جست‌وجوی استاد و پژوهشگر

Nivedita Aroraمشاهده پروفایل

استادیار

• Sustainable Computing
• Materials Science
• Computer Science
• +۷ مورد دیگر

Nivedita Arora is the Allen K. and Johnnie Cordell Breed Junior Professor of Design and Assistant Professor in the Departments of Electrical and Computer Engineering and Computer Science at Northwestern University's McCormick School of Engineering. She directs the VAK Sustainable Computing Lab, focusing on sustainable computational materials, energy harvesting, and ubiquitous computing systems. Her research integrates computer science, materials science, and environmental engineering to create eco-friendly technologies for climate change mitigation, smart infrastructure, and wildlife monitoring. Education: PhD (Computer Science, Georgia Tech), MS (Human-Computer Interaction, Georgia Tech), BS (Information Technology, Netaji Subhas Institute). Research Interests: Sustainable Computational Materials, Biodegradable IoT, Energy-Aware Quantum Computing, and Privacy in Smart Devices. Her lab emphasizes a sustainability-first approach across material production, system operation, and end-of-life disposal. Awards: ACM Dissertation Award (2023), Gaetano Borriello Award (2021), Fast Company Design Honoree (2021), and multiple best paper awards at ACM conferences. Grants & Mentoring: Secured over $1M in grants as PI, including funding for quantum sustainability and biodegradable sensors. Advised 15+ graduate/undergraduate researchers across materials science, electrical engineering, and computer science. Labs/Teams: VAK Sustainable Computing Lab (transdisciplinary team focused on eco-friendly computing innovations).

Prem Kumarمشاهده پروفایل

استاد

• Quantum Communications
• Quantum Sensing
• Quantum Imaging
• +۳ مورد دیگر

Prem Kumar is a Professor of Electrical and Computer Engineering at Northwestern University and Director of the Center for Photonic Communication and Computing. He is affiliated with the McCormick School of Engineering and the PhD Program in Applied Physics. His work focuses on advancing quantum communication, quantum sensing, fiber-optic systems, and photonic devices to enable secure quantum networks and ultrafast information processing. Prem Kumar holds a Ph.D. in Physics from the State University of New York at Buffalo (1980), an M.Sc. in Physics from the Indian Institute of Technology, Kanpur (1976), and a B.Sc. in Physics from the University of Delhi (1974). His research interests span quantum communications and quantum information processing, with a focus on quantum sensing, imaging, and fiber-optic technologies. He develops photonic systems for secure networking using quantum mechanics principles, emphasizing entanglement distribution and quantum light applications for precision measurements. Recent efforts include integrating quantum and classical communications in shared optical fibers and improving scalability of quantum-photonic systems with electronics. Recent articles highlight advancements in quantum wrapper networking, including noise mitigation strategies for classical-quantum coexistence, experimental quantum teleportation over deployed fiber, and CMOS-based quantum photonics. He explores scalable solutions for quantum light sources and network stabilization using feedback mechanisms. No scientific awards are mentioned in the text. His advising and grants narrative remains unspecified in the provided content, though his leadership in the Center for Photonic Communication and Computing indicates active research team coordination. He collaborates on projects like the Illinois Express Quantum Network (IEQNET), a metro-scale quantum networking initiative, and contributes to interdisciplinary labs involving photonics, electronics, and quantum mechatronics.

Ethan Ahnمشاهده پروفایل

دانشیار

• Nanoelectronics
• Energy-efficient Devices
• Carbon-based Nanomaterials
• +۶ مورد دیگر

Ethan Ahn is an Associate Professor at George Mason University's Department of Electrical and Computer Engineering, part of the Volgenau School of Engineering. Previously, he held academic positions at the University of Texas at San Antonio (2016–2023) and served as a senior panel process engineer at Apple and a postdoctoral researcher at Stanford University. He leads the Mason Nanoelectronics Lab, focusing on nanoscale materials and devices for energy-efficient electronics, spintronics, and beyond-CMOS technologies. Educational Background: PhD in Electrical Engineering, Stanford University (2015) MS and BS in Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST, 2005–2007) Research Interests: His work spans emerging nanomaterials (e.g., graphene, MoS2), energy-efficient logic/memory devices, and carrier transport mechanisms. Key areas include spintronics, phase-change memory, and energy harvesting systems. His lab collaborates with industry and government through VMEC and VAST alliances. Grants & Awards: Recipient of over $4M in funding, including the AFOSR Grant in Quantum Electronic Solids and the NSF EAGER Grant in Electronics/Photonics. He serves on IEEE technical committees and the editorial board of Scientific Reports. Labs & Teams: The Mason Nanoelectronics Lab operates a state-of-the-art nanofabrication facility, advancing research in nanoelectronics and workforce development. The lab explores biomedical devices, energy solutions, and smart infrastructure integration.

Mark Hempsteadمشاهده پروفایل

استاد

• computer architecture
• computer systems
• power-aware computing
• +۷ مورد دیگر

Mark Hempstead is a Professor in the Department of Electrical and Computer Engineering and Computer Science at Tufts University's School of Engineering. He leads the Tufts Computer Architecture Lab (TCAL) and has made significant contributions to computer architecture, systems research, and interdisciplinary applications of engineering tools to human subject research. Dr. Hempstead received his BS in Computer Engineering from Tufts University (Summa Cum Laude), and his MS and Ph.D. in Engineering from Harvard University, where he worked with Professors David Brooks and Gu-Yeon Wei. Prior to joining Tufts University in 2015, he was an Assistant Professor at Drexel University. His research focuses on increasing energy efficiency across circuits, architecture, and systems boundaries. Current research areas include: Computer architecture and systems Power-aware computing and embedded systems Mobile computing and machine learning systems Workload characterization and quantum computing Learning sciences and computer systems for human subjects research His group has published in several research communities including high-performance computer architecture, workload characterization, design automation, mobile systems, embedded systems, quantum computing, and Internet-of-Things. Recent publications show a strong trend toward machine learning systems, quantum computing architecture, and thermal management in modern processors, with applications spanning from embedded systems to high-performance computing platforms. Dr. Hempstead has received numerous scientific awards and honors: NSF CAREER award (2014) Allen Rothwarf Award for Teaching Excellence from Drexel University (2014) Excellence in Research Award from Drexel College of Engineering (2014) Winner of industry-sponsored SRC student design contest (2006) Best Paper Nominee in HPCA 2012 He has secured significant research funding including NSF Engineering Resource Center for Engineering Tools for Innovation and Research in Education (EnTIRE), multiple NSF grants including a CAREER award, DARPA funding, and industry collaborations with Google, Honeywell, and Facebook. His current research grants focus on hardware/software error detection, STEM education understanding, next-generation memory systems, and PCB assurance using thermal side-channel analysis. Dr. Hempstead leads the Tufts Computer Architecture Lab (TCAL), which investigates methods to increase energy efficiency across circuits, architecture, and systems. The lab has explored applications ranging from embedded systems and IoT to chip multiprocessors and high-performance computing. Current projects include systems support for machine learning, non-volatile memory design, thermal hotspot management, security implications of thermal side channels, automatic hardware accelerator generation, privacy-aware databases, and quantum computer architecture for ion-trap systems.

Thomas E. Bakerمشاهده پروفایل

استادیار

• Quantum Computing
• Quantum Algorithms
• Entanglement Renormalization
• +۴ مورد دیگر

Dr. Thomas E. Baker is an Assistant Professor and Canada Research Chair in Quantum Computing for Modelling of Molecules and Materials at the University of Victoria. He holds joint appointments in the Departments of Physics & Astronomy and Chemistry. His research focuses on quantum computing, quantum algorithms, and entanglement renormalization, with applications to quantum chemistry and density functional theory. He leads the sensing and quantum materials cluster under the Office of the VPRI and is a member of Quantum BC and the Centre for Advanced Materials and Related Technology. Education: M.Sc. (California State University Long Beach), PhD (University of California, Irvine), postdoctoral fellow at the Institute for Quantum Computing (IQ) at Université de Sherbrooke, and Fulbright U.S. Scholar at the University of York, UK. Research interests include quantum information processing, quantum error correction, and tensor networks. His team develops the DMRjulia library, a Julia-based tool for entanglement renormalization computations. Recent work emphasizes quantum algorithm design for near-term quantum computers and theoretical foundations of quantum materials. Scientific Awards: Fulbright U.S. Scholar (2018). Teaching includes graduate courses on quantum physics, computational methods, and tensor networks. He actively mentors students across physics, chemistry, and computer science backgrounds. Labs/Teams: Principal Investigator of the sensing and quantum materials cluster, co-developer of DMRjulia, collaborator in Quantum BC.

• Quantum Information Science
• Integrated Photonics
• Nanomechanics
• +۲ مورد دیگر

Han Zhao is an Assistant Professor in the Department of Physics at the University of Central Florida, leading the Laboratory for Hybrid Quantum Systems. His research integrates nanophotonics, quantum information science, and nanomechanics to develop quantum technologies. Key investigations include quantum transduction mechanisms, non-Hermitian topological systems, and acousto-optic computing architectures. His group leverages advanced nanofabrication to create interfaces between superconducting quantum processors and photonic networks.

Lu Pengمشاهده پروفایل

استاد

• Computer Architecture
• GPU Computing
• Quantum Computing
• +۲ مورد دیگر

Lu Peng holds the Yahoo! Founder Chair in Science and Engineering at Tulane University. His research spans computer architecture with focus on GPU optimization, quantum computing, and blockchain acceleration. Peng develops specialized hardware architectures for emerging computing paradigms, including quantum processors, blockchain processing units (BPUs), and efficient GPU memory systems. Recent innovations include GeauxTrace blockchain contact tracing and high-throughput GPU database indexing techniques. Awarded the ORAU Powe Award (2007) and IEEE conference best papers (2019, 2001), Peng maintains active research in computer systems design. He teaches graduate and undergraduate courses in computer architecture while directing research on next-generation computing paradigms.

David Isaacsonمشاهده پروفایل

استاد

• Mathematical Physics
• Medical Imaging
• Electrical Impedance Tomography
• +۳ مورد دیگر

David Isaacson holds the position of Professor in the Department of Mathematical Sciences at Rensselaer Polytechnic Institute (RPI), where he conducts cutting-edge research at the intersection of theoretical mathematics and clinical medicine. His primary institutional affiliation is with RPI, and he is also associated with the Center for Biotechnology and Interdisciplinary Studies, reflecting the multidisciplinary nature of his work. Professor Isaacson's long-term research goals center on improving diagnostic and therapeutic approaches for heart disease and cancer through innovative mathematical and engineering solutions. Professor Isaacson's research program is distinctly bifurcated into two major domains: mathematical physics and medical imaging. In mathematical physics, he develops advanced computational methods for approximating energy levels, particle masses, and critical exponents in quantum mechanics, quantum field theory, and statistical mechanics. His medical imaging research focuses on electrical impedance tomography (EIT), where he pioneers algorithms and hardware for non-invasively measuring and visualizing the electrical state of the body's interior from surface measurements. Specific applications include monitoring cardiac and pulmonary functions, diagnosing breast cancer through molecular impedance signatures, and optimizing chemotherapeutic interventions. His work in this area has significant clinical implications for conditions such as congenital heart defects, cystic fibrosis, and bronchopulmonary dysplasia. A review of Professor Isaacson's publication record from 2016 to 2025 demonstrates a sustained and evolving research trajectory in EIT technology. Early work concentrated on foundational reconstruction algorithms (e.g., D-bar and Calderón methods) and hardware development (ACT series systems), while recent publications emphasize clinical translation, particularly in pediatric cardiology and pulmonology. His team has produced innovative solutions for simultaneous EIT/ECG acquisition, 3D absolute imaging, and dynamic monitoring of ventilation-perfusion relationships. The consistent theme across these studies is the rigorous application of mathematical theory to solve practical biomedical imaging challenges, resulting in tools that are increasingly adopted in clinical settings for real-time physiological monitoring. No scientific awards or major honors were explicitly documented in the available sources. While detailed information about academic advisees, grant funding, or dedicated laboratory facilities was not provided in the current materials, Professor Isaacson's extensive collaborative network is evident from his numerous co-authored publications with clinicians and engineers. His work with the Center for Biotechnology and Interdisciplinary Studies suggests active participation in multidisciplinary research teams focused on translating engineering innovations into medical practice. Future research directions likely include further refinement of EIT for point-of-care diagnostics and expansion into new disease areas through continued cross-disciplinary partnerships.

Samuel Hedemannمشاهده پروفایل

مدرس

• Quantum Information Science
• Quantum Computation
• Quantum Entanglement
• +۴ مورد دیگر

Dr. Samuel Hedemann is a Lecturer of Physics at Stevens Institute of Technology, specializing in quantum information science, quantum computation, and theoretical physics. He holds a PhD from Stevens Institute of Technology (2014) and a BS from the University of Maryland, Baltimore County (2008). His research focuses on quantum entanglement universality, quantum computational hardware design, and post-quantum computation applications. Notable contributions include the development of TGX states theory and advancements in quantum teleportation resilience. Education: PhD in Physics (2014), Stevens Institute of Technology BS in Physics (2008), University of Maryland, Baltimore County Research Interests: Dr. Hedemann’s work bridges theoretical quantum mechanics with applied technologies. He explores entanglement universality across N-body systems, aiming to simplify quantum state analysis for practical applications like drug discovery and climate modeling. Recent achievements include proving TGX state universality for qubit-qutrit systems and designing noise-resistant quantum protocols. Awards: Inventor's Award (Johns Hopkins University APL, 2016) Quantum Information Science Postdoctoral Fellowship (2015–2016) Innovation & Entrepreneurship Doctoral Fellowship (2009–2014) Sigma Pi Sigma Honor Society (2008) Grants & Advising: Recipient of major fellowships from JHUAPL and Stevens. Advised students via courses like Quantum Information and Computation (PEP 557). Active in curriculum development for quantum computing education. Patents & Inventions: Filed disclosures for quantum computational devices at JHUAPL (2016) and Stevens (2014), advancing quantum communication and hardware design.

Chunhong Chenمشاهده پروفایل

استاد

• Digital Integrated Circuit Synthesis
• VLSI Computer-Aided Design
• High-Performance Low-Power Systems
• +۱ مورد دیگر

Dr. Chunhong Chen is a Professor in the Department of Electrical and Computer Engineering at the University of Windsor's Faculty of Engineering. He holds a PhD from Fudan University and is a P. Eng of Ontario and IEEE Senior Member. His research focuses on digital integrated circuit synthesis, VLSI CAD, high-performance low-power systems, and nanoelectronic circuit design. Education: PhD, Fudan University Recent work includes hybrid signal probability estimation methods, statistical delay modeling for nanoelectronics, and area-efficient cryptographic circuit design using hybrid SET-MOS technology. His research emphasizes practical applications in low-power systems and nanoscale device optimization. Dr. Chen's publications demonstrate expertise in both foundational theory and applied engineering solutions. He leads the Research Centre for Integrated Microsystems (RCIM), focusing on advanced microsystem integration challenges.

Sherali Zeadallyمشاهده پروفایل

استاد

• Artificial Intelligence
• Cybersecurity
• Cloud Computing
• +۳ مورد دیگر

Sherali Zeadally is a Professor and UK Alumni Association Endowed Professor at the School of Information Science, University of Kentucky. His expertise spans Cybersecurity, Artificial Intelligence, and Network Security. He holds a PhD from the University of Buckingham and a Bachelor's in Computer Science from the University of Cambridge, with postdoctoral research at the University of Southern California. Research focuses include AI threats, vehicular network privacy, cloud-edge computing, and supply chain security. Recent work addresses adversarial machine learning, quantum-inspired algorithms, and IoT security. Recipient of 64 honors/awards including NASA Faculty Fellowship and Best Paper Awards Over 557 publications since 1996 Active in global collaborations, particularly in cybersecurity advancements for smart systems.

Mostafa Tahaمشاهده پروفایل

استادیار

• Security of Embedded Systems
• Internet of Things (IoT)
• Implementation Attacks and Countermeasures
• +۳ مورد دیگر

Mostafa Taha is an Assistant Professor at Carleton University's Systems and Computer Engineering Department within the Faculty of Engineering and Design. He holds a PhD from Virginia Tech (2014) and has held postdoctoral roles at Worcester Polytechnic Institute and Western University. His research focuses on securing embedded systems and IoT against implementation attacks, including side-channel analysis, leakage-resilient designs, and cryptographic algorithm hardening. He has contributed to projects like LR-Keymill, a keystream generator with inherent SCA resistance, and has served on program committees for conferences such as DATE and SPACE. Education includes a PhD in Computer Engineering (Virginia Tech), M.Sc. in Electrical Engineering (Assiut University), and B.Sc. in Electrical Engineering (Assiut University). His work spans hardware security, cryptographic implementations, and vehicular networks. Awards include Egyptian Government and Assiut University scholarships for his PhD and M.Sc., respectively. Research interests emphasize quantifying side-channel resistance, leakage-resilient architectures, and lightweight cryptographic implementations. Notable publications include work on AES S-box optimization, threshold implementations for SIMON, and quantifying masking strength in software. He teaches courses on cryptographic implementations, computer systems design, and digital systems at Carleton. Publications reflect a focus on hardware-oriented security, with contributions to conferences like CHES, FDTC, and HOST. His work on LR-Keymill demonstrates a novel approach to SCA resistance without explicit countermeasures, achieving 67.9-bit post-attack complexity. Awards and industrial connections highlight his impact in embedded system security.

Bayaner Arigongمشاهده پروفایل

استادیار

• RF/Microwave Passive Circuit Design
• Beamforming Phased Array Antenna
• RF Power Amplifier Design
• +۶ مورد دیگر

Dr. Bayaner Arigong is an Assistant Professor in the Department of Electrical & Computer Engineering at Florida A&M University - Florida State University. He holds a Ph.D. in Computer Science and Engineering from the University of North Texas (2015), and M.Sc. and B.Sc. degrees in Electrical Engineering from China University of Geosciences, Wuhan (2008 and 2005). Prior to academia, he worked as an RF System Design Engineer at Infineon Technologies (2014–2017). Education: Ph.D., Computer Science and Engineering, University of North Texas, 2015 M.Sc., Electrical Engineering, China University of Geosciences, Wuhan, China, 2008 B.Sc., Electrical Engineering, China University of Geosciences, Wuhan, China, 2005 Research Interests: Beamforming Phased Array Antenna Integrated Passive Device Design Electromagnetic Cloaking & Metamaterials His recent work focuses on frequency-agile RF analog co-processors , 3D-printed reconfigurable components , and deep learning-enhanced monopulse receivers . Over 60 publications span topics like tunable Nolen matrices, VO₂-based smart materials, and IoT spectrum coexistence frameworks. He leads a research group actively recruiting students in RF systems, high-frequency circuits, and electromagnetic theory. Lab/Team: Active research group focused on RF circuit innovation and applied electromagnetic systems.

Rakshith Saligramمشاهده پروفایل

استادیار

• Cryogenic VLSI Circuits
• Quantum Computing Hardware
• TCAD Modeling
• +۶ مورد دیگر

Rakshith Saligram is an Assistant Professor in the Min H. Kao Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville, part of the Tickle College of Engineering. His research focuses on cryogenic VLSI circuits, quantum computing hardware, and TCAD modeling. He holds a PhD from Georgia Institute of Technology, an MS from the University of Southern California, and a BE from BMS College of Engineering, India. Education: PhD Electrical and Computer Engineering, Georgia Tech (Atlanta, U.S.) MS Electrical and Computer Engineering, University of Southern California (Los Angeles, U.S.) BE Electronics and Communication, BMS College of Engineering (Bangalore, India) His research interests include cryogenic circuits, compute-in-memory systems, and high-performance computing architectures. Recent work spans cryogenic DRAM designs, analog CIM systems, and cryogenic CPU optimization. His publications highlight advancements in low-temperature operation (down to -270°C) for quantum computing applications. Awards & Recognition: Colonel Oscar P. Cleaver Dissertation Proposal Award Nominee (2023) EDS PhD Fellowship (2022) Qualcomm Innovation Fellowship Finalist (2022) He has organized collaborations with IMEC USA and presented at venues like IEEE CICC and IEDM. His lab focuses on bridging cryogenic electronics and quantum computing infrastructure.

Ulrike Stegeمشاهده پروفایل

دانشیار

• Computational Biology
• Parameterized Complexity
• Design of Heuristics
• +۴ مورد دیگر

Ulrike Stege is an Associate Professor and Director of the Master of Engineering in Applied Data Science (MADS) at the University of Victoria's Faculty of Engineering and Computer Science. She holds a PhD from the Swiss Federal Institute of Technology (ETH Zurich). Her research spans computational biology, parameterized complexity, algorithm design, graph theory, and cognitive psychology. She leads initiatives in quantum computing frameworks and educational tools, including projects like SCOOP (quantum optimization) and QGrover (quantum algorithm visualization). Her work also addresses RNA pseudoknot structure prediction and the integration of quantum computing into combinatorial optimization software. Key educational contributions include developing browser-based quantum learning tools (e.g., QNotation and QuantumCrypto) and promoting computational thinking in K-12 education. Her research bridges theoretical computer science with practical applications in biology and quantum systems, emphasizing algorithmic innovation and interdisciplinary collaboration. Her publications focus on advancing quantum computing frameworks, optimizing bioinformatics algorithms, and creating accessible educational resources. Recent work addresses quantum annealing for constrained optimization, structural biochemistry of viral RNA, and hybrid quantum-classical problem-solving methods.