جست‌وجوی استاد و پژوهشگر

Jiang Huمشاهده پروفایل

استاد

• VLSI Design Automation
• Hardware Security
• Machine Learning Applications
• +۳ مورد دیگر

Jiang Hu is a Professor in the Department of Electrical and Computer Engineering at Texas A&M University, holding the Eric D. Rubin '06 Endowed Professorship. He also serves as Co-Director of Graduate Programs and is affiliated with the Computer Science & Engineering department. His research focuses on VLSI design automation, machine learning applications, and hardware security. He has held roles as editor for IEEE Transactions on CAD and ACM Transactions on Design Automation, and chaired the 2012 ACM International Symposium on Physical Design. Education: B.S. in Optical Engineering (Zhejiang University, 1990), M.S. in Physics (1997), and Ph.D. in Electrical Engineering (University of Minnesota, 2001). He worked at IBM Microelectronics before joining Texas A&M in 2002. Research interests include energy-efficient VLSI circuits, on-chip communication fabrics, analog layout automation, and AI-driven EDA. Recent work emphasizes machine learning for design closure, privacy-preserving frameworks, and systolic array-based architectures. Awards: IEEE Fellow (2016) Humboldt Research Fellowship (2012) Multiple best paper awards at DAC, ICCAD, and ASPDAC Advising and grants: Leads initiatives like the SLICE project, NSF workshops on ML-EDA infrastructure, and serves as Editor-in-Chief of ACM TODAES since 2024. His work bridges academic research and industry applications in EDA and semiconductor design. Labs/Teams: Active contributor to open-source tools like ALIGN for analog layout generation and collaborations on machine learning for EDA commons.

• RF Integrated Circuits
• Analog and Digital IC Design
• Wireless Communication Systems
• +۳ مورد دیگر

Sayfe Kiaei is a Professor in the School of Electrical, Computer and Energy Engineering at Arizona State University (ASU), where he also directs the Connection One Center, an NSF I/UCRC Center. He holds the Motorola Chair in Analog and RF Integrated Circuits. Previously, he served as a professor at Oregon State University (1987–1993) and worked at Motorola’s Wireless Technology Center (1993–2001), contributing to wireless communications and broadband systems. Education: Ph.D. in Electrical and Computer Engineering from Washington State University (1987). Research focuses on RF/analog/digital integrated circuits, transceiver design, sensors, and power management. His work is funded by agencies like DARPA, NSF, DOE, and industrial partners. Key achievements include establishing two Industry-University Cooperative Research Centers (CDADIC and Connection One) and over 200 publications. He is an IEEE Fellow and has led technical committees for major conferences (RFIC, ISCAS, MTT). Industry collaborations span companies like Intel, Samsung, Texas Instruments, and Motorola, with expertise in 3G-4G wireless, bioelectronics, Bluetooth, GPS, and MEMS sensors. Awards include IEEE Fellow status (2002–present) and leadership roles in IEEE editorial and conference committees. Grants and projects include the NSF I/UCRC for Power Management Circuits, DARPA-funded research, and international initiatives like the Pakistan Centers for Advanced Studies in Energy. His lab develops cutting-edge technologies in full-duplex radios, MEMS-based sensors, and energy-efficient IC design.

Clyde Kruskalمشاهده پروفایل

دانشیار

• Parallel Computing
• Algorithms
• Computer Architecture
• +۳ مورد دیگر

Clyde Kruskal is an Associate Professor in the Department of Computer Science at the University of Maryland, College Park. His research focuses on parallel architectures, models, and algorithms. He earned a Ph.D. from New York University in 1981 and a bachelor’s degree from Brandeis University in 1976. His work includes foundational contributions to parallel computing, such as the read–modify–write concept in distributed systems. Kruskal’s research spans topics like interconnection networks, synchronization mechanisms, and algorithm design for parallel systems. Education: Bachelor’s Degree: Brandeis University, 1976 Master’s Degree: New York University (Courant Institute), 1978 Ph.D.: New York University (Courant Institute), 1981 Research Interests: Parallel computing architectures, parallel algorithms design, multiprocessor synchronization, interconnection networks, and computational geometry problems like graph coloring and visibility analysis. His work emphasizes theoretical foundations and practical implementations in parallel systems. Notable Contributions: Kruskal co-authored the book Problems With A Point: Exploring Math And Computer Science (2019), and his research includes foundational papers on parallel prefix operations, sparse matrix algorithms, and synchronization protocols. His publications span over three decades, reflecting sustained contributions to parallel computing theory and practice. Advising & Outreach: He has mentored students through programs like the Summer Combinatorial Algorithms REU at UMD, fostering undergraduate research in algorithm design and parallel computing.

Oliver Hohlfeldمشاهده پروفایل

استاد

• Network Security
• Network Measurements
• Internet Architecture
• +۹ مورد دیگر

Oliver Hohlfeld is a Professor at the University of Kassel, where he leads the Distributed Systems group. He previously held academic positions at Brandenburg University of Technology and RWTH Aachen University, and was a visiting scholar at the University of Wisconsin–Madison. His research focuses on network security, Internet measurements, and Quality of Experience (QoE). He completed his Ph.D. in Computer Science at TU Berlin under Anja Feldmann and holds a B.Sc. and M.Sc. from Darmstadt University of Technology. He also worked at Fraunhofer IGD on telemedical network architectures. His research adopts a data-driven approach, combining large-scale Internet measurements, user studies, and machine learning to understand and improve Internet performance and security. Key areas include DDoS detection, QUIC, HTTP/2, TLS deployment, and BGP analysis. He investigates how protocols like QUIC and HTTP/2 impact user experience and network efficiency, often through empirical studies of real-world deployments. His recent publications highlight a strong trend in network security and protocol analysis, with significant work on DDoS attacks, traffic ingress detection, and web consolidation. He also explores social media dynamics and censorship circumvention through user reviews. 2022 IETF/IRTF Applied Networking Research Prize Best of CCR (2021) for TLS 1.3 deployment study ACM Senior Member (2020) IEEE QoMEX 2019 Best Reviewer Award ACM IMC Community Contribution Award (2018) He has advised numerous Master’s and Bachelor’s students, primarily at RWTH Aachen, and has been a principal investigator in major projects such as AIDOS (AI-based DDoS mitigation), DFG SFB MAKI, COMTEX, and the EU-funded SSICLOPS. He actively serves on the technical program committees of top-tier conferences including SIGCOMM, NSDI, IMC, and CoNEXT, and is a frequent reviewer for leading journals in networking and systems. He leads the Distributed Systems group at the University of Kassel, which conducts research on Internet observability, secure infrastructures, and scalable networking solutions.

• Quantum Optics
• Atomic Physics
• Quantum Information Science
• +۵ مورد دیگر

Jacob P. Covey is an Assistant Professor in the Department of Physics at the University of Illinois at Urbana-Champaign (UIUC). He holds a Ph.D. in Physics from the University of Colorado Boulder (2017) and B.S. in Engineering Physics from the University of Wisconsin-Madison (2011). His research focuses on quantum optics, atomic physics, and quantum information science, particularly in quantum control of ultracold atoms and molecules, superradiance phenomena, and quantum networking. He leads the Covey Lab, which explores topics such as neutral atom quantum processors, Rydberg atom interactions, and precision measurement with optical clocks. Academic Positions: Assistant Professor at UIUC (2020–present); Richard Chace Tolman Postdoctoral Scholar at Caltech (2017–2020). Research highlights include pioneering work on Dicke superradiance in ordered atomic arrays and telecom-band quantum networking with Yb-171 atom arrays. He teaches undergraduate courses in mechanics, electromagnetism, thermodynamics, quantum physics, and quantum information. Scientific Awards: NSF CAREER Award (2024), Young Investigator Awards from AFOSR (2023) and ONR (2022), Springer Thesis Award (2018), and multiple fellowships including the Richard Chace Tolman Postdoctoral Fellowship (2017). His work bridges experimental and theoretical advances in quantum technologies, with contributions to quantum state control, precision metrology, and many-body quantum systems.

Tzu-Chien Hsuehمشاهده پروفایل

استادیار

• Analog and mixed-signal integrated circuits
• Wireline communication systems
• Data centers
• +۵ مورد دیگر

Tzu-Chien Hsueh is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of California, San Diego (UCSD), where he leads the Integrated Communication Circuits Lab. His research focuses on advanced CMOS and heterogeneous process technologies for high-speed, low-power communication systems, including transceiver design, silicon photonics, and data link optimization. He holds a B.S. and M.S. from National Taiwan University (1999-2001) and a Ph.D. from UCLA (2010). Before joining UCSD, he served as a Senior Research Scientist at Intel Labs (2010-2018), leading projects like 200Gb/s SerDes Links and 7nm CMOS Memory I/Os. He currently serves on the Technical Program Committee of IEEE CICC and IEEE SSCS mentoring programs. His honors include the IEEE JSSC Best Paper Award (2015) and multiple Intel recognitions. His lab emphasizes practical design innovations, theoretical analysis, and robust circuit implementations for applications in data centers, cloud computing, and broadband communication networks.

Wai Pang Ngمشاهده پروفایل

استاد

• Radio-over-Fiber
• Optical Communications
• Fiber Optic Sensors
• +۳ مورد دیگر

Wai Pang Ng is a Professor and Head of the Department of Mathematics, Physics and Electrical Engineering at Northumbria University. He holds a BEng (Hons) in Communications and Electronic Engineering from the University of Northumbria and a PhD in Electronic Engineering from the University of Wales, Swansea. His research focuses on radio-over-fiber systems, distributed fiber sensing, high-speed optical communications, and adaptive signal processing. Ng has held leadership roles in IEEE chapters and conferences, including chairing the IEEE UK&RI Communications Chapter (2011–2015) and serving as publicity chair for IEEE ICC 2015 and 2016. His research interests include innovative fiber optic sensor designs, acoustic wave devices for biomedical applications, and hybrid communication systems combining radio-over-fiber and free-space optics. Recent work emphasizes ultra-sensitive pressure/temperature sensors using microstructured fibers and acoustofluidic platforms for lab-on-a-chip applications. Ng has supervised seven PhD/MSc projects and actively contributes to standards development in optical communication systems. Ng’s publications span advanced sensor technologies, nonlinear compensation in optical systems, and turbulence-resistant free-space optical links. His work bridges academic research with practical applications in telecommunications, environmental monitoring, and healthcare diagnostics. Professional affiliations include IEEE technical committees (SPCE, TCGCC, ONTC) and guest editorships for IET Communications.

James Aspnesمشاهده پروفایل

استاد

• Distributed Algorithms
• Computer Science
• Randomized Algorithms
• +۵ مورد دیگر

James Aspnes is the Harold W. Cheel Professor of Computer Science at Yale University, specializing in distributed algorithms and randomized methods. He holds a PhD from Carnegie Mellon University and degrees from MIT. His research focuses on distributed systems, peer-to-peer networks, and sensor networks, emphasizing tools for efficient data management and fault-tolerance. Education: PhD (CMU, 1992), SM & SB (MIT, 1987) Affiliations: Yale since 1993, IBM Almaden Research Center (1992–1993) Research interests include distributed algorithms, randomization, and applications in biology and economics. Notable contributions include skip graphs, population protocols, and consensus algorithms. He has received the ACM-EATCS Dijkstra Prize (2020) and Dylan Hixon Prize (2000). Publications span distributed computing, algorithms, and cryptography. Recent work explores consensus protocols and privacy in population models. Grants include NSF awards totaling over $2M. Active in editorial roles (Algorithmica, Distributed Computing) and conference organization (PODC 2005, DCOSS 2007).

• Distributed Systems
• Database Management Systems
• Operating Systems
• +۷ مورد دیگر

Natacha Crooks Dr. Natacha Crooks is an Assistant Professor in the Department of Electrical Engineering and Computer Science (EECS) at UC Berkeley. Her research focuses on distributed systems, databases, and security, with a particular emphasis on consistency models, BFT protocols, and cloud computing. She is a founding member of the SkyLab and a core contributor to the Data Systems and Foundations Group at Berkeley. She holds a Ph.D. in Distributed Systems from the University of Texas at Austin (2019) and a BA in Computer Science and Law from the University of Cambridge (2012). Affiliations & Roles: Assistant Professor, UC Berkeley EECS Visiting Researcher at Azure Research, Security & Privacy Founding Member of SkyLab Member of Berkeley Center for Decentralized Intelligence Former Scientific Advisor at Improbable and Astronomer Research Interests: Her work bridges distributed systems and database research, addressing challenges in transactional consistency, fault-tolerant protocols, and cloud resource optimization. Key themes include: Designing scalable BFT consensus algorithms Secure multi-cloud storage solutions Optimizing distributed transaction processing Privacy-preserving distributed systems Awards & Recognition: Sloan Research Fellow (2025) NSF CAREER Award ACM SIGOPS Dennis M. Ritchie Doctoral Dissertation Award (2020) IEEE CS TCDE Early Career Award (2024) Teaching: Fall 2025: CS 294-282 (Research Culture and Community Norms), Wheeler 130. Industrial Collaboration: Prior roles include visiting researcher at Cornell University, Microsoft Research (DMX group), and Imperial College London. Industrial partnerships include work with Materialize, Astronomer, and Improbable.

Eby G. Friedmanمشاهده پروفایل

استاد

• VLSI Design
• Integrated Circuit Design
• Low Power CMOS
• +۴ مورد دیگر

Eby G. Friedman is a Professor in the Department of Electrical and Computer Engineering at the University of Rochester, where he has served since 1991 as director of the High Performance VLSI/IC Design and Analysis Laboratory. He concurrently holds a visiting professor position at the Technion - Israel Institute of Technology, directing the Technion Advanced Circuits Research Center (ACRC). His research specializes in high performance synchronous digital and mixed-signal microelectronic design with applications in high-speed portable processors and low-power wireless communications. Core focus areas include CMOS circuit design, clock/power distribution networks, interconnect synthesis, substrate noise mitigation, pipelining techniques, and 3-D integration methodologies. His work bridges theoretical frameworks with practical implementations in VLSI systems. Scientific Awards and Honors IEEE Fellow Distinguished Lecturer of the IEEE CAS Society Dr. Friedman has authored or edited 16 books and nearly 500 publications, establishing foundational contributions in clock distribution and power delivery networks. He maintains significant editorial leadership as Editor-in-Chief of the Microelectronics Journal, past Editor-in-Chief of IEEE Transactions on VLSI Systems, and serves on the editorial boards of the Journal of Low Power Electronics, Journal of VLSI Signal Processing, Journal of Low Power Application and Circuits, and Proceedings of the IEEE. His laboratory directs cutting-edge research in high-speed circuit design and 3-D integration architectures.

Kyojin Chooمشاهده پروفایل

استادیار

• Charge-domain circuits
• Sensor interfaces
• Energy converters
• +۴ مورد دیگر

Kyojin Choo is a Tenure Track Assistant Professor at the Swiss Federal Institute of Technology Lausanne (EPFL) in the School of Engineering , affiliated with the Mixed-Signal Integrated Circuits Lab (MSIC-LAB). He also holds teaching roles in Microengineering and Electrical and Electronics Engineering at EPFL. B.S. and M.S. in Electrical Engineering from Seoul National University (2007, 2009) Ph.D. in Electrical Engineering from the University of Michigan (2018) His research focuses on charge-domain analog/mixed-signal circuits , low-power sensor interfaces , and compact ADCs for IoT, wearables, and millimeter-scale systems. He has pioneered charge-injection cell techniques for energy-efficient circuits in energy management, sensor front-ends, and communication. His work emphasizes reducing power consumption to nanowatt levels while enabling ultra-compact designs. His recent publications highlight advancements in compact SAR ADCs , low-power MEMS accelerometers , millimeter-scale imaging systems , and ultra-low-power timing generators . His research integrates charge-domain circuit design with sensor interface optimization , energy harvesting , and high-speed link architectures . He holds over 20 US patents and has taught courses in Microengineering and Electrical Engineering at EPFL. His group (MSIC-LAB) addresses challenges in battery-free sensor design, power-constrained system scaling, and commercialization of wearables with unconventional form factors.

Jeffrey Krolikمشاهده پروفایل

استاد

• Signal Processing
• Sensor Array Processing
• Radar Systems
• +۴ مورد دیگر

Jeffrey Krolik is a Professor of Electrical and Computer Engineering at Duke University's Pratt School of Engineering. He holds a Ph.D. in Electrical Engineering from the University of Toronto (1987) and previously served as an Assistant Professor at Concordia University and Assistant Research Scientist at Scripps Institution of Oceanography. Ph.D. University of Toronto (1987) M.A. University of Toronto (1983) B.A. University of Toronto (1980) His research focuses on physics-based and statistical signal processing with applications in radar, sonar, microwave remote sensing, and medical imaging. Key projects include adaptive beamforming for ocean acoustic waveguides, aircraft height finding via HF radar, and motion-robust fMRI algorithms. Recent publications cover multipath mitigation in sonar arrays, vibrational radar backscatter communication, and CNN implementations for radar signal processing. His work spans underwater acoustics, urban radar tracking, and distributed sensor networks. He teaches advanced courses in sensor array signal processing, digital audio systems, and radar applications. His research has been supported through collaborations with institutions like Scripps and consulting roles with ONR, DARPA, and Air Force Rome Laboratories. Key contributions include waveguide invariant processing, matched-field beamforming, and novel approaches to radar clutter suppression in urban and maritime environments. His work integrates statistical signal processing with physical propagation models across diverse domains.

• Global Navigation Satellite Systems (GNSS)
• Avionics Systems
• Wireless Communication
• +۷ مورد دیگر

René Jr Landry is a full Professor in the Department of Electrical Engineering at École de technologie supérieure (ETS), Université du Québec, specializing in Global Navigation Satellite Systems (GNSS), avionics, and wireless communication technologies. His academic journey includes a B.Ing. from Polytechnique Montréal, M.Sc. from University of Surrey (UK), and Ph.D. from SupAréo in Toulouse. He maintains active research leadership through two key laboratories: LASSENA (Laboratory of Space Technologies, Embedded Systems, Navigation and Avionics) and LACIME (Communications and Microelectronic Integration Laboratory). His research spans critical aerospace navigation domains including GNSS signal processing, inertial navigation systems, software-defined radio for avionics, radio frequency interference mitigation, and indoor positioning technologies. Landry's work addresses real-world challenges in satellite navigation robustness, precision positioning in urban/denied environments, and next-generation avionic system security. His current projects focus on blockchain-enhanced IoT security, AI-driven GNSS disruption analysis, and adaptive RF front-ends for multi-band avionics applications. Analysis of his recent publications reveals strong emphasis on resilient positioning systems through multi-constellation integration (particularly Iridium-NEXT), blockchain applications for navigation security, and explainable AI techniques for GNSS signal quality assessment. His work increasingly bridges traditional navigation engineering with cutting-edge security and machine learning paradigms. 2014 Prix d'excellence du c.a. pour les services à la collectivité Landry has supervised over 100 graduate students across doctoral, master's, and research projects since 2005, with current supervision extending through Summer 2025. His research funding supports multiple industry partnerships focused on avionics certification, software-defined radio implementations, and next-generation navigation systems. The LASSENA laboratory under his leadership develops certified avionic products from open-source SDR platforms and advances multi-sensor fusion techniques for challenging navigation environments. His research infrastructure includes specialized facilities for GNSS signal simulation, avionics hardware testing, and multi-sensor integration. Current work emphasizes flight-tested validation of RF front-end technologies, blockchain-secured navigation data, and real-time interference mitigation systems for aviation applications.

Alexander Russellمشاهده پروفایل

استاد

• Cryptography
• Blockchain Protocols
• Quantum Computing
• +۴ مورد دیگر

Alexander Russell is a Professor of Computer Science and Mathematics at the University of Connecticut, serving as Director of Graduate Affairs in the School of Computing and Director of the UConn Voting Technology Research Lab. He holds a Ph.D. in Mathematics and an S.M. in Computer Science from MIT, alongside dual B.A. degrees in Mathematics and Computer Science from Cornell University. His research focuses on cryptographic protocols, blockchain security, quantum computing, algorithms, and election auditing. Key areas include consensus algorithms, complexity-theoretic cryptography, and applied cryptography in voting systems. Recent work emphasizes low-variance risk-limiting audits and adaptive security mechanisms for blockchains. Notable contributions span provably secure blockchain protocols (e.g., Ouroboros), election integrity methods, and smartphone-based depression prediction models. His articles address topics like settlement bounds in longest-chain consensus, Byzantine-resilient gossip protocols, and energy-efficient neighbor discovery in mobile networks. Russell advises on interdisciplinary projects at the Voting Technology Research Center and collaborates on grants involving quantum-resistant cryptography and healthcare analytics. His work bridges theoretical computer science with practical applications in secure systems and public infrastructure.

Forest Agostinelliمشاهده پروفایل

استادیار

• Deep Learning
• Reinforcement Learning
• Search Algorithms
• +۷ مورد دیگر

Forest Agostinelli is an Assistant Professor in the Department of Computer Science and Engineering at the Molinaroli College of Engineering and Computing, University of South Carolina, where he is also affiliated with the AI Institute. His research focuses on designing AI algorithms for pathfinding problems, integrating deep learning, reinforcement learning, heuristic search, and formal logic. He holds a Ph.D. in Computer Science from the University of California, Irvine, an M.S. from the University of Michigan, and a B.S. in Electrical and Computer Engineering from The Ohio State University. Research Overview : Agostinelli’s work emphasizes solving pathfinding problems in domains like robotics, theorem proving, and molecular optimization. His group develops explainable AI methods to enable collaboration between humans and machines. Key projects include DeepCubeA (solving the Rubik’s Cube via deep reinforcement learning) and neural activation function research. Funding & Awards : He has secured grants from NSF, NASA EPSCoR, and South Carolina’s ASPIRE and MADE programs. Notable awards include the NSF Graduate Research Fellowship and the Graduate Education for Minority Students Fellowship. Teaching : He teaches courses in Artificial Intelligence (CSCE 580) and Deep Reinforcement Learning and Search (CSCE 790), mentoring over 15 students at undergraduate and graduate levels. Labs & Collaborations : Active in AI-driven education and interdisciplinary projects, his lab contributes to tools like ALLURE for children’s learning and Bioinformatics platforms like CircadiOmics.