جستجوی استاد راهنمای دانشگاهی

Mark Libermanمشاهده پروفایل

استاد

• Corpus-based Phonetics
• Speech and Language Technology
• Clinical Applications of Linguistics
• +۶ مورد دیگر

Mark Liberman is a Trustee Professor at the University of Pennsylvania , holding appointments in the Department of Linguistics and Department of Computer and Information Science . He serves as Director of the Linguistic Data Consortium and Faculty Director of Ware College House . His career spans linguistics, speech technology, and computational methods. Education: Harvard University (1965-1969), MIT (M.S. 1972, Ph.D. 1975) Professional Experience: AT&T Bell Laboratories (1975-1990), University of Pennsylvania (1990-present) His research interests include: Corpus-based Phonetics : Analyzing speech patterns via large-scale datasets. Clinical Applications : Developing speech biomarkers for neurodegenerative diseases. Tonal Phonology : Studying lexical tone and intonation in languages like Yoruba and Mandarin. Formal Annotation Models : Creating frameworks for linguistic data standardization. Recent publications highlight automated speech analysis, cross-linguistic prosody, and digital biomarkers for conditions like ALS-FTD and Alzheimer’s. His collaborations span computational linguistics , neurology , and cognitive science . Scientific awards include the IEEE James L. Flanagan Award (2017), Antonio Zampolli Prize (2010), and fellowships from the AAAS and Linguistic Society of America . He advises PhD students May Chan and Jonathan Him Nok Lee and contributes to editorial boards for journals like Cognition and Annual Review of Linguistics . His work bridges speech science , language technology , and neurocognitive research .

John F. Beacomمشاهده پروفایل

استاد

• Neutrinos
• Dark Matter
• High-Energy Astrophysics
• +۵ مورد دیگر

John F. Beacom is a Distinguished Professor of Physics and Astronomy at The Ohio State University and Director of the Center for Cosmology and AstroParticle Physics (CCAPP). His academic roles include leadership in astroparticle physics research and education. He holds joint appointments in both the Department of Physics and the Department of Astronomy within the College of Arts and Sciences. Beacom earned his Ph.D. in Physics from the University of Wisconsin (1997) and dual B.S. degrees in Physics and Mathematics from the University of Kansas (1991). He has held postdoctoral positions at Fermilab and Caltech before joining Ohio State in 2004. His research focuses on neutrinos, dark matter, and multi-messenger astrophysics, with emphasis on neutrino detection techniques, supernova physics, and cosmological implications. He leads major projects like the All-Sky Automated Survey for Supernovae (ASAS-SN) and contributes to the Deep Underground Neutrino Experiment (DUNE). Awards: APS Fellow (2014), NSF CAREER Award (2005–2010), multiple teaching awards for distinguished instruction. Grants: Extensive funding from NSF, DOE, and collaborative international initiatives. Labs/Teams: CCAPP, DUNE Collaboration, ASAS-SN project. His articles span neutrino physics, detector development, and observational astrophysics, reflecting interdisciplinary expertise in theoretical and experimental particle astrophysics.

Haijun Xiaمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Human-AI Collaboration
• Interface Design
• +۲ مورد دیگر

Haijun Xia is an Assistant Professor at the University of California, San Diego (UCSD), where he directs the Foundation Interface Lab and contributes to the Cognitive Science and Design Lab. His work focuses on Human-Computer Interaction (HCI) and Human-AI Collaboration , emphasizing the development of dynamic, malleable interfaces that integrate human cognition with intelligent systems to enhance thinking and working paradigms. Education: Bachelor's, Tsinghua University Master's and PhD, University of Toronto His research spans generative AI , interface design , and creative collaboration , with applications in data visualization, programming, and scholarly work. He advocates for treating information as a malleable material that can be flexibly manipulated by users and AI agents. Recent publications highlight advancements in: 2025 CHI Conference - Generative user interfaces, malleable overview-detail designs, and compositional structures for human-AI co-creation 2024 CHI Conference - Structured design space exploration with LLMs, ASCII diagram analysis, and adaptive presentation systems 2023 CHI/UIST Conferences - Data particle visualization, contextual logging tools, and metaphor generation for science communication Scientific recognitions include: Multiple Best Paper Awards and Honorable Mentions at CHI and UIST Hellman Fellowship and grants from NSF , Microsoft , Google , Meta , Apple , and Adobe He actively recruits undergraduate and graduate interns and has an upcoming postdoc position in early 2025 for researchers interested in foundational interface development.

Asmita Mukherjeeمشاهده پروفایل

استاد

• Theoretical Particle Physics
• Quantum Chromodynamics
• QCD Spin Physics
• +۵ مورد دیگر

Professor Asmita Mukherjee is a faculty member in the Department of Physics at the Indian Institute of Technology Bombay (IIT Bombay), where she holds the position of Professor. She is actively engaged in theoretical particle physics research with a focus on Quantum Chromodynamics (QCD) and related phenomena. Professor Mukherjee's research interests primarily include Theoretical Particle Physics, Quantum Chromodynamics, QCD spin physics, Light-cone wave functions, and collider phenomenology. She teaches several advanced courses including Elementary Particle Physics (PH540), Mathematical Physics-I (PH407), Mathematical Physics-II (PH408), Quantum Physics and Applications (PH107), and various Quantum Mechanics courses (PH422, PH423, PH105). Her publication record shows a strong focus on gravitational form factors, transverse momentum dependent distributions, angular momentum structure of hadrons, and electron-ion collider physics. Recent work has explored gluon contributions to proton structure, dressed quark states, and azimuthal asymmetries in various production processes. Her research demonstrates expertise in light-front quantization techniques and their application to fundamental questions in hadron physics. Professor Mukherjee has received recognition for her work in High Energy Theory, with numerous publications in prestigious journals addressing fundamental questions in hadron structure and QCD dynamics. Her work provides crucial theoretical foundations for upcoming experiments at the Electron Ion Collider. Current PhD students: Sudeep Saha, Amol Pawar Graduated PhD students: Ravi Manohar, Sreeraj Nair, Vikash K. Ojha, Sangem Rajesh, Raj Kishore Postdoctoral researchers: Shaik Khatiza Banu (CFNS), Jai More, Tanmay Maji, Mariyah Siddiqah Research projects: BRNS project with Ravi Singh as Junior Research Fellow Her research group at IIT Bombay continues to explore fundamental questions in hadron physics, with ongoing projects examining the mechanical properties of protons, the decomposition of angular momentum in QCD, and the development of theoretical tools for interpreting data from next-generation colliders.

Sriram Subramaniamمشاهده پروفایل

استاد

• cryo-electron microscopy
• structural biology
• drug-design
• +۴ مورد دیگر

Sriram Subramaniam is a Professor in the Department of Biochemistry and Molecular Biology at the University of British Columbia (UBC) and holds the Gobind Khorana Canada Excellence Research Chair in Precision Cancer Drug Design. His research leverages cryo-electron microscopy (cryo-EM) to advance structural biology and drug design, focusing on protein dynamics and therapeutic target identification. Education: PhD in Physical Chemistry (1987) from Stanford University; MSc in Chemistry (1981) from Indian Institute of Technology, Kanpur. Subramaniam's interdisciplinary work combines cryo-EM with computational tools and molecular biology to study protein structures at atomic resolution. His lab has pioneered cryo-EM applications in precision medicine, including mapping small molecule drugs on patient-specific cancer mutants. Recent publications (2024-2022) highlight his contributions to understanding SARS-CoV-2 immune evasion, structural mechanisms of ATPases, and AI integration in structural biology. His research spans viral entry mechanisms, CRISPR systems, and neurodegenerative disease pathways. Scientific Awards: Gobind Khorana Canada Excellence Research Chair NIH Director’s Award for Scientific Excellence Fellow of the Biophysical Society Breakthrough Prize nomination Based at the Djavad Mowafaghian Center for Brain Health, Subramaniam leads the Program in Cryo-EM Guided Drug Design, contributing to over 177 peer-reviewed publications with a career h-index of 58 and citations exceeding 12,340.

Mo Rastgaarمشاهده پروفایل

استاد

• Assistive Robotics
• Rehabilitation Robotics
• Cyber-Physical Systems
• +۳ مورد دیگر

Dr. Mo Rastgaar is a Professor at Purdue Polytechnic Institute, Purdue University. He holds a PhD in Mechanical Engineering from Virginia Tech (2008) and completed a postdoctoral fellowship at MIT's Newman Laboratory for Biomechanics and Human Rehabilitation. He leads the Human-Interactive Robotics Lab (HIRoLab), focused on assistive and rehabilitation robots for enhanced mobility, particularly lower-extremity devices. His research emphasizes understanding agile gait dynamics through human experiments and modeling. Research interests include assistive robotics, cyber-physical systems, dynamics, and control systems. Notable awards include the 2014 NSF CAREER Award. He has secured grants such as the 2019 NRI Collaborative Grant on robotic ankle prosthetics and 2020 grants for undersea infrastructure. Dr. Rastgaar's work bridges biomechanics, robotics, and clinical applications, advancing prosthetic designs and human-robot interaction. Key contributions include developing steerable powered ankle-foot prostheses and exploring multi-robot systems for underwater exploration. His labs integrate interdisciplinary approaches to solve complex mobility challenges, emphasizing both technical innovation and real-world clinical impact.

• Particle Physics
• High Energy Physics
• Experimental Physics
• +۳ مورد دیگر

Prof. Dr. Günther Dissertori is a Full Professor and Rector of ETH Zurich, where he oversees teaching and academic affairs. His academic journey began at the University of Innsbruck, followed by a doctoral position at CERN, and he joined ETH Zurich as an Assistant Professor in 2001 before becoming a Full Professor in 2007. Academic Role: Full Professor of Particle Physics Institutional Leadership: Rector of ETH Zurich (since 2022) Contact: guenther.dissertori@sl.ethz.ch Research Interests: Dissertori's work spans Particle Physics and Experimental Physics , notably contributing to the CMS experiment at CERN, which was instrumental in the Higgs boson discovery. His group also developed cost-effective PET devices, leading to the spin-off Positrigo AG . Research keywords include Detector Development , Medical Imaging , and Quantum Physics . Teaching Excellence: Recognized with multiple Golden Owl awards (2005–2020) and the Credit Suisse Award for Best Teaching (2013), Dissertori is celebrated for his pedagogical impact in the Department of Particle Physics. Scientific Contributions: His publications include advancements in CMOS technology, quantum dynamics, and medical applications, reflecting interdisciplinary expertise in high-speed electronics, environmental science, and architectural history.

Seth Aubinمشاهده پروفایل

استاد

• Experimental Atomic Physics
• Quantum Physics
• Precision Measurements
• +۵ مورد دیگر

Seth Aubin is a Professor of Physics at the College of William & Mary, affiliated with the College of Arts & Sciences. His research focuses on experimental atomic, molecular, and optical physics, with emphases on precision measurements and quantum phenomena. Key projects include developing atom chip technologies for trapping ultracold atoms, Rydberg atom-based sensors for charged particle diagnostics, and francium spectroscopy for weak interaction studies. Education: License de Physique (ENS Paris/MIP), 1994 B.Sc. in Physics, Yale University, 1995 Ph.D. in Physics, SUNY Stony Brook, 2003 Research Themes: Quantum Trapping Techniques: Innovations in AC Zeeman atom chip traps and RF microtraps to suppress potential roughness Rydberg Atom Sensors: Pioneering applications in electron beam profiling and electromagnetic field imaging Franium Spectroscopy: Collaborative work on parity-violation measurements and isotope shift analyses Recent Article Trends: Recent work emphasizes practical implementations of quantum sensors (e.g., charged particle beam diagnostics) and foundational trapping technology advancements. Over 30 peer-reviewed publications since 2018 reflect sustained contributions to atom chip systems and precision measurements. Awards: American Physical Society Fellow (APS Fellow) Grants & Collaborations: Lead PI on atom chip-based interferometry projects Contributing member to the FrPNC collaboration at TRIUMF (atomic parity violation studies) Developed hybrid optical dipole traps for magnetometry applications Labs & Infrastructure: Manages state-of-the-art atomic physics labs at W&M, including ultrahigh-vacuum systems for francium trapping and laser stabilization setups. Active in developing microwave/radio-frequency atom chip platforms for next-generation quantum sensors.

• Neural Interfaces
• Micro/Nano Electro Mechanical Systems (MEMS)
• Biosystems & Computational Biology
• +۳ مورد دیگر

Michel M. Maharbiz is a Professor in the Department of Electrical Engineering and Computer Science at the University of California, Berkeley. He leads research on miniaturized bioelectronic interfaces, including neural dust implants and cyborg insects. He holds affiliations with the Berkeley Sensor & Actuator Center (BSAC), Center for Neural Engineering & Prostheses (CNEP), and SWARM Lab. His education includes a Ph.D. in EECS from UC Berkeley (2003) and a B.S. in EE from Cornell University (1997). Maharbiz's research integrates MEMS, ultrasonic systems, and synthetic biology to develop wireless neural interfaces, implantable sensors, and biohybrid devices. Key focus areas are neural dust technology for peripheral nerve recording, magnetoelastic strain sensors for medical applications, and electrochemical biosensing using bacterial flagellar motors. His publications emphasize neural interfaces, ultrasonic implants, and biomedical monitoring. Recent articles explore ultrasonic power delivery (2025), radiation detectors for oncology (2025), and fracture-healing smart plates (2019). Trends include miniaturization of wireless implants, closed-loop therapeutic systems, and novel biomaterials. Scientific Awards: McKnight Technological Innovations in Neuroscience Award (2017) Chan-Zuckerberg Biohub Investigator (2017) NSF CAREER Award (2009) MIT TR10 Top Emerging Technology (2009) Bakar Fellows Spark Award (2012) He directs the Maharbiz Lab, advancing neural dust and bioelectronic interfaces. Projects include impedance-based fracture monitoring, carbon fiber neural arrays, and hernia repair sensors. Funding includes NSF and industry partnerships for implantable device development.

Simo Särkkäمشاهده پروفایل

استاد

• Machine Learning
• Signal Processing
• Bayesian Filtering
• +۷ مورد دیگر

Professor Simo Särkkä holds a position in Sensor Informatics and Medical Technology at the Department of Electrical Engineering and Automation (EEA), Aalto University. His research focuses on multi-sensor data processing, Bayesian filtering, machine learning, and their applications in medical technology, brain imaging, and inverse problems. He leads research groups including the Helsinki Institute for Information Technology (HIIT) and Sensor Informatics and Medical Technology. His work bridges theoretical advancements in probabilistic methods with practical implementations in healthcare and engineering. Key research interests include Gaussian processes, stochastic differential equations, quantum machine learning, and signal processing. He has contributed to advancements in algorithms for nonlinear state-space models, parallel computing techniques, and medical imaging technologies such as scatter correction in CT scans. His methodologies are applied across domains like autonomous systems, robotics, and bioengineering. Notable publications span topics like quantum-assisted Gaussian regression, physics-informed machine learning for industrial processes, and parallel-in-time numerical methods. His work emphasizes computational efficiency and robustness in high-dimensional and real-time systems.

Albert Prestoمشاهده پروفایل

استاد پژوهش

• air quality
• atmospheric particle studies
• climate resilience
• +۷ مورد دیگر

Albert Presto is a Research Professor in the Department of Mechanical Engineering at Carnegie Mellon University with a courtesy appointment in Civil and Environmental Engineering. He serves as Director of the Center for Atmospheric Particle Studies (CAPS) and is a Faculty Affiliate at the Steinbrenner Institute for Environmental Education and Research. His work spans multiple interdisciplinary collaborations across environmental science, engineering, and public health domains. Department of Mechanical Engineering, College of Engineering Center for Atmospheric Particle Studies (CAPS) Steinbrenner Institute for Environmental Education and Research Africa Clean Air Network Advisory Council Health Effect Institute's Energy Review Committee Presto's research focuses on pollutant emissions from energy extraction and consumption and their subsequent atmospheric transformations. His work examines how gas and oil wells emit methane, how vehicles emit carbon monoxide and particulate matter, and how these pollutants undergo oxidation in the atmosphere to create secondary pollutants like ozone and secondary particulate matter. His approach combines ambient measurements, laboratory experiments, source testing of pollution sources, and atmospheric models to provide a holistic view of pollutant emissions and transformations. His recent publications reveal a strong emphasis on air quality monitoring technologies, particularly low-cost sensor networks deployed internationally. There's a clear trend toward studying air pollution in African cities (especially Nairobi, Kampala, and Addis Ababa), examining spatial and temporal variability of particulate matter, and investigating the health impacts of air pollution exposure. His work increasingly integrates machine learning approaches for pollution forecasting and leverages international collaborations to address global air quality challenges. Member of Africa Clean Air Network Advisory Council Collaborator with US embassies worldwide on air quality data collection Quoted in The Guardian on inequality of air pollution exposure, specifically noting how people of color are more likely to be exposed to harmful air pollution Collaborated on research regarding chemicals released during the Ohio train derailment Presto actively collaborates with medical professionals to develop neighborhood-by-neighborhood studies of pollutant exposure and to understand relationships between emissions and health effects like childhood asthma. His work includes investigating racial-ethnic exposure disparities to airborne pollutants and examining how proximity to pollution sources like fast-food restaurants affects pediatric asthma outcomes. He has received seed funding from the Scott Institute for Energy Innovation for research in clean hydrogen production, AI hardware efficiency, and decarbonizing transportation. As Director of CAPS, Presto leads a research team focused on atmospheric particle studies with applications ranging from local Pittsburgh air quality to global monitoring initiatives. His lab develops and deploys advanced air quality monitoring technologies, including low-cost sensor networks that have been implemented in multiple cities across Africa. The CAPS research group works at the intersection of environmental engineering, atmospheric science, and public health to address critical air quality challenges worldwide.

Erik B. Sudderthمشاهده پروفایل

استاد

• Machine Learning
• Computer Vision
• Statistical Inference
• +۳ مورد دیگر

Erik B. Sudderth is a Professor of Computer Science and Statistics and Chancellor's Fellow at the University of California, Irvine (UCI). He leads the Learning, Inference, & Vision Group and directs multiple research centers, including the UCI Center for Machine Learning and Intelligent Systems and the HPI Research Center in Machine Learning and Data Science. He previously served as an Associate Professor at Brown University. Education: B.S. (summa cum laude) in Electrical Engineering from UC San Diego (1999), M.S. and Ph.D. in EECS from MIT (2002, 2006). His research focuses on statistical methods for scalable machine learning, Bayesian nonparametrics, probabilistic graphical models, and applications in computer vision, AI, and environmental science. Key areas include nonparametric clustering, deep generative models, and particle-based inference algorithms. Research interests span diverse topics: advancing Bayesian nonparametric models for medical time series, scalable variational inference, and AI ethics. Notable contributions include the NET-VISA seismic monitoring system (ISBA Mitchell Prize, 2014), the BNPy toolbox (NSF CAREER Award), and work on diverse particle max-product algorithms for continuous inference. Scientific awards include the NSF CAREER Award, ISBA Mitchell Prize, and recognition as one of "AI's 10 to Watch" (IEEE). He has served as editor for top journals (JMLR, IEEE PAMI) and conference chairs (NeurIPS, CVPR). His work bridges theory and practice, with applications in robotics, climate science, and healthcare. Labs/Teams: UCI Learning, Inference, & Vision Group; UCI Center for Machine Learning; CREATE Technology Center. Grants include NSF funding for visually impaired collaboration tools and soil biogeochemical modeling.

Supratik Guhaمشاهده پروفایل

استاد

• Quantum Computing
• Semiconductor Materials
• Sensor Networks
• +۴ مورد دیگر

Supratik Guha is a Professor at the Pritzker School of Molecular Engineering and Senior Advisor to Argonne National Laboratory's Physical Sciences and Engineering directorate. His work bridges industrial R&D with academic and national lab research, focusing on quantum computing , semiconductor materials , and sensor networks for water and soil monitoring. Guha leads Argonne’s quantum information science strategy and serves as Faculty Director for the University of Chicago Center in Delhi. Education: PhD in Materials Science (USC, 1991), BTech in Engineering Physics (IIT Kharagpur, 1985) Research interests span multiple domains: Quantum technologies focusing on erbium-doped oxides for quantum memory and quantum interconnects Sensor networks for soil and water quality monitoring using cyberphysical systems Nanofabrication techniques including controlled spalling for heterogeneous material integration Advanced memory technologies exploring ferroelectric and optically addressable memory at atomic scales Scientific awards include: Election to National Academy of Engineering (2015) APS Prize for Industrial Applications of Physics (2015) Vannevar Bush Faculty Fellow (2018) Fellow of Materials Research Society and American Physical Society IBM Corporate Award (2013) Advising notable students like Manish Kumar Singh (co-founder memQ ), Cheng Ji (now at Intel), and Vamsi Nittala (now at Micron Technology). His group contributes to major DOE , NSF , and USDA funded projects including: Q-NEXT - DOE National Quantum Information Center AIFARMS - NSF/USDA AI for Agriculture Institute Thoreau Project - Geospatial sensor networks Labs and teams operate across University of Chicago and Argonne National Lab , with facilities for molecular beam epitaxy , nanofabrication , and optical/electrical characterization . The group has spawned startups like memQ (quantum networking) and K1 Semiconductors (wide-bandgap material transfer).

Alexey Gorshkovمشاهده پروفایل

استاد مدعو

• Quantum Optics
• Quantum Information Science
• Condensed Matter Physics
• +۶ مورد دیگر

Alexey Gorshkov is an Adjunct Professor at the University of Maryland (UMD) affiliated with the Joint Quantum Institute (JQI) and the Quantum Information and Computer Science Laboratory (QuICS). His primary academic role is in theoretical physics, focusing on quantum optics, quantum information science, and condensed matter physics. He leads a research group exploring quantum magnetism with alkaline-earth atoms, driven-dissipative systems, topological matter, and strongly interacting photons. His work bridges AMO (atomic, molecular, and optical) systems with high-energy and condensed matter physics, emphasizing quantum simulation and novel quantum technologies like precise clocks and quantum computers. Education details are not explicitly listed, but his research collaborations with institutions like JQI and UMD suggest advanced academic training in theoretical physics. His research interests revolve around understanding and controlling quantum many-body systems, particularly in far-from-equilibrium scenarios, entanglement dynamics, and dissipation effects. He has contributed to studies on Rydberg atoms, quantum routing protocols, and error mitigation in quantum simulators. Recent articles highlight his work on quantum protocols for verifying speedups, time-independent information flow, and entanglement dynamics. His group's achievements include demonstrating one-dimensional anyons and developing methods for correlated noise estimation with quantum sensors. Awards and grants are not explicitly mentioned in the provided text, but his prolific publication record indicates sustained research impact. Labs and teams associated with him include the JQI and QuICS, where he collaborates on experimental and theoretical projects. Graduate student and postdoc positions are available in his group, focusing on areas like quantum magnetism and topological systems. His work often involves close ties with experimental groups, emphasizing practical applications of theoretical breakthroughs.

Jianjing Kuangمشاهده پروفایل

دانشیار

• Phonetics
• Tonal Languages
• Speech Production and Perception
• +۴ مورد دیگر

Jianjing Kuang is an Associate Professor of Linguistics at the University of Pennsylvania, affiliated with the School of Arts and Sciences. As Director of the Penn Phonetics Laboratory, they lead research in phonetics, laboratory phonology, and tonal language studies. Kuang holds a Ph.D. from UCLA (2013) and specializes in the interplay between production and perception in speech, particularly focusing on tonal systems, prosody, and cross-linguistic fieldwork. Their work integrates behavioral experiments, corpus studies, and computational modeling to explore phonological contrasts, voice quality, and sound change. Key affiliations include MindCORE and the Center for East Asian Studies. Research interests include multidimensional cues in tone processing, glottal articulations, mapping production-perception relationships, and prosodic sentence processing. Kuang has conducted fieldwork on languages such as Yi, Q’anjob’al, and Mandarin. Their studies address topics like tonal splitting in Yi, cue-changing in Korean stops, and prosodic patterns in Mayan languages. Recent work explores voice quality’s role in pitch perception and prosodic boundary detection. Awards and grants are not explicitly listed, but Kuang’s extensive publications (over 50 peer-reviewed papers) reflect sustained academic impact. They advise graduate students in phonetics and phonology, with active collaborations in computational linguistics and speech technology. The Penn Phonetics Laboratory, under Kuang’s direction, emphasizes interdisciplinary research bridging experimental and theoretical phonetics.