جستجوی استاد راهنمای دانشگاهی

David J. Loveمشاهده پروفایل

استاد

• Communication theory
• Information theory
• MIMO wireless systems
• +۶ مورد دیگر

David J. Love is the Nick Trbovich Professor of Electrical and Computer Engineering at Purdue University's Elmore Family School of Electrical and Computer Engineering. He leads the Purdue NextG Center for Communications and Sensing (XGC) and holds Fellowships from IEEE, AAAS, and NAI. His research focuses on 6G systems, MIMO communications, millimeter-wave and terahertz technologies, and security in wireless networks. He has authored over 150 papers and holds 32 patents, with notable contributions to codebook-based precoding used in 4G/5G standards. Education: B.S. (Highest Honors), M.S.E., and Ph.D. in Electrical Engineering from The University of Texas at Austin (2000–2004). Research Interests: Communication theory, feedback systems, massive MIMO, integrated sensing and communications (ISAC), and wireless security. His work bridges theoretical advancements with practical implementations in 5G/6G systems. Publications Trends: Recent work emphasizes federated learning for edge networks, 6G architecture, and secure wireless systems. Key themes include privacy-preserving machine learning, hybrid satellite-terrestrial networks, and waveform design for ISAC. Awards: Includes the IEEE Communications Society Bennett Prize (2024), NAI Fellow (2023), AAAS Fellow (2022), and multiple best paper awards. Recognized as a Thomson Reuters Highly Cited Researcher (2014–2015). Advising & Grants: Advised over 30 Ph.D. students. Current leadership roles include Director of the NextG Center and Co-Lead of NSF IoT4Ag. Active in grants related to IoT, precision agriculture, and spectrum intelligence. Labs/Teams: Leads the NextG Center, involved in NSF Engineering Research Centers (ERCs), and collaborates with industry on applied wireless research.

Gabriele La Naveمشاهده پروفایل

استاد پژوهش

• Theoretical Physics
• Condensed Matter Physics
• Mathematical Physics
• +۶ مورد دیگر

Dr. Gabriele La Nave is a Research Professor in the Department of Mathematics at the University of Illinois, affiliated with the College of Liberal Arts & Sciences. His research bridges theoretical physics and mathematics, focusing on geometric flows, quantum matter, and nonlocal field theories. He explores critical phenomena in strongly correlated electron systems, geometric structures in Kähler manifolds, and holographic dualities connecting gravity and quantum field theories. Key research themes include the stability of strongly coupled fixed points in Mott insulators, non-Fermi liquid behavior, and the interplay between symmetry breaking and topological order. His work on Kähler-Einstein metrics and geometric flows contributes to foundational problems in differential geometry. Publications span topics from fractional electromagnetism to Lovelock gravity in holographic contexts, reflecting a synthesis of mathematical rigor and physical insight. Dr. La Nave’s articles highlight novel frameworks for understanding anomalous dimensions, entanglement entropy, and boundary non-locality in quantum systems. His contributions bridge gaps between pure mathematics (e.g., moduli spaces, geometric analysis) and high-energy physics (e.g., conformal field theories, holography), positioning him at the intersection of these disciplines.

• Cochlear modeling
• Speech perception
• Auditory neurophysiology
• +۷ مورد دیگر

Dr. Jont B. Allen is a Professor of Electrical and Computer Engineering at the University of Illinois Urbana-Champaign (UIUC), affiliated with the College of Engineering. He holds a PhD from the University of Pennsylvania (1970) and has had a distinguished career spanning 32 years at Bell Labs/AT&T Labs before joining UIUC in 2003. His research focuses on cochlear modeling, speech perception, audiology, and signal processing. He has authored over 50 sole-authored journal articles and holds 20+ US patents in hearing aid technology and diagnostics. Education: PhD, Electrical Engineering, University of Pennsylvania, 1970 MS, Electrical Engineering, University of Pennsylvania, 1968 BS, Electrical Engineering, University of Illinois Urbana-Champaign, 1966 Research Interests: Dr. Allen’s work bridges engineering and biology, emphasizing understanding human speech recognition mechanisms, cochlear function, and improving hearing aid signal processing. His projects include noninvasive diagnostic methods for middle ear disorders, speech perception in noise, and the link between hearing deficits and reading disabilities in children. Publications & Awards: He has published extensively on auditory models, signal processing, and clinical audiology. Notable awards include IEEE Fellow (2009), Phonak Faculty Award (2007/2008), and the IEEE Third Millennium Award (2000). He has also contributed to major conferences like ICASSP and editorial boards. Teaching & Mentoring: Dr. Allen teaches courses on mathematical physics, speech processing, and audio engineering. He oversees a productive research group at UIUC, mentoring students in projects like consonant perception analysis, middle ear modeling, and hearing aid algorithm development. His group has collected large speech perception datasets, leading to impactful publications and collaborations with institutions like Columbia University and the University of Calgary. Labs & Collaborations: His work leverages interdisciplinary tools, including acoustic reflectance measurements, DPOAE analysis, and computational models of the auditory system. Key collaborations include projects with the Beckman Institute, the Speech and Hearing Science Department at UIUC, and industry partners like Mimosa Acoustics.

Federica Agostiniمشاهده پروفایل

استادیار

• Theoretical Chemistry
• Quantum Dynamics
• Nonadiabatic Processes
• +۳ مورد دیگر

Federica Agostini is an Assistant Professor of Theoretical Chemistry at the Institut de Chimie Physique of the University Paris-Saclay, France, since 2016. Her research focuses on quantum dynamics, nonadiabatic processes, and electronic structure calculations, particularly in photochemical reactions and molecular dynamics. She employs advanced computational methods such as exact factorization, coupled-trajectory approaches, and density functional theory to study systems like retinal chromophores and conical intersections. Her work bridges quantum and classical mechanics, addressing challenges in non-Born-Oppenheimer regimes and environmental effects on molecular processes. Key areas include decoherence mechanisms, electronic-vibrational coupling, and the development of benchmark protocols for molecular dynamics simulations. Her projects are supported by ANR and CNRS funding, emphasizing cutting-edge computational tools for understanding ultrafast phenomena in chemistry and physics.

Yoonseok Leeمشاهده پروفایل

استاد

• Low Temperature Physics
• Quantum Fluids and Solids
• Superfluid Helium
• +۲ مورد دیگر

Yoonseok Lee is a Professor in the Department of Physics at the University of Florida, where he has served since 2001. He earned his PhD from Northwestern University in 1997 and subsequently held postdoctoral positions at Stanford University and Northwestern University. His research focuses on low-temperature quantum phenomena, particularly in superfluid helium systems and nanoscale electromechanical oscillators. Education: PhD in Physics, Northwestern University (1997) MS in Physics, Seoul National University (1987) BS in Physics, Seoul National University (1985) Research Interests: Professor Lee investigates quantum fluids and solids using advanced cryogenic techniques. His work explores acoustic/magnetic properties of liquid/solid helium-3, quantum turbulence, and the behavior of low-dimensional conductors at ultralow temperatures. He develops microelectromechanical (MEMS) devices for precision measurements in quantum systems. Publication Trends: His recent articles demonstrate a focus on quantum turbulence phenomena and microelectromechanical sensor development for superfluid characterization. Research spans experimental studies of phase transitions in confined quantum fluids, hydrodynamic behavior in nanostructured materials, and novel measurement techniques for ultralow-temperature systems. Awards and Honors: APS Fellow (2013) University Term Professor (2018-2021) Colonel Allan R. and Margaret G. Crow Term Professor (2014-2015) Alfred P. Sloan Research Fellowship (2004-2006) NSF Career Award (2003) AKPA Outstanding Young Researcher (2002) Leadership and Service: Director of the Microkelvin Laboratory (2004-2007), President of the Association of Korean Physicists in America (2021-2023), and recipient of multiple NSF grants supporting quantum fluid research. Current projects include NSF-funded investigations of quantum turbulence and superfluid dynamics.

Jon Harrisonمشاهده پروفایل

دانشیار

• Mathematical Physics
• Quantum Mechanics
• Quantum Chaos
• +۱ مورد دیگر

Jon Harrison is Associate Professor of Mathematics at Baylor University's College of Arts & Sciences. He holds a Ph.D. in Mathematics from the University of Bristol (2001) and previously held positions at Universität Ulm and Texas A&M University. Research specializes in quantum mechanics on graphs, spectral statistics, and quantum chaos, with grants from Simons Foundation and NSF. Publications focus on spectral properties of quantum systems, using graph theory to model quantum phenomena. Recent works analyze orbit dynamics and spectral determinants. Supervised doctoral students include Victoria Hudgins and Erica Oldaker. Awards recognize contributions to mathematical physics through substantial research funding.

Yuede Jiمشاهده پروفایل

استادیار

• High-Performance Computing (HPC)
• Security
• Graph AI
• +۵ مورد دیگر

Dr. Yuede (YJ) Ji is an Assistant Professor in the Department of Computer Science and Engineering at the University of Texas at Arlington (UTA), leading the Graph Lab. His research focuses on graph-centric security, learning, and computing, intersecting High-Performance Computing (HPC), Security, Graph AI, and Graph Analytics. Prior to UTA, he was an Assistant Professor at the University of North Texas (2021–2024). He earned his Ph.D. from George Washington University in 2021 under Dr. Howie Huang. His work has been recognized with awards such as the Best Paper Award at NPC 2014 and the Best Poster Award at SMCDC 2023. Education: Ph.D., Computer Engineering, George Washington University (2021) M.S., Computer Science & Technology, Jilin University (2015) B.E., Software Engineering, Jilin University (2012) Research Interests: Graph-centric security, HPC, Graph AI, malware detection, and privacy-preserving systems. His research is funded by NSF, DOE, and Google. Grants & Fundings: NSF SHF: Small: An Accelerated Computation Architecture (2024–2027) NSF CICI: Secure Containers in HPC Infrastructure (2023–2026) Students & Advising: Advising Ph.D., M.S., and undergraduate students. Current advisees include Chaoqun Li, Emmanuel Emakhue Oseghale, and Xiao Hu. Awards: Best Editor Award, IEEE OJCOMS (2024) CSE Junior Faculty Research Award Nominee (2024) Labs & Teams: The Graph Lab develops scalable solutions for HPC security and graph analytics. Recent projects include BINGO (EuroSys ‘25) and TANGO (SC ‘23).

• Semiconductor Reliability
• Machine Learning for CAD
• Hardware Security
• +۶ مورد دیگر

Hussam Amrouch is a Professor (W3) at the Technical University of Munich (TUM) , leading the Chair of AI Processor Design (AI-Pro) and affiliated with the Munich Institute of Robotics and Machine Intelligence (MIRMI) . He also serves as the head of Semiconductor Test and Reliability (STAR) at the University of Stuttgart. His academic journey includes a Ph.D. (Dr.-Ing.) summa cum laude from Karlsruhe Institute of Technology (KIT) and leadership of the Dependable Hardware Research Group at KIT. His research spans design for reliability and testing , machine learning for CAD , hardware security , approximate computing , and emerging technologies with a focus on ferroelectric devices . Recent publications highlight applications in hyperdimensional computing , cryogenic circuits , and neuromorphic systems . Amrouch has received 8 HiPEAC Paper Awards and best paper nominations at top EDA conferences. His work is funded by organizations including the German Research Foundation (DFG) , Advantest Corporation , and the U.S. Office of Naval Research (ONR) . He has over 200 publications across multidisciplinary domains from semiconductor physics to computer architecture. As an editor at Nature Scientific Reports , he contributes to journal oversight. His technical leadership extends to program committees of major EDA conferences like DAC, ASP-DAC, and ICCAD.

Mubarak Shahمشاهده پروفایل

استاد

• Computer Vision
• Video Surveillance
• Visual Tracking
• +۷ مورد دیگر

Dr. Mubarak Shah is the Trustee Chair Professor of Computer Science and Founding Director of the Center for Research in Computer Vision (CRCV) at the University of Central Florida. His research focuses on computer vision, including video surveillance, visual tracking, human activity recognition, and UAV video analysis. He has held prestigious fellowships from ACM, NAI, AAAS, IAPR, and IEEE. Roles: Trustee Chair Professor, Director of CRCV, Graduate Faculty Member Affiliations: University of Central Florida, College of Engineering and Computer Science Research interests span visual analysis of crowded scenes, video registration, and privacy-aware diffusion models. He has pioneered geolocalization techniques and multimodal learning frameworks. His work impacts security, autonomous systems, and medical imaging. Recent publications emphasize diffusion models, 3D object detection, and adversarial learning. His work has been presented at CVPR, ECCV, and NeurIPS. Awards: Pegasus Professor (2006) ACM SIGMM Technical Award (2019) Multiple fellowships and recognitions from IEEE, AAAS, and others Advising and mentorship include over 50 graduate students and NSF REU programs. He leads CRCV, a hub for interdisciplinary vision research, and contributes to high-impact datasets like MAVREC. Labs/Teams: CRCV hosts cutting-edge projects in geolocalization, action recognition, and medical vision. Collaborative efforts include global partnerships in AI and robotics.

Gregory L. McColmمشاهده پروفایل

دانشیار

• Mathematical Logic
• Theoretical Computer Science
• Probabilistic Methods
• +۷ مورد دیگر

Gregory L. McColm is an Associate Professor in the Department of Mathematics & Statistics at the University of South Florida, College of Arts and Sciences. He holds a Ph.D. in Mathematical Logic from UCLA (1986), an M.A. from UCLA (1982), and a B.A. from Oberlin College (1980). His interdisciplinary research spans mathematical logic, theoretical computer science, discrete geometry, mathematical crystallography, and mathematics education. Recent publications focus on applications of lattice theory and coding in communications systems, with innovations in MIMO transmission, fiber-optic communications, and signal constellation design. His work demonstrates consistent development of efficient algorithms for high-dimensional modulation schemes and error correction techniques. Professor McColm has advised multiple graduate students in mathematics and maintains active research programs in both pure and applied mathematics. His work in mathematical crystallography explores nanostructure design principles using computational geometry approaches.

Bin Yangمشاهده پروفایل

استاد

• Computer Science
• Data Management
• Machine Learning
• +۹ مورد دیگر

Bin Yang is a Professor at the Department of Computer Science, Aalborg University, affiliated with The Technical Faculty of IT and Design. His research focuses on data engineering, artificial intelligence, and machine learning, with emphasis on spatiotemporal data analysis, representation learning, and time series forecasting. He leads projects like aSTEP (spatio-temporal data analytics) and Light-AI for Cognitive Power Electronics. Key contributions include advancements in trajectory data processing, anomaly detection, and lightweight neural architectures. Research interests span machine learning, data mining, intelligent transport systems, and material science applications. Notable awards include the IJCAI 2019 Distinguished PC Member and Sapere Aude Research Leader (2018). He has supervised six PhD students and contributed to over 119 publications. His work is supported by grants from Villum Foundation and EU initiatives. Yang is involved in interdisciplinary collaborations, including data-driven decision-making frameworks and environmental monitoring systems. Labs and teams include the Daisy Center for Data-intensive Systems and AI for the People initiatives. Projects emphasize real-world applications in smart cities, traffic forecasting, and sustainable technologies. His research bridges theoretical foundations with practical implementations in domains like oceanography and crowdsourcing systems.

Enzo Tartaglioneمشاهده پروفایل

دانشیار

• Deep Learning
• Model Compression
• Pruning
• +۶ مورد دیگر

Enzo Tartaglione serves as Associate Professor at Télécom Paris, Institut Polytechnique de Paris, holding a Hi!Paris chair and contributing as Associate Editor for IEEE Transactions on Neural Networks and Learning Systems. His academic journey spans multiple institutions across Europe and the US, reflecting a strong interdisciplinary foundation. Educational milestones include: MS in Electronic Engineering, Politecnico di Torino (2015, cum laude) MS in Electrical and Computer Engineering, University of Illinois at Chicago (2015, magna cum laude) MS in Electronics, Politecnico di Milano (2016, cum laude) PhD in Physics, Politecnico di Torino (2019, cum laude), thesis: 'From Statistical Physics to Algorithms in Deep Neural Systems' His research centers on efficient deep learning , with pioneering work in model compression, neural pruning, and debiasing techniques. He actively develops methods for privacy-aware learning and green AI, targeting real-world deployment constraints in computer vision and medical imaging applications. His approach bridges theoretical physics with practical AI optimization. Recent publications (2024-2025) demonstrate consistent focus on computational efficiency, with 60% of works addressing model compression for vision tasks, 25% on bias mitigation, and emerging contributions in privacy preservation. Key venues include ICCV, CVPR, and IEEE Transactions, reflecting strong industry-academia impact. Scientific recognition includes: Finalist for Multimedia Rising Star Award (2025) He mentors 10 active PhD candidates across compression, debiasing, and on-device learning domains, having previously guided 3 PhD graduates and 17+ Master's researchers. Research funding includes the Hi!Paris GIFFAI project (2025) for frugal AI and ANR's BANERA initiative (2024) on bias-aware architecture search. His group operates within Télécom Paris' joint laboratory, driving the Frugal AI initiative through collaborations with ELLIS Society partners and industry stakeholders focused on sustainable deep learning deployment.

• Computer Networks
• Immersive Video Streaming
• Information Centric Networking
• +۳ مورد دیگر

Giuseppe Ribezzo is affiliated with the C3Lab, focusing on advanced networking and multimedia systems research. His work emphasizes immersive video streaming optimization, information-centric networking (ICN), and IoT middleware design. He has contributed to developing tools like TAPAS-360 for evaluating 360° video streaming systems and exploring adaptive bitrate control mechanisms using DASH protocols. Research interests include optimizing network bandwidth for immersive content, improving industrial IoT communication via IEEE 802.15.4 protocols, and enhancing streaming QoE through innovative compression and resolution adaptation techniques. His publications span from 2015 to 2021, addressing challenges in both theoretical frameworks and practical implementations. No scientific awards or student advisees are explicitly listed in the provided materials. Collaborations and grants are not detailed here, but his work aligns with C3Lab’s focus on cutting-edge telecommunications and multimedia systems.

Jin Liuمشاهده پروفایل

استاد

• Analog Integrated Circuits
• High-Speed Communications
• Biomedical Applications
• +۴ مورد دیگر

Dr. Jin Liu is a Professor in the Department of Electrical & Computer Engineering at the University of Texas at Dallas, affiliated with the Erik Jonsson School of Engineering and Computer Science. She joined UT Dallas as an Assistant Professor in 1999, advancing to Associate Professor in 2005 and full Professor in 2012. Her educational background includes: B.S. in Electronics and Information Systems from Zhongshan University (1992) M.S. in Electrical and Computer Engineering from University of Houston (1995) Ph.D. in Electrical and Computer Engineering from Georgia Institute of Technology (1999) Dr. Liu's research focuses on analog integrated circuits and systems for high-speed communications and biomedical applications. Key areas include: High-performance ADCs for communication systems Energy harvesting techniques for IoT devices Low-power IC design for biomedical implants RF/wireless circuit architectures including MIMO and 5G technologies Her work emphasizes efficiency optimization, metastability mitigation in converters, and novel clock generation techniques for millimeter-wave applications. Recent publications demonstrate a consistent focus on high-speed data conversion (ADCs), power management ICs, and RF systems. Trends include: Advanced calibration techniques for analog-to-digital converters Time-interleaved and flash ADC architectures Millimeter-wave clock generators for 5G applications Low-power solutions for IoT and biomedical devices Her research spans from fundamental circuit design to system-level optimization in communication and energy harvesting domains.

Mini Dasمشاهده پروفایل

استاد

• Medical Imaging
• Biomedical Engineering
• Optical Physics
• +۷ مورد دیگر

Mini Das is the Moores Professor in the Department of Physics at the University of Houston, with affiliations in the Cullen College of Engineering's Biomedical Engineering and Electrical and Computer Engineering departments. She holds a Ph.D. from the Indian Institute of Technology, Delhi. Her research focuses on advanced imaging techniques at the intersection of optical physics, computational methods, and engineering, with applications in medical diagnostics, defense/security, and global health. Key areas include X-ray phase contrast imaging, photon-counting detectors (collaborating with CERN), virtual clinical trials, and psychophysical models for human perception in medical imaging. Her work aims to improve cancer screening accessibility in underserved regions through innovative imaging systems. Das leads interdisciplinary projects combining quantum detection, material decomposition algorithms, and virtual patient modeling. She is a leader in developing cutting-edge imaging tools and has pioneered methods for low-dose and high-resolution biomedical imaging. Education : Ph.D., Indian Institute of Technology, Delhi Research Interests : Experimental/Optical design and computational imaging, virtual clinical trials, psychophysics/image science, vision science-driven imaging systems, and global health applications in cancer screening. Her lab develops advanced imaging modalities like multi-contrast X-ray phase mammography and spectral CT material decomposition systems. Grants & Collaborations : Works with CERN to optimize quantum detectors, FDA on regulatory-compliant imaging systems, and non-profits to deploy screening tools in low-resource areas. Her lab also collaborates on eye-tracking studies for human observer performance modeling in radiology. Labs/Teams : Directs a lab focused on quantum detection systems, computational imaging platforms, and bio-inspired optical designs. Active in multi-university consortia for biomedical imaging innovation.