جستجوی استاد راهنمای دانشگاهی

Sheng Shen is a Professor in the Mechanical Engineering Department at Carnegie Mellon University (CMU) , with courtesy appointments in the Departments of Electrical and Computer Engineering and Materials Science and Engineering . He earned his Ph.D. in Mechanical Engineering (Minor in Electrical Engineering) from Massachusetts Institute of Technology (MIT) , and his B.S. and M.S. from Huazhong University of Science and Technology in China. Prior to joining CMU in 2011, he conducted postdoctoral research at UC-Berkeley . Education: Ph.D., Mechanical Engineering, MIT (2010) B.S. & M.S., Power Engineering & Engineering Thermophysics, Huazhong University of Science and Technology (2000 & 2003) Research interests include nanophotonics , nanoscale energy transport and conversion , nanofabrication , and advanced manufacturing , with applications in thermal management , light sources and devices , thermal emission control , solar energy conversion , infrared sensing , and multifunctional materials . His work leverages interdisciplinary expertise in thermal and optical measurements , material synthesis , device fabrication , and theoretical modeling . Recent publications highlight advancements in infrared radiation control , thermal interface materials , metasurface engineering , and graphene-based nanosystems . His scientific awards include: NSF CAREER Award DARPA Director's Fellowship DARPA Young Faculty Award Elsevier/JQSRT Raymond Viskanta Award CMU Dean's Early Career Fellowship Philomathia Foundation Research Fellowship Hewlett-Packard Best Paper Award Best Paper Award, Julius Springer Forum Advising spans Ph.D. and postdoctoral researchers in nanoscale energy systems, with alumni contributing to solar energy conversion , infrared sensing , and flexible electronics . His lab receives funding from ARL, DARPA, DOE, DTRA, NASA, NSF, and ONR , and recently secured a DURIP award for instrumentation.

• Nanophotonics
• Nanoscale Energy Transport and Conversion
• Advanced Manufacturing
• +۷ مورد دیگر

Professor Marc Sorel is a faculty member in the Department of Electronic & Nanoscale Engineering at the University of Glasgow's School of Engineering. He holds a PhD from Università di Pavia (1999) and joined the Optoelectronics Research Group at Glasgow in 1998 with a Rotary Foundation fellowship. Appointed Lecturer in 2002 and Senior Lecturer in 2008, he is now a Professor specializing in integrated optics, silicon photonics, and semiconductor lasers. His research focuses on applications like quantum technology, mid-infrared optoelectronics, and nonlinear photonics. Notable projects include silicon nitride optical phased arrays and rubidium-based atomic systems. He leads a team advancing chip-scale sensors and photonic integrated circuits. Collaborations with institutions like the Quantum Technology Hub highlight his industry engagement. Research interests span semiconductor ring lasers, ultrashort pulse lasers, and coupled ring resonators on silicon-on-insulator platforms. His work integrates materials science (e.g., alumina/silicon nitride) with quantum and optical engineering innovations. Over 300 publications and presentations at conferences like CLEO and ECOC reflect his global impact. Current efforts emphasize mid-infrared sensing, cold atom systems, and high-precision laser development. His lab develops photonic components for atomic trapping, quantum communication, and biomedical sensing. Recent advancements include sub-kHz linewidth lasers and low-loss waveguides. Funding from UK Research and Innovation supports his exploration of next-generation photonic technologies.

• Integrated Optics
• Silicon Photonics
• Semiconductor Lasers
• +۳ مورد دیگر

Maj Keith A. Wyman, PhD is a researcher affiliated with the Air Force Institute of Technology (AFIT), specializing in quantum optics and atmospheric photonics. His work focuses on photonic qubit propagation, atmospheric turbulence effects, and laser-based quantum technologies. He holds a PhD in Applied Physics from AFIT (2023), an M.S. in Applied Physics (2014), and dual B.S. degrees in Physics and Mathematics from the United States Air Force Academy (2012). Wyman’s research interests include developing atmospheric turbulence simulators, studying quantum communication protocols, and advancing laser technologies for free-space optical networks. His recent publications address photon pair indistinguishability, qubit degradation under turbulence, and sodium beacon systems for adaptive optics. He collaborates with institutions like Ohio State University’s Center for Quantum Information Science and Engineering. His academic contributions span conferences such as SPIE and FQMT, with a focus on experimental quantum systems and optical metrology. Wyman’s work bridges theoretical quantum mechanics with applied engineering solutions for military and civilian optical communication challenges.

• Quantum Optics
• Atmospheric Propagation
• Photonics
• +۳ مورد دیگر

Tomas Palacios is a Professor of Electrical Engineering at the Massachusetts Institute of Technology (MIT) , where he directs the Center for Graphene Devices and 2D Systems and leads the Microsystems Technology Laboratories (MTL). His research focuses on pushing the boundaries of microelectronics through novel semiconductor materials and device architectures, including Gallium Nitride (GaN) and 2D materials like graphene and molybdenum disulfide (MoS2). Professor, MIT Electrical Engineering and Computer Science Director, MIT Center for Graphene Devices and 2D Systems Clarence J. LeBel Professor, MIT Faculty Director, Northeast Microelectronics Internship Program (NMIP) Research Interests span multiple cutting-edge domains: High-frequency electronics (>300 GHz) for 6G and quantum applications High-voltage power devices (600V–10kV) for energy conversion Post-silicon logic devices using 2D materials High-temperature electronics (e.g., Venus rover applications) Distributed neural networks on large-area 2D materials Graphene-based biosensors and chemical detection systems Scientific Contributions include: Double recipient of the IEEE George Smith Award for groundbreaking GaN transistor work Co-invented first MoS2 electronic circuits Developed world’s first Wi-Fi-to-electricity conversion antenna Led MIT’s Microsystems Technology Laboratories since 2021 Advising Philosophy emphasizes cross-layer expertise, with students gaining experience from materials synthesis to system-level prototyping. His lab has incubated startups like Vertical Horizons , focused on GaN power devices for AI and EVs.

• Semiconductor Physics
• Gallium Nitride (GaN) Electronics
• Two-Dimensional Materials
• +۶ مورد دیگر

Prof. Marcy Zenobi-Wong is a Full Professor at ETH Zurich's Department of Health Sciences and Technology, specializing in biofabrication and tissue engineering. Her research focuses on cartilage regeneration using advanced biomaterials, including nanofilm coatings and 3D printing techniques. She holds patents in tissue engineering and has pioneered methods like filamented light (FLight) biofabrication for creating anisotropic tissues. Her academic journey includes a B.Sc. from MIT (1985), M.Sc. and Ph.D. from Stanford (1987, 1990), followed by postdoctoral work at the University of Michigan. She leads the Biofabrication Group at ETH, developing therapies for joint repair and regenerative medicine. Courses taught include Biomedical Engineering and Materials and Mechanics in Medicine . Research highlights include engineered hydrogels for cartilage protection, CRISPR-driven gene editing in chondrocytes, and biohybrid neural interfaces. Her work bridges material science, cell biology, and clinical applications, with a focus on translational medicine. Collaborative projects involve creating elastic cartilage grafts for microtia reconstruction and volumetric printing of complex tissue constructs.

• Tissue Engineering
• Biofabrication
• Cartilage Regeneration
• +۳ مورد دیگر

Harvey B. Meyer is a Professor of Theoretical Physics at Johannes Gutenberg University Mainz since 2014. Previously, he held positions including Junior Professor at Mainz (2010), Fellow at CERN's Theoretical Physics Division (2009), Research Scientist at MIT (2008), and postdoctoral roles at MIT (2006-2008) and DESY (2004-2006). He earned his D.Phil. in Theoretical Physics from the University of Oxford (2001-2004) and a Diplome de Physique from the University of Lausanne (1996-2001). His research focuses on lattice field theory, QCD phase diagrams, thermal field theory, and hadron structure. He leads the NEPhEuQCD collaboration and has received the ERC Consolidator Grant (2018) for the SIMDAMA project. Meyer teaches courses in theoretical physics and mathematical methods at Mainz, including 'Theoretische Physik 4' and 'Mathematische Rechenmethoden'. His work integrates advanced computational techniques to address fundamental questions in particle and nuclear physics. Key achievements include pioneering studies on the muon's anomalous magnetic moment, hadronic light-by-light scattering, and quark-gluon plasma dynamics. Collaborations include MIT, CERN, and institutions globally through lattice QCD projects. His lab and team contributions are central to the PRISMA+ Cluster of Excellence at Mainz.

• Lattice Field Theory
• QCD Phase Diagram
• Thermal Field Theory
• +۴ مورد دیگر

Moe Z. Win is the Robert R. Taylor Professor at the Massachusetts Institute of Technology (MIT), specializing in wireless communications, optical communications, and space communications systems. His research bridges theoretical and applied domains, including quantum sensing, network localization, and signal processing. B.S.E.E., Texas A&M (1987) M.S.E.E. & Ph.D., University of Southern California (1989, 1998) Recent work focuses on quantum-enhanced positioning, machine learning for localization, and next-generation (xG) non-terrestrial networks. He leads research at the Quantum neXus Laboratory (QX Lab), Wireless Information & Network Sciences Lab, and Laboratory for Information and Decision Systems. His career spans the Jet Propulsion Laboratory (1987-1995) and AT&T Research Laboratories (1998-2002). Key methodologies include soft information fusion, variational quantum sensing, and robust beam tracking for terahertz communications.

• Wireless communications
• Optical communications
• Space communications systems
• +۲ مورد دیگر

Professor CHEN Wei (National University of Singapore) holds the Provost's Chair Professorship (2023-2026) and serves as Vice-Dean (Research) with joint appointments in the Departments of Chemistry and Physics. His research focuses on molecular-scale interface engineering for 2D materials-based devices and interface-controlled nanocatalysis in energy/environmental applications. PhD in Material Science, NUS (2004) Lee Kuan Yew Research Fellow (2006-2008) Established Surface and Interface Lab (2009) Director, NUS Research Institute (Fuzhou) His work on 2D optoelectronic memory (Nat. Comm. 2018), Kagome lattice design (Nano Lett. 2020), and single-atom catalysis (Nat. Comm. 2021) has been recognized by multiple high-impact publications and the Clarivate Highly Cited Researcher status (2017-2021). Awards include the NRF Investigatorship (2023) , Mitsui Chemicals-SNIC Industry Award (2020) , and Singapore Young Scientist Award (2012) . Grants from NUS, Singapore MOE, CREATE/CRP programs, and A*STAR support his exploration of interface engineering for neuromorphic computing and energy-efficient nanocatalysts . Current projects include monolayer blue phosphorus synthesis and solid electrolyte interphase engineering for lithium batteries.

• 2D Materials Engineering
• Interface-Controlled Nanocatalysis
• Organic Electronics
• +۳ مورد دیگر

Dr. Saree Alnaghy is an Honorary Associate Professor at the University of Wollongong's Faculty of Engineering and Information Sciences, affiliated with the Centre for Medical Radiation Physics. She holds a Bachelor of Medical and Radiation Physics (Honours) and a PhD in Physics from the University of Wollongong (2009–2017). Her research focuses on advanced medical imaging and radiation therapy technologies, including photon counting detectors, dosimetry systems, and robotic motion phantoms for quality assurance. Key research areas include: Development of novel X-ray detectors for radiotherapy guidance High-resolution dosimetry techniques using silicon and polymer-based systems Integration of real-time imaging in radiation therapy Robotic systems for motion management in oncology Her work has been supported by grants such as 'Sharper Targeting, Brighter Future' (2024) and 'Bringing Colour to Radiotherapy' (2021–2025). She currently supervises PhD and MRes students on projects involving photon counting CT scanners and radiotherapy imaging. Alnaghy also serves as a Radiation Oncology Medical Physics Registrar at the Nelune Comprehensive Cancer Centre.

• Medical Physics
• Radiation Oncology
• Medical Imaging
• +۳ مورد دیگر

Adrien Desjardins is a Professor at the University of British Columbia, jointly appointed in the Department of Mechanical Engineering and Department of Electrical and Computer Engineering within the Faculty of Applied Science. He joined UBC in 2024 after serving as a Full Professor at University College London from 2019-2024, following 13 years on faculty there. His educational background includes a B.Sc. from UBC (2001) and a Ph.D. from MIT and Harvard University (2007). Dr. Desjardins' research program focuses on interdisciplinary development of imaging and sensing modalities and autonomous robotics with marine and biomedical applications. His work integrates photonics, ultrasound, machine learning, and robotics to create innovative diagnostic tools and sensing systems, particularly in optical coherence tomography, diffuse optical spectroscopy, and photoacoustic imaging. His publication record reveals an evolution from foundational neuroimaging work (2001) toward increasingly sophisticated optical systems culminating in breakthroughs like ultrasensitive optical microresonators for ultrasound sensing (2017), demonstrating consistent innovation in biomedical optics with growing emphasis on machine learning integration and real-world applications. His scientific contributions have been recognized through prestigious awards: Research Chair from the Royal Academy of Engineering Healthcare Technologies Challenge Award from EPSRC Starting grants from ERC, EPSRC, and Royal Society World Economic Forum Young Scientist (2015) UCL Provost Teaching Prize (2013) Dr. Desjardins actively mentors graduate students and secures major research funding through competitive grants, with current openings for January/September 2025 intakes. His program involves close industry collaboration indicating strong translational focus, though specific lab names aren't mentioned. The interdisciplinary nature of his work suggests teams spanning engineering, computer science, and medical disciplines working on next-generation imaging systems for healthcare and marine exploration.

• Imaging and sensing
• Robotics
• Machine learning
• +۶ مورد دیگر

Dr. Tommaso Marcato is a Lecturer at the Department of Chemistry and Applied Biosciences, ETH Zürich. He earned his MSc in Chemical and Bioengineering from ETH Zürich after completing his BSc in Chemical Engineering at Politecnico di Milano, Italy. His research focuses on perovskite light-emitting diodes (PeLEDs), emission anisotropy, and light-outcoupling efficiency, with a particular emphasis on transition dipole moment orientation and nanocrystal self-assembly. His publications span topics such as Stabilization of CsPbI₃ nanoplatelets via metal iodide doping Molecular orientation engineering in OLEDs Ultraflexible self-powered optoelectronics Electroluminescent metasurfaces using perovskite nanocrystals His work aims to overcome photon trapping in devices by manipulating emitter orientation and exploring quantum confinement effects. Dr. Marcato's recent articles (2019–2025) demonstrate expertise in Hybrid perovskite systems Quantum dot applications Photonic device architecture Surface passivation techniques . He is part of the Shih group at ETH Zurich and has received funding from ETH-33 18-2 for his research on graphene-templated molecular alignment in LEDs.

• Materials Science
• Optoelectronics
• Nanotechnology
• +۳ مورد دیگر

Haitong Li is an Assistant Professor in the School of Electrical and Computer Engineering at Purdue University's College of Engineering, joining the faculty in 2022. His research bridges nanoelectronic devices, integrated circuits, and nanotechnology-inspired AI hardware to address critical challenges in energy-efficient artificial intelligence systems. Education: Ph.D. in Electrical Engineering, Stanford University Research Interests: Dr. Li pioneers emerging memory technologies—particularly Resistive RAM (RRAM)—for in-memory computing and neuromorphic systems. His work focuses on 3D monolithic integration of RRAM and gain cell memory with CMOS to enable edge AI, with recent breakthroughs in hardware acceleration for large language models and sustainable computing. Key innovations include carbon footprint prediction for LLMs and zeroth-order fine-tuning techniques. Publication Trends: Dr. Li's 2023-2025 publications reveal a strategic shift toward sustainable AI hardware, emphasizing carbon-aware LLM inference and edge deployment. His research consistently targets data movement reduction through memory-centric architectures, spanning photonic accelerators, neuro-symbolic computing, and heterogeneous 3D integration. Awards: No scientific awards were documented in the provided sources. Advising and Grants: Current advisees and grant funding details were not specified in the available materials. Labs and Teams: Research group composition and laboratory facilities were not described in the source text.

• Nanoelectronic devices
• Integrated circuits
• AI hardware
• +۵ مورد دیگر

Tzu-Mao Li is an Assistant Professor in the Department of Computer Science and Engineering (CSE) at the University of California, San Diego (UCSD), affiliated with the Center for Visual Computing. His research focuses on differentiable graphics algorithms, combining classical visual computing with modern machine learning techniques. He holds a Ph.D. from MIT CSAIL under Frédo Durand and a postdoc at MIT and UC Berkeley with Jonathan Ragan-Kelley. His work spans rendering, programming languages for graphics, Monte Carlo methods, and inverse problems. Education: B.S. and M.S. from National Taiwan University (2011-2013), advised by Yung-Yu Chuang. Ph.D. from MIT CSAIL (Computer Graphics Group), advised by Frédo Durand. Postdoctoral research at MIT and UC Berkeley with Jonathan Ragan-Kelley. Research Interests: Differentiable rendering, Monte Carlo integration, programming language design for visual computing, physical simulation, adversarial machine learning, and applications in computer vision and robotics. Key areas include rendering algorithms (path tracing, bidirectional methods), optimization techniques (MCMC, gradient-based), and neural representations (SDFs, neural fields). Publications focus on advancing rendering algorithms, differentiable systems, and applications in inverse problems. Notable contributions include edge sampling for differentiable rendering, warped-area sampling, and diffusion models for BSDF sampling. Awards: ACM SIGGRAPH 2020 Outstanding Doctoral Dissertation Award, multiple Best Paper Awards at SIGGRAPH, and oral presentations at ICCV. Teaching: Courses include CSE 167 (Computer Graphics), CSE 168 (Rendering), and CSE 272 (Advanced Image Synthesis), emphasizing physically-based methods and programming.

• Computer Graphics
• Rendering Algorithms
• Differentiable Programming
• +۵ مورد دیگر

Rakesh Kumar is a Professor and John Bardeen Faculty Scholar in the Electrical and Computer Engineering Department at the University of Illinois at Urbana-Champaign. His work focuses on computer architecture, system-level design automation, and low-power computing. PhD in Computer Engineering from University of California, San Diego BS in Electrical Engineering from IIT Kharagpur His research spans all layers of the computing stack, with key contributions to flexible computer systems , waferscale computing , error-resilient architectures , and approximate computing . He has pioneered work on voltage-reliability tradeoffs and peak power management techniques. Recent publications highlight trends in space microdatacenters , printed microprocessors , and neural graph accelerators . His work on plastic chips was recognized as one of the three biggest semiconductor headlines of 2022 by IEEE Spectrum. IEEE Fellow (2024) ISCA Influential Paper Award MICRO Test-of-Time Award ICCAD Ten Year Retrospective Most Influential Paper Award Best Paper Awards at CASES, SELSE, HPCA He has received teaching accolades including the Stanley H. Pierce Faculty Award and Ronald W. Pratt Outstanding Teaching Award . His research group explores hardware-software co-design for emerging applications in AI, IoT, and sustainable computing.

• Computer Architecture
• System-Level Design Automation
• Low Power Computing
• +۳ مورد دیگر

David B. Lindell is an Assistant Professor in the Department of Computer Science at the University of Toronto, with affiliations to the Vector Institute and AXL. He is a founding member of the Toronto Computational Imaging Group. His research focuses on physically based intelligent sensing, integrating physical models, signal processing, and AI to advance sensing systems. Notable projects include imaging around corners, through scattering media, and developing machine learning algorithms for 3D scene reconstruction. Education: Ph.D. in Computational Imaging from Stanford University (advisor: Gordon Wetzstein). Awards include the 2024 Ontario Early Researcher Award and the Best Student Paper at CVPR 2025. His work combines computational imaging with applications in computer graphics and autonomous systems. Research interests span non-line-of-sight imaging, single-photon sensing, and neural representations. Key contributions include the Light-Cone Transform (Nature 2018), confocal diffuse tomography (Nature Communications 2020), and AutoInt (CVPR 2021). His lab develops systems for 3D reconstruction, transient imaging, and photon-efficient sensors. Selected grants and support: NSF CAREER Award, DARPA REVEAL program, and KAUST Visual Computing Center funding. Active collaborations with industry and academic institutions on autonomous driving and medical imaging applications.

• Computational Imaging
• Computer Vision
• Non-Line-of-Sight Imaging
• +۵ مورد دیگر