جست‌وجوی استاد و پژوهشگر

Hai (Helen) Liمشاهده پروفایل

استاد

• Neuromorphic Computing
• Machine Learning
• Emerging Memory Technologies
• +۳ مورد دیگر

Hai (Helen) Li is a Professor and Clare Boothe Luce Associate Chair at Duke University's Electrical and Computer Engineering department. She was a TUM-IAS Hans Fischer Fellow (2017) hosted by Prof. Ulf Schlichtmann in the Neuromorphic Computing focus group. Education: B.S./M.S. from Tsinghua University, Ph.D. from Purdue University Positions: Qualcomm, Intel, Seagate, Polytechnic Institute of New York University, University of Pittsburgh Her research spans neuromorphic computing systems , machine learning acceleration , emerging memory technologies , and low-power circuits . Publications demonstrate expertise in ReRAM/memristor-based accelerators, sparse neural networks, and processing-in-memory architectures. Key contributions include cross-layer optimization frameworks and robust neuromorphic designs. Her awards include: 9 Best Paper Awards (ASPDAC, ICMLA, ISVLSI, etc.) NSF Career Award DARPA Young Faculty Award IEEE Fellow (2019) ACM Distinguished Member (2017) IEEE TCSDM Outstanding Leadership Award (2021)

Changhee Jungمشاهده پروفایل

دانشیار

• Compilers
• Computer Architecture
• Performance Optimization
• +۸ مورد دیگر

Changhee Jung is the Samuel D. Conte Associate Professor in the Department of Computer Science at Purdue University. His research focuses on compilers and computer architecture with an emphasis on performance, reliability, and security. His educational background includes a Ph.D. from Georgia Tech (2013) under the supervision of Prof. Santosh Pande. Professor Jung's research spans compilers and computer architecture with a focus on performance, reliability, and security. He has developed program analysis and microarchitecture optimization techniques for soft error resilience, concurrency bug detection, and system security such as memory safety and Linux kernel permission check. Currently, he is working on energy-efficient intermittent computation and nonvolatile memory crash consistency. He often leverages compiler-architecture codesign and repurposes existing hardware features to develop cost-effective solutions for complex computing challenges. His recent publications demonstrate a clear trajectory toward intermittent computing systems, nonvolatile memory architectures, and security mechanisms for energy-constrained environments. His work shows innovative approaches to power failure recovery, capacitor vulnerability exploitation, and EMI attack defense in intermittent systems, with significant contributions to whole-system persistence, cache design, and prefetching techniques for low-power computing. His notable scientific achievements include: NSF CAREER Award (2018) Inducted into MICRO Hall of Fame (2021) Best Paper Honorable Mention in ISCA 2025 Memorable Paper Award Finalist in NVMW 2024 Dissertation Advisor of 2023 ACM SIGBED Paul Caspi Memorial Dissertation Award winner Jongouk Choi 2017 AMD Faculty Research Award Professor Jung has successfully advised numerous graduate students, many of whom have secured prominent positions at leading technology companies including Google, Intel, and Samsung Electronics. His lab, the CompArch (Compiler and Architecture) research group, was formed in 2013 at Virginia Tech and continues at Purdue, focusing on compiler-architecture cooperation to address cross-cutting concerns involving performance, reliability, and security. The lab has received significant research funding, including an NSF CAREER Award in 2018 and an AMD Faculty Research Award in 2017.

Vishal Saxenaمشاهده پروفایل

استاد

• Silicon Photonic Integrated Circuits
• Neuromorphic Computing
• CMOS Electronics
• +۳ مورد دیگر

Professor Vishal Saxena is a faculty member in the Department of Electrical and Computer Engineering at the University of Delaware since 2019. Previously, he held positions at Boise State University (2010–2016) as Assistant and Associate Professor, and served as the Micron Endowed Professor of Microelectronics at the University of Idaho (2016–2019). His research focuses on analog electronic and photonic integrated circuits (ICs), particularly in sustaining IC design advancements post-Moore scaling through hybrid CMOS-photonic integration, neuromorphic computing, and energy-efficient embedded intelligence. Dr. Saxena earned his B.Tech. in Electrical Engineering from IIT Madras (2002), followed by M.S. and Ph.D. in Electrical and Computer Engineering from Boise State University (2007–2010). He has industry experience in semiconductor and telecommunication engineering. His work is supported by NSF, AFOSR, DARPA, NASA, and industry collaborators. Notable awards include the NSF CAREER (2015), AFOSR YIP (2016), and DARPA YFA (2019). His research interests span silicon photonic ICs for optical interconnects, RF photonic systems, neuromorphic circuits using emerging NVM devices, and high-speed analog-to-digital converters. He has pioneered compact modeling techniques for photonic components and developed energy-efficient architectures for spiking neural networks. Dr. Saxena’s publications reflect advancements in photonic integration, neuromorphic hardware, and mixed-signal IC design. He actively contributes to the IEEE community through editorial roles and conference steering committees, including MWSCAS and ISCAS.

Yichuang Sunمشاهده پروفایل

استاد

• Wireless Communications
• 5G/6G Technologies
• RF Circuits and Systems
• +۷ مورد دیگر

Yichuang Sun is a Professor of Communications and Electronics at the University of Hertfordshire, leading the Communications and Intelligent Systems Research Group and the Electrical and Electronic Engineering Department. He holds a PhD from the University of York (1996) and has over 450 peer-reviewed publications, 5 authored books, and 40+ supervised PhD students. His research focuses on wireless communications (5G/6G, RIS-aided systems), RF/microwave circuits, neuromorphic computing, and machine learning applications. He serves as Editor or Guest Editor for 12+ IEEE/IET journals and chairs technical committees for IEEE conferences. Notably ranked in the World's Top 2% Scientists since 2019, he also advises global institutions like Oxford and the Royal Academy of Engineering. Education: PhD in Electronics, University of York, UK (1996) Research Interests: Wireless/Mobile Communications and Networks RF and Microelectronic Circuits Neuromorphic Computing and Machine Learning Memristor-based Systems Secure and Energy-Efficient Communications Grants & Projects (selected): Advanced mmWave MIMO 4D Radar for Traffic Detection (2024–2027) Wireless Power Transfer for Implantable Medical Devices (2023–2025) RFID System for Sample Management (2021–present) Labs/Teams: Leads the Communications and Intelligent Systems Research Group, collaborating on 6G, neuromorphic hardware, and IoT systems.

Amit Ranjan Trivediمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Hardware Security
• Nano-robotics
• +۳ مورد دیگر

Amit Ranjan Trivedi is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Illinois at Chicago (UIC). He completed his B.Tech. and M.Tech. at the Indian Institute of Technology (IIT) Kanpur (2003-2008), where he received an Academic Excellence Award, and earned his Ph.D. at Georgia Institute of Technology (Georgia Tech) from 2010 to 2015. His research focuses on Artificial Intelligence (AI) at the edge , Hardware Security , and Nano-robotics , with an emphasis on low-power and neuromorphic computing using emerging technologies like Tunneling field-effect-transistors and magneto-tunneling junctions. Trivedi's publications reveal a strong interdisciplinary approach spanning VLSI Systems , Neural Networks , Nanotechnology , and Embedded Systems . His work addresses challenges in device authentication , energy-efficient AI , and nonvolatile memory , often leveraging nanoscale phenomena for novel applications. NSF CAREER Award (2021): Robust and Ultra-low-power Spatial Intelligence Sigma Xi Best PhD Dissertation (2015) IEEE Electron Device Society Fellowship (2014) Academic Excellence Award, IIT Kanpur (2005) At UIC, he has secured the College of Engineering Seed Funding award and the Phase-I Chancellor’s Proof-of-Concept award. His prior roles included research internships at IBM T.J. Watson Research Center (2012) and Intel’s Circuit Research Lab (2014), following his tenure at IBM Semiconductor Research and Development Center (2008-2010).

• Marketing
• Consumer Behavior
• Brand Management
• +۴ مورد دیگر

Lawrence Ang is an Associate Professor and Honorary Associate Professor in the Department of Marketing at Macquarie University. His research focuses on consumer behavior, brand equity, advertising creativity, and digital marketing strategies. He has led notable projects such as improving the Bachelor of Business Administration (BBA) program and a field study on the Australian Self Medication Industry. His work bridges marketing theory and practical applications, with a strong emphasis on understanding consumer decision-making processes and the impact of visual and digital elements in communication. Recent studies explore topics like the influence of buy-now-pay-later payment modes and impression management through eye-tracking in financial reporting. Ang has received a teaching award for MKTG204 Integrated Marketing Communications (2014). He actively engages in academic activities, including keynote talks on data-centric storytelling and behavioral finance technologies, and media contributions discussing financial report bias.

• Materials Science
• Machine Learning in Materials Discovery
• Phase-Change Materials
• +۷ مورد دیگر

Ichiro Takeuchi is an Affiliate Professor at the University of Maryland, specializing in materials science and engineering with a strong focus on autonomous materials discovery and machine learning integration. He leads research in phase-change materials, elastocaloric cooling systems, and high-throughput experimentation platforms. His work bridges theoretical physics, computational methods, and experimental material synthesis. Key research areas include developing AI-driven tools for materials design, optimizing phase-change-based photonic devices, and advancing sustainable cooling technologies through elastocaloric effects. He pioneers automated platforms like the JARVIS-Leaderboard and SANE optimization frameworks, enabling rapid discovery of novel materials for energy and electronics applications. Takeuchi’s contributions span interdisciplinary collaborations, integrating neutron diffraction, scanning probe microscopy, and multi-modal data analysis. His group’s innovations in reconfigurable photonics and combinatorial library screening have positioned him as a leader in next-generation materials engineering.

Hemangee Kapoorمشاهده پروفایل

استاد

• Computer Architecture
• Memory Systems
• Emerging Technologies
• +۴ مورد دیگر

Hemangee Kapoor is a full Professor in the Department of Computer Science and Engineering at Indian Institute of Technology Guwahati. She has made groundbreaking contributions to emerging nonvolatile memory (NVM) technologies and mentored numerous women in computing. Major Recognition: Recipient of the ACM India OCCW 2024 Award, sponsored by Google, for her technical and mentoring excellence. Research Impact: Developed novel approaches to address NVM challenges like write latency and cell longevity, with 40 journal and 74 conference publications. Educational Leadership: Graduated 8 PhD students and 40 masters students, while serving as Associate Dean of Students and Alumni Affairs at IIT Guwahati. Mentorship & Outreach: Organized ACM-W regional events in India's North-East and mentored undergraduates through summer internships. Her work bridges hardware innovation with systemic efforts to empower women in computing.

Baishakhi Mazumderمشاهده پروفایل

دانشیار

• Materials Science
• Semiconductor Technology
• Nanotechnology
• +۳ مورد دیگر

Baishakhi Mazumder is an Associate Professor in the Department of Materials Design and Innovation at the University at Buffalo. She specializes in materials science with a focus on advanced characterization techniques like atom probe tomography (APT) and machine learning-driven materials design. Her work spans semiconductor technologies, thin films, and quantum materials. Education: PhD in Physics and Materials Science, University of Rouen, France (2010) MS in Physics, University of Pune, India (2005) BS in Physics, University of Calcutta, India (2002) Research Interests: Dr. Mazumder explores atomic-scale dynamics in ultrawide bandgap semiconductors, machine learning for materials optimization, and structural-chemical evolution in thin films. Her group studies novel materials for energy applications, quantum devices, and advanced electronics. Techniques include APT, chemical vapor deposition (CVD), and computational modeling. Articles Trends: Recent work emphasizes data-driven approaches to superconductors, quantum materials, and thin film growth. Key themes include optimizing coercive fields in AlScN, enhancing NbN superconductivity, and unraveling phase transformations in AlGaO₃ films. Awards/Grants: No specific honors listed, but her CAREER award highlights sustained research impact. Labs/Teams: The Mazumder Group focuses on interdisciplinary materials innovation, combining experimental and computational methods.

Changhee Jungمشاهده پروفایل

دانشیار

• Compilers
• Computer Architecture
• Performance Optimization
• +۷ مورد دیگر

Changhee Jung is the Samuel D. Conte Associate Professor of Computer Science at Purdue University, Department of Computer Science. His research focuses on compilers and computer architecture with an emphasis on performance, reliability, and security. He joined Purdue in Fall 2019 after serving as an Assistant Professor at Virginia Tech (2013–2019). Prior academic roles include a post at ETRI (2005–2008) and internships at Google (2010–2012). Education: PhD in Computer Science from Georgia Institute of Technology (2013) under Prof. Santosh Pande. His work spans compiler-architecture co-design for intermittent computing, nonvolatile memory systems, and security frameworks like PeX for Linux kernel permission checks. Notable recognitions include the NSF CAREER Award (2018) and induction into the MICRO Hall of Fame (2021). Research interests include energy-efficient computing, fault resilience, and compiler-driven hardware optimizations. His lab, CompArch, emphasizes cross-layer solutions for performance, reliability, and security challenges. Recent projects include IPEX (ISCA 2025), Write-Light Cache (ISCA 2023), and DevFuzz (Oakland 2023). Awards: NSF CAREER, MICRO Hall of Fame, Memorable Paper Finalist (NVMW 2024), Best Student Paper Finalist (SC 2016), and multiple industry awards. Active in service roles, including program chair for LCTES 2020 and editorial roles for ACM journals. Teaching: Courses include CS 352 (Compilers), CS 502 (Compiling Systems), and advanced special topics. Supervised over 15 graduate students and postdocs, with alumni in academia and industry (e.g., Samsung, Intel, Xilinx).

Hassan Razaمشاهده پروفایل

مدرس ارشد

• Nanoelectronics
• Graphene Nanoelectronics
• Nanotechnology
• +۵ مورد دیگر

Hassan Raza is a Senior Lecturer in the Department of Electrical and Computer Engineering at Clemson University. He joined the faculty in 2020 and has previously taught at the University of Iowa, Rowan University, and Georgia Southern University. Dr. Raza focuses on nanoscale device modeling, simulation, and education, with expertise in graphene nanoelectronics, spintronics, and computational methods. Ph.D. in Electrical and Computer Engineering (2007), Purdue University M.S. in Electrical and Computer Engineering (2002), Purdue University M.S. in Operations Management (2016), University of Arkansas B.S. in Electrical Engineering (2001), University of Engineering and Technology, Lahore, Pakistan His research spans nanoscale materials and devices, emphasizing theoretical, computational, and experimental approaches. He has contributed to understanding transport phenomena in graphene systems, molecular electronics, and memory devices. Recent work involves electric-field modulation, misalignment effects, and bandgap engineering in 2D materials. Dr. Raza’s publications reveal a strong focus on graphene nanoelectronics, molecular memory, and low-voltage transistor design. Key subfields include Dirac fermion dynamics, nanoribbon properties, and quantum transport modeling. His 2019 textbooks on nanoelectronics and nanotechnology further solidify his educational contributions. Presidential Faculty Fellowship (University of Iowa, 2010) Old Gold Fellowship (University of Iowa, 2011) As Undergraduate Assessment Coordinator and Chair of the ECE Laboratory Committee, Dr. Raza shapes curriculum and lab infrastructure. He edited the 2012 book Graphene Nanoelectronics and developed interactive seminars for freshman nanotechnology education.

Roman Shugayevمشاهده پروفایل

استادیار

• Quantum Science
• Applied Electromagnetics
• Integrated Photonics
• +۳ مورد دیگر

Dr. Roman Shugayev is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Nevada, Las Vegas. He holds a Ph.D. in Electrical Engineering from Purdue University and a master's from Boston University. His research focuses on applied electromagnetics and quantum science, with expertise spanning quantum sensing, integrated photonics, plasmonics, and nanophotonics applications. His primary research investigates quantum emitters, photonic modulation, and advanced sensing techniques using nanomaterials. Recent work explores ultraviolet photonics in VLSI architectures, quantum communication networks, and metamaterial-based sensing platforms. Key innovations include strain-engineered photonic devices and metal-organic frameworks for quantum sensing enhancement. Publications demonstrate strong focus on quantum-photonic integration with applications in energy systems and communications. Trend analysis shows consistent development of chip-scale quantum devices, MEMS-based photonics, and novel sensing methodologies using nanomaterials.

Myungkoo Kangمشاهده پروفایل

استادیار

• Materials Science
• Optical Engineering
• Photonics
• +۴ مورد دیگر

Myungkoo Kang is an Assistant Professor in the Department of Ceramic Engineering at Alfred University. His research focuses on advanced materials science, particularly chalcogenide glasses and phase change materials, with applications in photonics, optical devices, and nanocomposite systems. He leads investigations into material reliability, thermal processing, and optoelectronic functionality. Key research areas include: Optical phase change materials (O-PCMs) for reconfigurable photonic systems Development of gradient refractive index (GRIN) materials for infrared optics Nanocomposite fabrication via photothermal and solution-based methods Failure mechanism analysis in chalcogenide materials He has pioneered work on electrically reconfigurable metasurfaces, low-loss optical systems, and novel material characterization platforms. His studies often involve collaborations across disciplines, addressing challenges in material stability, scalability, and functional integration.

• Memristor Technology
• Nanomaterials
• Neuromorphic Computing
• +۳ مورد دیگر

Sun Sun is an Adjunct Professor at the University of Waterloo, specializing in advanced memristor technologies and their applications in neuromorphic computing, biomedical engineering, and artificial intelligence. Their research focuses on developing novel memristor-based devices for sensor integration, energy harvesting, and bionic systems. Key research areas include organic nanomaterials, hybrid heterostructures (e.g., TiO2@MoO3, HfOx/FeOx), and biomaterials such as silk fibroin for implantable devices. Sun Sun explores memristor behaviors like negative differential resistance, resistive switching, and self-rectifying effects to enhance device functionality and scalability. Applications span healthcare (e.g., rapid tumor cell detection, follicular fluid monitoring), neuromorphic systems (e.g., artificial synapses, emotional perception circuits), and energy systems (soil-based energy harvesting). Their work often emphasizes multi-factor regulation of memristive properties and interdisciplinary integration with photonics, robotics, and sustainable materials. Collaborative projects include designing flexible and transparent memristor-based systems for wearable electronics and neuromorphic chips. Sun Sun’s contributions bridge fundamental device physics with real-world biomedical and AI applications, leveraging both organic and inorganic materials for next-generation smart technologies.

Mathieu Luisierمشاهده پروفایل

استاد

• Computational Nanoelectronics
• Device Physics
• Quantum Transport
• +۷ مورد دیگر

Prof. Mathieu Luisier is a Full Professor of Computational Nanoelectronics at ETH Zurich's Department of Information Technology and Electrical Engineering. He earned his PhD in 2007 from ETH Zurich, followed by postdoctoral research there and a role as Research Assistant Professor at Purdue University (2008–2011). His research focuses on nanoscale device modeling, including nanowire transistors, memristors, and 2D semiconductors, with a strong emphasis on quantum transport and high-performance computing. ERC Starting Grant (2013) SNSF Advanced Grant (2022) ACM Gordon Bell Prize (2019) His work integrates advanced simulation techniques like GW approximations and parallel algorithms to address challenges in nanoelectronics. He teaches courses on digital circuits and integrated systems, and leads research groups exploring next-generation devices for applications in quantum computing and neuromorphic systems.