جست‌وجوی استاد و پژوهشگر

Chengmo Yangمشاهده پروفایل

استاد

• Embedded Systems
• Design Automation
• Computer Architecture
• +۶ مورد دیگر

Dr. Chengmo Yang is a Professor in the Department of Electrical and Computer Engineering at the University of Delaware, with a joint appointment. She received her PhD and MSc in Computer Science from the University of California, San Diego, and a BSc in Microelectronics from Peking University, China. PhD, University of California, San Diego MSc, University of California, San Diego BSc, Peking University, China Her research focuses on enhancing security, reliability, non-volatility, and energy efficiency in embedded systems, cyber-physical systems (CPS), and Internet-of-Things (IoT). She leads the Computer Architecture, Reliability, and Security (CARES) group and has authored over 70 peer-reviewed publications. Recent publications emphasize neural network accelerators, non-volatile memory (NVM) optimization, and security frameworks for embedded systems. Her work explores fault tolerance, wear leveling, and side-channel attack mitigation in NVM-based FPGAs, STT-RAM, and SSDs. National Science Foundation Career Award (2013) University of Delaware Mid-Career Faculty Excellence in Scholarship Award (2020) Best paper award at ICESS (2019) Three best paper nominations at DAC, DATE, and GLSVLSI (2019) Dr. Yang serves as Associate Editor for IEEE TCAD and ACM TODAES. She is the Diversity & Inclusion Representative for IEEE CEDA and has organized numerous conferences including Technical Program Chair for CODES-ISSS 2022. Her lab has hosted current and former students like Fanruo Meng (PhD candidate), Fateme Hosseini (Qualcomm), and Patrick Cronin (Intel), focusing on graduate-level research in hardware security and reliability.

Sumanta Acharyaمشاهده پروفایل

استاد

• Thermal and Fluid Sciences
• Computational Fluid Dynamics
• Turbulence Modeling
• +۵ مورد دیگر

Sumanta Acharya is a Professor in the Department of Mechanical Engineering at Illinois Tech's Armour College of Engineering. His career spans computational methods, experimental fluid mechanics, and combustion, with affiliations including ASME, AIAA, and ASTFE. Ph.D. in Mechanical Engineering, University of Minnesota (1982) M.S. in Mechanical Engineering, University of Minnesota (1980) B.S. in Mechanical Engineering, Indian Institute of Technology (1978) A leading expert in thermal and fluid sciences, Acharya focuses on gas turbine heat transfer, turbulence modeling, and advanced cooling systems. His work integrates Computational Fluid Dynamics (CFD) with experimental validation for applications in biofuels , hydrogen combustion , and phase change materials . Recent publications highlight innovations in Brayton cycle integration, impingement cooling, and aerothermal performance optimization. Awarded by ASME, AIAA, and LSU, his honors include the ASME Heat Transfer Memorial Award (2011) and ASME Fellow (1999). He has contributed to key committees, including the ASME Heat Transfer Division Executive Committee and the Department of Energy's University Turbine Systems Research program. Researcher to Know, Illinois Science & Technology Coalition (2022) ASME Dedicated Service Award (2019) AIAA Thermophysics Award (2015) Contact: sacharya1@illinoistech.edu | Phone: 312.567.3701

Mayank R. Mehtaمشاهده پروفایل

استاد

• Neurophysics
• Synaptic Plasticity
• Learning and Memory
• +۳ مورد دیگر

Mayank R. Mehta is a Professor at the University of California, Los Angeles (UCLA), holding joint appointments in the Departments of Physics & Astronomy, Neurology, and Neurobiology. He is a member of the Brain Research Institute and the W. M. Keck Center for Neurophysics at UCLA. His research bridges experimental and theoretical neuroscience, focusing on how neuronal networks encode space-time, the role of brain rhythms in learning and memory, and the impact of sleep and virtual reality on neural dynamics. His recent publications highlight breakthroughs in understanding hippocampal spatiotemporal selectivity, dendritic activity during behavior, and the causal influence of visual cues on memory neurons. Notable findings include the discovery that dendrites generate ten times more spikes than neuronal cell bodies and the modulation of hippocampal theta rhythms in virtual reality. Research Themes: Neurophysics of spatial-temporal coding Dendritic contributions to learning Virtual reality and brain plasticity Neural oscillations in memory consolidation Key Collaborators: Bert Sakmann (Max Planck Florida Institute) Thomas Hahn (Bernstein Center Heidelberg/Mannheim) Maryam Ghorbani (UCLA) Mehta's lab at UCLA trains graduate and postdoctoral researchers in cutting-edge techniques combining hardware development, electrophysiological recordings, and biophysical modeling. His work has significant implications for treating learning and memory disorders like Alzheimer's disease.

Daniel Abadiمشاهده پروفایل

استاد

• Database System Architecture
• Distributed Database Systems
• Scalable Transaction Processing
• +۳ مورد دیگر

Daniel Abadi is the Darnell-Kanal Professor of Computer Science at the University of Maryland, College Park, with an appointment in the University of Maryland Institute for Advanced Computer Studies. He leads the Data Systems Lab at Maryland (DSLAM) and has made significant contributions to database system architecture and implementation, particularly in scalable and distributed systems. Prof. Abadi's research focuses on database system architecture, especially at the intersection with scalable and distributed systems. He is best-known for the development of the storage and query execution engines of the C-Store (column-oriented database) prototype, which was commercialized by Vertica and eventually acquired by Hewlett-Packard, and for his HadoopDB research on fault tolerant scalable analytical database systems which was commercialized by Hadapt and acquired by Teradata. His current work includes deterministic distributed systems like Calvin and SLOG, which provide strictly serializable, low-latency, geographically replicated database transactions. Analysis of his recent publications reveals a strong focus on modern database challenges including transaction processing, distributed systems architecture, data mesh concepts, schema evolution, and IoT data management. His work consistently addresses the tension between consistency, availability, and performance in distributed database systems, with recent emphasis on moving beyond traditional two-phase commit protocols and exploring novel approaches to data architecture like data mesh. ACM Fellow Sloan Research Fellowship Churchill Scholarship NSF CAREER Award VLDB Best Paper Award Two VLDB Test of Time Awards (for C-Store and HadoopDB) 2008 SIGMOD Jim Gray Doctoral Dissertation Award 2013-2014 Yale Provost's Teaching Prize 2013 VLDB Early Career Researcher Award PhD dissertation advisor for Alexander Thomson and Jose Falerio, whose dissertations won SIGMOD Jim Gray Doctoral Dissertation Awards in 2015 and 2020 respectively Prof. Abadi has advised multiple PhD students, including Alexander Thomson and Jose Falerio, both of whom received the prestigious SIGMOD Jim Gray Doctoral Dissertation Award. His research has been supported by numerous grants including NSF funding for projects like SLOG. He maintains an active presence in the database community through his widely-read blog DBMS Musings and through service on program committees for major conferences including SIGMOD, VLDB, and CIDR. He leads the DSLAM research group at the University of Maryland, which focuses on cutting-edge database system research with strong industry connections and practical impact.

Mark Leeمشاهده پروفایل

استاد مدعو

• Human Factors Engineering
• Healthcare Safety
• Data Analytics in Manufacturing
• +۳ مورد دیگر

Mark Lee is an Adjunct Professor in the People Analytics department at NYU’s Tandon School of Engineering, specializing in Technology Management and Innovation. He holds a Ph.D. in Engineering Psychology from Georgia Institute of Technology (1996). Currently, he serves as Head of Research, Analytics, and Business Development at UL ComplianceWire, focusing on pharmaceutical and medical device manufacturing training. His research leverages large datasets to improve healthcare safety through regulatory compliance and best practices. Courses taught include Human Factors Engineering, Workplace Design, and Predictive Analytics. Education: Ph.D. in Engineering Psychology, Georgia Tech (1996) Key Roles: Adjunct Professor, Head of Research at UL ComplianceWire Research Focus: Human Factors, Training Systems Design, Healthcare Compliance His work spans auditory display systems for aviation (e.g., 3D audio cockpit interfaces) and ergonomic design for industrial products. Recent projects emphasize data-driven solutions for regulatory challenges in life sciences. Publications highlight studies on visual search strategies, age-related cognitive performance, and application of signal detection theory in decision-making. He actively collaborates with industry and government entities, exemplified by the FDA-UL Cooperative Research Agreement.

Yildiz Bayazitogluمشاهده پروفایل

استاد

• Thermal Sciences
• Heat Transfer
• Nanotechnology
• +۴ مورد دیگر

Dr. Yildiz Bayazitoglu is the Harry S. Cameron Professor of Mechanical Engineering and Professor of Materials Science and NanoEngineering at Rice University since 1996. She joined Rice in 1977 and has held prior roles as an assistant professor at Middle East Technical University (1973–74) and a visiting assistant professor at the University of Houston (1975–76). Her education includes a B.S. from Middle East Technical University (1967), and M.S. and Ph.D. from the University of Michigan (1969 and 1974). Her research focuses on convective heat transfer with phase change , micro/nano-scale heat transfer , and radiation heat transfer . Key areas include thermal modeling of biomedical systems, containerless materials processing, and fuel cell design. She has pioneered work on nanofluids, interfacial thermal resistance, and radiation shielding for aerospace applications. Dr. Bayazitoglu has published over 200 technical papers and holds patents in thermal engineering. She authored two heat transfer textbooks and serves as Editor-in-Chief of the International Journal of Thermal Sciences . Her honors include ASME’s Heat Transfer Memorial Award, AAAS and AIAA Fellowships, and membership in the Turkish Academy of Sciences. Education: B.S., Middle East Technical University (1967) M.S., University of Michigan (1969) Ph.D., University of Michigan (1974) Leadership Roles: Former Vice-President of the International Center for Heat and Mass Transfer (2019–2021) Member of Turkish Academy of Sciences Energy Sources Committee (2017–2018) Her work bridges thermal engineering with biomedical, aerospace, and materials science applications, emphasizing practical solutions to complex thermal challenges.

H.-S. Philip Wongمشاهده پروفایل

استاد

• Nanotechnology
• Semiconductor Technology
• Solid-State Devices
• +۵ مورد دیگر

H.-S. Philip Wong is the Willard R. and Inez Kerr Bell Professor in the School of Engineering at Stanford University, where he has been since 2004. He holds the rank of Professor in the Department of Electrical Engineering and serves as the Director of the Stanford Nanofabrication Facility. Prior to Stanford, he spent 16 years at IBM’s T.J. Watson Research Center and served as Vice President of Corporate Research at TSMC (2018–2020), remaining as Chief Scientist in an advisory role thereafter. Leadership roles include founding the Stanford SystemX Alliance and leading the Microelectronics Commons AI Hardware Hub funded by the CHIPS Act. Research focuses on nanotechnology, semiconductor devices, and next-generation computing architectures, including carbon nanotube electronics, 3D integration (N3XT/MOSAIC), and neuromorphic computing. Awarded IEEE Fellow (2001), the IEEE Andrew S. Grove Award, and the J.J. Ebers Award for contributions to electron devices. His work spans device physics, fabrication, and system integration, with over 600 publications. Key contributions include advancements in phase-change memory, carbon nanotube transistors, and compute-in-memory systems. He advises numerous students and collaborates with industry through initiatives like the Stanford Non-Volatile Memory Technology Research Initiative. Recent efforts emphasize AI hardware acceleration, cryo-CMOS for quantum computing, and scalable memory architectures. His lab innovations include CellChips for synthetic biology and hyperdimensional computing using 3D RRAM.

• Numerical Modeling
• Computational Simulation
• Materials Science
• +۵ مورد دیگر

Assoc Prof Ng Teng Yong is an Associate Professor at the School of Mechanical & Aerospace Engineering (NTU), specializing in numerical modeling and simulation. With a background as Research Manager at A*STAR Institute of High Performance Computing, his work spans materials science, nanotechnology, and aerospace engineering. Current focus on graphene-based desalination membranes Expertise in molecular dynamics simulations Investigates nanoscale fluid mechanics and structural dynamics Recent publications highlight advancements in energy-efficient electrodialysis, smart robotics, and nonlinear vibration analysis. His interdisciplinary approach integrates computational methods with experimental validation in additive manufacturing and soft material mechanics.

David Melcherمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Perception
• Attention
• +۷ مورد دیگر

David Melcher is Professor of Psychology and Program Head in Psychology at New York University Abu Dhabi (NYUAD), where he also serves as a Global Network Professor. He is affiliated with the Division of Science and leads the Perception and Active Cognition Lab, focusing on the integration of perception, attention, memory, and action within a cognitive neuroscience framework. PhD in Psychology and Cognitive Science, Rutgers University (2001) Former researcher and professor in Italy and the UK Current leadership: Program Head, Psychology, NYUAD David Melcher's research centers on cognitive neuroscience , particularly how perception, attention, working memory, eye movements, and self-motion interact to shape cognition and behavior. His lab emphasizes active cognition —the idea that perception is not passive but dynamically shaped by action, context, and goals. He investigates how temporal dynamics in neural processing organize perceptual experiences and guide decision-making. His work spans both healthy and clinical populations, exploring individual differences in spatial and temporal processing across the lifespan. The 15 most recent publications reflect a consistent focus on temporal organization in cognition , perception-action coupling , and neural mechanisms of attention and memory . Keywords across these works include cognitive neuroscience, perception, and neuroimaging, with subfields ranging from eye movement research and neural synchrony to computational modeling and clinical neuropsychology. Collectively, they demonstrate a trajectory toward integrative models of brain function that bridge behavioral, neuroimaging, and computational approaches. Among his notable recognitions is the Distinguished Scientific Award for Early Career Contribution to Psychology from the American Psychological Association (2011), highlighting the early impact of his work in cognitive neuroscience. Distinguished Scientific Award for Early Career Contribution to Psychology, APA (2011) David Melcher has advised numerous students through capstone projects in psychology and computer science, fostering interdisciplinary research at the intersection of cognitive science and technology. His research has been generously supported by major funding agencies including the European Research Council , the US National Institutes of Health , the Italian Ministry of Research and Education , and the Chinese Ministry of Foreign Expert Affairs . He also contributes to the academic community as a member of the editorial boards of Journal of Vision , Psychonomic Bulletin & Review , Perception , and iPerception . He leads the Perception and Active Cognition Lab at NYUAD, which employs a multidisciplinary approach combining behavioral experiments, neuroimaging (fMRI, EEG, MEG), eye-tracking, computational modeling, and clinical assessments. The lab’s research aims to understand how the brain constructs stable percepts from dynamic sensory input, particularly during active engagement with the environment.

• Nuclear Magnetic Resonance (NMR)
• In vivo imaging
• MRI pulse sequence development
• +۷ مورد دیگر

Professor Guy Williams is a leading academic at the University of Cambridge with a focus on imaging science and clinical neurosciences, affiliated with Downing College and the Wolfson Brain Imaging Centre . Holding a PhD in Physics from his initial Natural Sciences degree, he specializes in nuclear magnetic resonance (NMR) and MRI techniques for brain imaging. Education: BA, PhD in Physics His research centers on non-invasive imaging of brain structure and function, particularly in traumatic brain injury (TBI) and dementia. His work involves developing novel MRI pulse sequences and advanced data analysis algorithms, including AI-based diagnostic tools. He leads studies on white matter integrity post-trauma, longitudinal dementia assessment, and applications of MRI in disorders of consciousness and addiction. Recent publications highlight collaborations in traumatic brain injury outcomes, AI-guided dementia prediction, and neuroimaging of post-COVID cognitive deficits. His team's work on ultra-high field laminar fMRI and distortion correction methods has advanced clinical neuroscience applications. Key techniques include diffusion tensor imaging (DTI), 7 Tesla MRI, and positron emission tomography (PET/MR). His research spans from basic NMR physics to clinical translation, with a strong emphasis on multi-site studies and real-world diagnostic implementation.

Jeehwan Kimمشاهده پروفایل

دانشیار

• Nanotechnology
• Materials Science
• Electronics
• +۷ مورد دیگر

Jeehwan Kim is an Associate Professor in Mechanical Engineering and Materials Science and Engineering at MIT. He joined the Mechanical Engineering faculty in 2015 and became a joint faculty member in DMSE in 2016. His research focuses on nanotechnology for computing/electronics, electronic/photonic devices, neuromorphic computing, and heterogeneous integration. He holds over 100 patents from IBM and has received awards like the Samsung Fellow (2022) and DARPA Director’s Award (2021). Education : BS (Hongik University), MS (Seoul National University), PhD (UCLA), all in Materials Science and Engineering. Research Interests : Kim’s group innovates in 2D materials, remote epitaxy, neuromorphic systems, and next-gen electronics. Key areas include monolithic 3D integration, bioelectronic devices, and energy-efficient semiconductors. His work bridges material physics with practical device applications. Awards : Samsung Fellow (2022) DARPA Director’s Award (2021) Young Faculty Award (2019) IBM Faculty Award (2016) IBM Master Inventor (2012) Labs/Teams : Jeehwan Kim Research Group at MIT, focusing on advanced material synthesis and device engineering. Active in cross-disciplinary projects involving AI and semiconductor innovation.

• Self-organized criticality
• Neuronal network dynamics
• Excitation/Inhibition balance
• +۵ مورد دیگر

Anna Levina is an Assistant Professor for Computational Neuroscience at the University of Tübingen , affiliated with the Department of Computer Science under the Faculty of Science. Her research focuses on the self-organization of neuronal activity, critical dynamics in neural networks, and the excitation/inhibition balance in cortical circuits. Current positions: Assistant Professor (since 2018), Group Leader (2017-2018), Equality Officer (Computer Science) Previous roles: IST Fellow (2015-2017), Associated Researcher (2011-2015), Postdoc/PI (2011-2015), Postdoc (2008-2011) Her research integrates mathematical modeling , statistical physics , and computational neuroscience to study criticality phenomena, neural avalanches, and adaptive network dynamics. Key interests include: Self-organized criticality in neural systems Excitation/Inhibition balance mechanisms Network topology and dynamics Timescale analysis in neural processing Stochastic modeling of neural activity Recent publications reveal trends in understanding critical dynamics across biological and artificial networks, with applications to memory systems, sensorimotor integration, and disease modeling. She has received recognition as an IST Fellow .

Jing Liمشاهده پروفایل

دانشیار

• Computer Architecture
• Compiler Design
• Distributed Systems
• +۷ مورد دیگر

Dr. Jing Li is an Associate Professor and Eduardo D. Glandt Faculty Fellow at the University of Pennsylvania , holding dual appointments in the Electrical and Systems Engineering and Computer and Information Science departments. As co-director of the CyberSavvy nationwide security research center and director of the Penn Computational Intelligence Lab (PennCIL) , she pioneers innovations in non-von Neumann computing paradigms. Her research spans post-CMOS technologies, in-memory computing, and hardware-software co-design for security and AI applications. PhD in Computer Engineering, Purdue University (2009) BSc in Electrical Engineering, Shanghai Jiaotong University (2004) Research Focus: Dr. Li's work addresses fundamental challenges in computer systems across the stack. Key areas include: In-Memory Computing: Liquid Silicon architecture combining RRAM with silicon CMOS through monolithic 3D integration Security Engineering: Transforming computer security from "Art" to formal "Engineering" discipline within CyberSavvy Virtualization: Cloud FPGA abstraction layers decoupling compilation from runtime resource management Graph Analytics: Degree-aware optimization techniques for massive-scale graph processing Deep Learning Systems: Roofline model extensions for FPGA-based CNN acceleration Scientific Impact: Awarded DARPA Young Faculty Award , NSF CAREER Award , and IBM CEO Milestone Award , her team has achieved world records in energy-efficient computing (ENIAD supercomputer). With 46 U.S. patents and over 80 publications, she leads ecosystem development for emerging computing architectures through initiatives like the open-source MEG simulation platform . Community Leadership: Dr. Li serves on program committees for flagship conferences ( ISCA , FPGA Symposium ), chairs the International Memory Workshop , and contributes to the MLsys conference's inaugural committee. She actively mentors through multiple PhD openings and industry collaborations.

Katrina Morgan-Innesمشاهده پروفایل

مدرس

• Energy Harvesters
• Flexible and Wearable Technologies
• 2D Materials
• +۳ مورد دیگر

Katrina Morgan-Innes is a Lecturer (Assistant Professor) at the School of Electronics and Computer Science, University of Southampton. Her research focuses on advanced flexible materials for energy harvesting and storage, leveraging semiconductor industry fabrication techniques to develop wearable thermoelectric devices and next-generation batteries. She leads the Morgan Materials and Devices for Energy (MADE) research group and a £220k EPSRC New Horizons grant (Smart Cloth). Her work emphasizes commercial scalability and integration of 2D materials with flexible substrates. Education: MPhys in Physics (University of Sussex, 2011), CASE Award PhD in Electronics and Computer Science (University of Southampton, 2016–2022). Previous roles include Photonics Development Engineer at the AIM Photonics Programme (SUNY) and Visiting Fellow at the Optoelectronics Research Centre. Research interests include energy harvesters, flexible wearables, 2D materials, and nanofabrication. She has pioneered scalable manufacturing methods for photonic and energy devices and contributed to chalcogenide material applications. Her research group aims to create fully flexible systems enabling integrated sensing, power, and communication on lightweight platforms. Key grants include EPSRC funding for wearable thermoelectric generators and collaborations like the ChAMP/WAFT-funded projects on flexible ion sensors and 3D nanophotonics. She has published in high-impact journals (e.g., ACS Applied Materials and Interfaces , npj 2D Materials and Applications ) and conferences, focusing on thermoelectric materials, photonic heterostructures, and scalable manufacturing. Awards: UNSW Women in Engineering Visiting Fund (2019), Top 100 Physics Paper (2020), Outreach Engagement Award (2016) Labs/Teams: Morgan MADE Group, Collaboration with Optoelectronics Research Centre and Zepler Institute Advocacy: Chair of WiSET+ (University-wide STEM+ Equality Committee), founder of Early Career Researcher Forum

• Ultrafast Phenomena
• Photoinduced Phase Transitions
• Spin-Crossover Materials
• +۷ مورد دیگر

Eric Collet is a University Professor and Head of Department at the Institute of Physics of Rennes (IPR), a joint research unit of CNRS and Université de Rennes. His work centers on ultrafast photoinduced phase transitions, spin-crossover materials, and the control of functional materials using light and THz excitation. He leads a dynamic research team and is deeply involved in international collaborations, particularly through the IM-LED International Laboratory with Japan. University: University of Rennes School: Institute of Physics of Rennes Department: Department of Materials and Light Academic Rank: Professor Email: eric.collet@univ-rennes.fr Professor Collet's research explores the ultrafast dynamics of molecular and condensed matter systems, especially those exhibiting multistability and photoresponsiveness. His work combines femtosecond optical and X-ray techniques to probe structural and electronic changes at atomic scales. Key areas include spin-crossover phenomena, photomagnetism, ferroelasticity, and nonlinear phononics. He investigates how light can trigger cooperative responses in materials, leading to persistent phase transitions with applications in photonics and memory devices. The recent publications of Eric Collet reveal a strong focus on ultrafast structural dynamics, photoinduced charge and spin transitions, and the coupling of electronic states with lattice distortions. His team frequently employs advanced X-ray methods at large-scale facilities like ESRF and LCLS. The research spans from fundamental quantum dynamics to applied materials science, with recurring themes in symmetry breaking, cooperative switching, and room-temperature photoresponse in molecular systems. Scientific awards and recognitions include: CNRS Silver Medal (2020) Louis Ancel Prize, French Physical Society Hot Paper selection in PCCP (2019) Very Important Paper recognition in Eur. J. Inorg. Chem. (2019) News & Views feature in Nature Chemistry (2020) Eric Collet actively mentors PhD students and postdoctoral researchers, and has supervised numerous publications in top journals. He has led major scientific initiatives such as the UCM2018 symposium and JMC2021 conference. His research is supported by grants from ANR, CNRS, and the Institut Universitaire de France. He collaborates extensively with institutions in France, Japan, and beyond. His research is conducted primarily within the Department of Materials and Light at the Institute of Physics of Rennes. He co-directs the IM-LED International Laboratory with Prof. Shin-ichi Ohkoshi (University of Tokyo) and collaborates with groups in Bordeaux, Lebanon, and Japan. His lab specializes in time-resolved X-ray diffraction, ultrafast spectroscopy, and nonlinear optical control of materials.