioneered EMI modeling techniques for EV systems and SiC motor drives - Advanced hardware security through runtime EM analysis and FPGA deployment methods - Integrated NFC/wireless charging technologies for consumer electronics - Addressed cybersecurity risks in VR/MR devices and industrial systems Awards : HWCOE Doctoral Dissertation Advisor Award (2024) UF Innovate Invention of the Year (2023) NSF CAREER Award (2012) Grants & Advising : Recipient of multiple NSF grants and industry partnerships. Advises on cutting-edge topics like EMI mitigation in wide bandgap devices and secure cloud FPGA deployment. No specific grant details listed in provided text.

• Photonics
• Lasers
• Electromagnetics

Henry Zmuda is an Associate Professor in the Department of Electrical & Computer Engineering at the University of Florida. His primary research area is Electrophysics, with a focus on Photonics, Lasers, and Electromagnetics. He holds a Ph.D. and M.S. in Electrical Engineering from Cornell University (1984 and 1982), and a B.E. in Electrical Engineering from Stevens Institute of Technology (1979). His research interests span advanced optical materials, high-speed signal processing systems, and sensor technologies. He has contributed significantly to photonic-based analog-to-digital converters, phased array antennas, and thermal acoustic imaging. His work frequently integrates photonics with electronic systems to solve challenges in telecommunications, aerospace, and biomedical applications. Key research trends include investigations into surface plasmon polaritons in novel materials like lanthanum nickelate and barium titanate, as well as the development of high-resolution photonic ADC architectures. His publications also highlight innovations in beamforming systems, wireless sensors for fluid dynamics, and resonant thermal imaging methodologies. Zmuda’s advising and grants activities are not detailed in the provided text, though his extensive publication record suggests active participation in graduate research supervision. His laboratory work likely focuses on experimental photonics and sensor prototyping, though specific lab affiliations are not explicitly mentioned.

Paul Padleyمشاهده پروفایل

استاد

• Particle Physics
• High Energy Physics
• Standard Model
• +۴ مورد دیگر

B. Paul Padley is the Vice President for IT and Chief Information Officer at Rice University, overseeing technology strategies. He is a Professor of Physics and Astronomy and Director of the T.W. Bonner Nuclear Laboratory, affiliated with the Department of Physics and Astronomy. With over 30 years at Rice, he leads U.S. contributions to the CMS detector at CERN's Large Hadron Collider. Education: Ph.D. & M.S. in Physics, University of Toronto (1987, 1984) B.S. in Physics, York University (1981) Research Interests: Particle physics beyond the Standard Model, Higgs sector exploration, supersymmetry, and advanced machine learning techniques for signal/background separation in high-energy collisions. His group develops custom electronics and GPU/FPGA-based systems for ultra-rare event detection in CMS experiments. Articles Overview: Recent work focuses on precision measurements of particle interactions at the LHC, including jet production dynamics, Higgs boson decays, and searches for new physics. Machine learning applications dominate experimental analyses with signal/background ratios as low as 1:10¹⁰. Awards: Fellow of the American Physical Society (APS). Grants & Labs: Leads the T.W. Bonner Lab’s CMS operations. Active in designing next-gen electronics for LHC upgrades. Collaborates with CERN and U.S. academic institutions on detector technology advancements.

V Kumarمشاهده پروفایل

استاد

• Marketing
• Customer Relationship Management
• Global Marketing
• +۲ مورد دیگر

V Kumar is Goodman Academic-Industry Partnership Professor and Professor of Marketing at Brock University's Goodman School of Business. A leading scholar recognized as a 'Marketing Legend' in the Sage Legend Series, he has held distinguished positions at University of Houston, University of Connecticut, and Georgia State University. His research spans marketing accountability, globalization, customer relationship management, and technology-driven innovation. Kumar's work has generated over $2B+ in revenue gains for businesses implementing his models. Honors include the 2024 Shri BML Jain Lifetime Achievement Award, 2023 Tara Lifetime Achievement Award, and induction into the Analytics Hall of Fame (2019). He has published over 300 scholarly papers and 30 books, receiving 25+ research excellence awards. Recent research examines international marketing transformations, firm resilience during crises, and methodological advancements in cross-cultural studies. His work consistently addresses the intersection of technology, globalization, and marketing strategy.

• Cloud Computing
• Grid Computing
• Health Informatics
• +۵ مورد دیگر

David Levine serves as an Associate Professor in the Computer Science and Engineering Department within the College of Engineering at The University of Texas at Arlington. His academic career spans decades with continuous teaching and research contributions, evidenced by his ongoing course instruction through Fall 2025 and active grant leadership. Levine's research spans cloud and grid computing, health informatics, bioinformatics, pervasive computing, and secure programming. His work integrates computational techniques with practical applications in healthcare (Smart Hospital for Elderly Care), high-energy physics (Fermilab collaborations), and accessibility infrastructure. He has pioneered curriculum development in emerging fields including Cloud Computing, Secure Programming, Mobile Computing, and Data Mining, with courses consistently reaching maximum enrollment capacity and establishing distance learning records within the engineering college. His publication portfolio demonstrates significant interdisciplinary impact across IEEE Supercomputing, health informatics, genetics, and pervasive computing. Recent work focuses on spatial data visualization for public health (2022), hardware simulation platforms (2017), and scalable notification frameworks for healthcare systems (2011). His research has secured over $5 million in funding from NSF, NIH, DoE, and industry partners including Luminant Power. Computer Science Department Teaching Award recipient Student teams won ATT University Challenge, Nokia Symbian Challenge, and Department of Energy Challenge ($200k+ total) Levine has mentored 4 PhD students as co-supervisor, chaired 6 Master's theses, and advised numerous undergraduate researchers. His laboratory work focuses on grid computing applications for high-energy physics and bioinformatics, with current projects including the GAANN Doctoral Fellowships in IoT and Smart Hospital infrastructure development. He serves as NTT Hiring Committee Chair and Faculty Senate Chair, demonstrating significant institutional leadership.

• Machine Learning
• MPPT Algorithms
• Harmonic Detection
• +۵ مورد دیگر

Assoc. Prof. Marko Dimitrijević is affiliated with the University of Niš, Faculty of Electronic Engineering, where he holds the position of Associate Professor since 2021. He leads the Laboratory for Electronic Design Automation (LEDA) and the Laboratory for Electronics. His academic journey includes a PhD in 2012 on 'Electronic System for Polyphase Loads Analysis Based on FPGA' and postgraduate studies from 2005. He has conducted research exchanges at Technische Universität Ilmenau (Germany), IHP Microelectronics (Germany), the University of Southampton (UK), and Universidad Politécnica de Madrid (Spain). Prof. Dimitrijević teaches courses such as 'Introduction to Electronics' and 'System on a Chip' across undergraduate, master’s, and doctoral programs. His research focuses on MPPT algorithms, harmonic detection, FPGA applications, and smart grid technologies. He has supervised two master’s theses and contributed to numerous academic publications. His work bridges theoretical advancements with practical applications in renewable energy systems and power electronics. Education: Bachelor's in Electronics and Telecommunications (2002, Faculty of Electronics, Niš) Master's in Electronics (2005, Faculty of Electronics, Niš) PhD in Electronics (2012, Faculty of Electronics, Niš) Professional Roles: Assistant Professor (2016–2021) Associate Professor (since 2021) Head of LEDA and Electronics Lab Research Highlights: Development of FPGA-based systems for polyphase load analysis MPPT controller optimization for standalone PV systems Nonlinear load characterization using machine learning Labs & Teams: LEDA focuses on electronic design automation and power electronics, while the Electronics Lab supports undergraduate teaching and experimental research.

Anju Johnsonمشاهده پروفایل

مدرس ارشد

• Astrocyte-Neuron Networks
• Hardware Security
• Internet of Things
• +۲ مورد دیگر

Anju Johnson is a Senior Lecturer in Computer Science at the University of Huddersfield's School of Computing and Engineering. She holds a Ph.D. in Computational Media Design and researches astrocyte-neuron networks, hardware security, and Internet of Things systems. Her work focuses on biologically-inspired computing and secure hardware design. Dr. Johnson's expertise includes FPGA-based systems, hardware-intrinsic security, and anomaly detection. She develops fault-tolerant neural network architectures inspired by astrocyte-neuron interactions in the brain. Her recent work explores multi-layer security models for 5G-enabled Industrial IoT and remote dynamic partial reconfiguration of FPGA systems.

Ronald F. DeMaraمشاهده پروفایل

استاد

• Computer Systems Architecture
• Machine Learning Hardware
• Reconfigurable Computing
• +۲ مورد دیگر

Ronald F. DeMara is a Professor in the Department of Electrical and Computer Engineering at the University of Central Florida's College of Engineering and Computer Science. He holds a Ph.D. in Computer Engineering from the University of Southern California (1992). His research focuses on adaptive hardware systems, energy-efficient computing architectures, and educational innovations in STEM fields. Current research explores machine learning accelerators, hardware security, and reconfigurable computing fabrics. He leads projects on adaptive rate/resolution designs for spectral signal acquisition and probabilistic spin logic for low-energy computing. DeMara's publication trends focus on hardware-software co-design, educational technology innovations, and emerging memory technologies. Recent work integrates AI/ML techniques with hardware optimization for applications ranging from cybersecurity education to efficient neural network implementations. Honors include: Online Learning Consortium Effective Practice Award (2018) IEEE Outstanding Engineering Educator (2008) Multiple Teaching Incentive and Research Incentive Awards He directs educational initiatives including the Digitally-Mediated Team Learning project and Digitizing STEM Assessments program, securing funding from NSF, Semiconductor Research Corporation, and technology grants.

Arsène Pérard-Gayotمشاهده پروفایل

پژوهشگر ارشد

• Computer Graphics
• Ray Tracing Algorithms
• High-Performance Computing
• +۱ مورد دیگر

Dr. Arsène Pérard-Gayot is a Research Fellow in the Computer Graphics Lab at Saarland University, Germany. His research develops high-performance rendering systems through compiler innovations and hardware optimization techniques. Pérard-Gayot's work creates frameworks for automatic generation of optimized renderers using partial evaluation, eliminating manual compiler development. His FLOWER compiler enables efficient dataflow programming for FPGAs, while Rodent generates specialized renderers for CPUs/GPUs. Additional contributions include ray tracing acceleration structures for irregular grids and BVH traversal abstractions. Publications demonstrate consistent focus on bridging high-level programming models with hardware efficiency. Collaborative projects include molecular dynamics simulation mapping to heterogeneous architectures and distributed ray tracing for massive scenes. Research outcomes advance real-time rendering capabilities and domain-specific compiler technologies for scientific computing.

Jesús Ureña Ureñaمشاهده پروفایل

استاد

• Electronic Engineering
• Positioning Systems
• Infrared Sensors
• +۳ مورد دیگر

Jesús Ureña Ureña is Full Professor of Electronics at the University of Alcalá, heading the GEINTRA research group in electronic engineering applied to intelligent spaces. His research develops positioning systems using ultrasonic/infrared technologies with applications in assisted living. Research focuses on: Infrared/ultrasonic positioning architectures Sensor fusion for 3D localization FPGA-based signal processing Industrial IoT and edge computing Non-intrusive load monitoring Developed systems include LOCATE-US ultrasonic positioning and QUAPOS visible light positioning. Leads projects on high-frequency signal acquisition and adaptive federated learning. Awarded UAH Social Council Award for 'Ambient intelligence for independent living' (2019).

Kevin Luمشاهده پروفایل

استاد آموزشی

• Telecommunications
• Network Survivability
• Fiber Optics
• +۵ مورد دیگر

Kevin Lu is a Teaching Professor and Associate Chair for Undergraduate Studies in Stevens Institute of Technology's Department of Electrical and Computer Engineering. He holds a PhD in Systems Science and Mathematics from Washington University in St. Louis and a BS in Control Engineering from National Chiao Tung University. His career spans 28 years at Bellcore/Telcordia, where he led applied research in telecommunications, followed by roles at Broadcom and Stevens. He is actively involved in IEEE standards development, serving in leadership roles on multiple committees, including the IEEE Standards Association Audit and Industry Connections Committees. Research interests include network survivability, fiber optics, vehicular communications, and standards for autonomous systems. He emphasizes ethical design principles in technology through courses on research ethics and technical writing. Awards include the Henry Morton Distinguished Teaching Professor Award (2018-2019) and Stevens' Outstanding Service Award (2023). He has contributed over 50 peer-reviewed publications and holds leadership roles in professional societies like IEEE Communications Society. Teaching focuses on engineering design, IoT, and research methodologies. Advises on grants related to FPGA-accelerated image processing and standards development. Active in curriculum development, admissions outreach, and student wellbeing initiatives.

• Signal Processing
• Computer Vision
• Quantum Computing
• +۲ مورد دیگر

Dr. David Muresan is Teaching Professor at Stevens Institute with PhD from Cornell. Develops frameworks for sensor data processing using: Computer vision algorithms Quantum computing applications FPGA-based systems Model-driven engineering Holds 8 patents in image processing and hardware design. Recipient of 2024 teaching excellence award.