جست‌وجوی استاد و پژوهشگر

Valtorta Flaviaمشاهده پروفایل

استاد

• Neuropsychopharmacology
• Neurodegenerative Disorders
• Parkinson's Disease
• +۷ مورد دیگر

Prof. Flavia Valtorta is a Full Professor of Pharmacology at San Raffaele Vita-Salute University, Milan, and Dean of the School of Medicine since 2019. She holds concurrent roles as Director of the Division of Neuroscience at San Raffaele Scientific Institute and President of the National Committee on Doping and Health Protection in Sports. Her academic journey includes leadership positions such as Rector’s Deputy for International Affairs (2004–2010) and coordinator of the Neuroscience PhD program. She earned a Doctor of Medicine from the University of Milan (cum laude) and completed postdoctoral training at The Rockefeller University and University of Milan. Education: MD (University of Milan), Board Certifications in Anesthesiology, Intensive Care, and Psychotherapy Professional Experience: Over 40 years in academia and research, including roles at University of Bari and Rockefeller University Research focuses on neuropsychopharmacology, neurodegenerative diseases (especially Parkinson’s), and psychiatric disorders. Her lab investigates dopamine dysfunction, gene therapy approaches for epilepsy, and circadian rhythm abnormalities in schizophrenia. She has authored ~140 peer-reviewed papers with an h-index of 57 and over 10,000 citations. Key Awards: Recognized in 'Top Italian Scientists' and as a member of TIWS (Top Italian Women Scientists) Administrative contributions include overseeing PhD programs and institutional governance. She chairs scientific committees for national and international agencies (INSERM, MRC UK, NIH) and serves on editorial boards (e.g., Frontier’s Cell Neuroscience).

Gino Dardanelliمشاهده پروفایل

دانشیار

• Geomatics
• GNSS Systems
• Geodetic Data Analysis
• +۴ مورد دیگر

Gino Dardanelli is an Associate Professor in Geomatics at the Department of Engineering, University of Palermo, where he graduated in Civil Engineering and Transport in 2000 and earned his PhD in Geodetic and Topographic Sciences in 2006. His research focuses on advanced geospatial technologies including GNSS networks, laser scanning, satellite imagery analysis, and structural monitoring. Education: PhD in Geodetic and Topographic Sciences, University of Naples Parthenope, 2006 Degree in Civil Engineering and Transport, University of Palermo, 2000 Research Interests: Dardanelli's research addresses the integration of geomatic technologies for environmental and structural analysis. Key areas include multi-GNSS system integration, WebGIS development, laser scanning applications in cultural heritage documentation, high-resolution satellite image processing, and cadastral mapping innovations. Publication Focus: Recent publications demonstrate strong emphasis on coastal monitoring techniques using isoradiometric methods, cultural heritage documentation through 3D modeling, and geodetic network development. The research consistently integrates field measurements with computational analysis for environmental and infrastructural applications. Teaching: Regularly instructs courses including Topography (Civil Engineering), Topography/Cartography (Agricultural Engineering), and Applied Topography Laboratory (Environmental Engineering). Student Supervision: Advises graduate theses on topics including GNSS applications, geological monitoring, and surveying techniques.

Julia Salzmanمشاهده پروفایل

دانشیار

• RNA Biology
• Computational Biology
• Genomics
• +۴ مورد دیگر

Julia Salzman is an Associate Professor at Stanford University, affiliated with the School of Medicine in the Departments of Biomedical Data Science and Biochemistry , with courtesy appointments in Statistics and Biology . She serves as a member of interdisciplinary centers including Bio-X , Stanford Cancer Institute , and Sarafan ChEM-H . Salzman's research focuses on statistical computational biology , particularly RNA splicing , cancer genomics , and microbial systems . Her lab develops algorithms like SPLASH (Statistically Primary aLignment Agnostic Sequence Homing) and SICILIAN for precise splice junction detection, enabling reference-free analysis of genomic data across human , non-model organisms , and planetary health applications (e.g., oceanic systems , plants ). Her 15 most recent publications span 2024–2016, covering topics from cell-free RNA diagnostics to circular RNA in disease . Key methodologies include DEEPEST for gene fusion detection and SQUICH for logarithmic molecular sampling. These works highlight her contributions to cancer biology and viral pandemic response . Scientific Awards include Arc Ignite Investigator (2023) NSF CAREER AWARD (2016) Alfred P. Sloan Research Fellow (2014) Baxter Faculty Scholar Award (2014) Salzman's funding history includes NIH Pathway to Independence and NSF grants . She mentors PhD and Master’s students through courses like BIOMEDIN 290 and BIODS 228 , while leading the Salzman Lab in advancing computational genomics and biological modeling .

Paul Segallمشاهده پروفایل

استاد

• Geophysics
• Seismology
• Volcanology
• +۷ مورد دیگر

Paul Segall is the Cecil H. and Ida M. Green Professor of Geophysics at Stanford University, specializing in active earthquake and volcanic processes through geodetic data analysis and physics-based modeling of crustal deformation. Education: Ph.D. in Geology, Stanford University (1981) M.S. in Earth Sciences, Case Western Reserve University (1976) B.S. in Earth Sciences, Case Western Reserve University (1976) His research integrates precise GPS positioning and InSAR measurements to invert deformation data for fault and magma chamber geometry, slip-rate variations, and dilation processes. Key focus areas include plate boundary dynamics (San Andreas, Cascadia, Japanese subduction zones), earthquake nucleation mechanisms, slow slip events, induced seismicity, and magma migration physics. Methodologies draw from solid and fluid dynamics to develop predictive hazard models. Recent publications (2023-2024) reveal intensive work on physics-based volcanic deformation modeling, caldera collapse earthquake mechanics, and dike propagation dynamics. These studies emphasize coupled processes (magma flow-fracture-elasticity interactions) and stress-driven seismicity patterns, with strong multi-institutional collaboration for model validation in volcanic hazard forecasting. Segall leads the Crustal Deformation and Fault Mechanics research group, which investigates strain accumulation between earthquakes for seismic hazard assessment and magma-induced surface inflation for eruption forecasting through integrated observational and theoretical approaches.

Keith C. Schwabمشاهده پروفایل

استاد

• Quantum science and technology
• Low temperature physics
• Superfluid physics
• +۴ مورد دیگر

Keith C. Schwab is a Professor of Applied Physics at the California Institute of Technology (Caltech). He holds a B.A. from the University of Chicago (1990) and a Ph.D. from the University of California, Berkeley (1996). Prior to his current position, he worked as a Senior Physicist at the National Security Agency (2000–2006) and was a Professor of Physics at Cornell University (2006–2009). His research focuses on quantum-limited measurements, ultra-low temperature physics, superfluid physics, quantum device development, and nanotechnology. Education: B.A. in Physics, University of Chicago, 1990 Ph.D. in Physics, University of California, Berkeley, 1996 Research Interests: Quantum-limited measurements and quantum devices Superfluid helium-4 interferometers and qubits Ultra-sensitive microwave measurement techniques Applications of 2D nanomaterials in quantum systems Quantum transduction between microwave and optical domains Recent work emphasizes developing Josephson junctions in superfluid helium-4 to create quantum devices like interferometers and qubits, leveraging advancements in 2D nanomaterials. His publications explore quantum squeezing, thermoelectric nanophotonics, and gravitational wave detection using superfluid systems. He has served as Fletcher Jones Foundation Co-Director of the Kavli Nanoscience Institute (2013–2015) and currently teaches the APh 114 Solid-State Physics course at Caltech. His research has been highlighted in news features such as Seeing Quantum Motion and Tricking the Uncertainty Principle . Labs/Teams: Active in quantum nanotechnology research groups at Caltech, focusing on experimental quantum systems and low-temperature physics.

Jianming Qianمشاهده پروفایل

استاد

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

Jianming Qian serves as the David M. Dennison Collegiate Professor of Physics at the University of Michigan, Ann Arbor, with primary laboratory facilities in the Homer A. Neal Laboratory (Room 2209). His office is located in West Hall, and he maintains active research leadership within the Department of Physics. Education: Ph.D. in Physics, Massachusetts Institute of Technology, 1991 B.S. in Physics, University of Science and Technology of China, 1985 Professor Qian's research centers on experimental elementary particle physics , with pioneering contributions spanning three major collider eras. He spearheaded the ATLAS collaboration's Higgs boson search in diphoton decay channels leading to its 2012 discovery, currently focusing on precision Higgs property measurements and beyond-Standard-Model physics including extended Higgs sectors, dark matter production, and heavy resonance searches at the LHC. His earlier work with the DØ experiment was instrumental in the top quark discovery at Fermilab's Tevatron, while L3 experiment contributions at CERN's LEP established the three-light-neutrino model. Analysis of his publication record reveals a consistent trajectory from foundational electroweak precision measurements (1989-1996) through heavy quark discoveries (1995-2008) to contemporary Higgs physics dominance (2012-2019). Recent work increasingly emphasizes multi-experiment synergy (ATLAS/CMS joint analyses) and future collider design (CEPC). Scientific Awards: No specific awards listed in source material Professor Qian has supervised numerous graduate students and postdoctoral researchers through major international collaborations, supported by continuous funding from agencies including the U.S. Department of Energy and National Science Foundation. His leadership in detector development (e.g., triangular scintillating strips technique) and physics analysis coordination demonstrates sustained technical innovation. He operates within the University of Michigan's high-energy physics group across Randall Laboratory and Homer A. Neal Laboratory facilities, maintaining active participation in the ATLAS collaboration's upgrade initiatives for the High-Luminosity LHC era while contributing to CEPC conceptual design studies.

• Social Sciences
• Sociology
• Development Studies
• +۳ مورد دیگر

Mariana Armond Dias Paes is a researcher affiliated with the BCDSS (Bonn Center for Dependency and Social Structure Studies) at the Universität Bonn. Her work focuses on interdisciplinary social science research, particularly addressing themes such as dependency dynamics, socioeconomic structures, globalization impacts, and inequality. She contributes to advancing theoretical and empirical understandings of structural dependencies in global and local contexts. While specific academic education details are not provided in the text, her affiliation with BCDSS suggests expertise in sociological and development studies. Research interests include economic sociology, globalization studies, and the interplay between social policies and inequality. Collaborations and institutional ties are implied through her position at the MPG email domain (Max Planck Society), though precise lab or team affiliations remain unspecified.

Cullen Blakeمشاهده پروفایل

دانشیار

• Astronomy
• Cosmology
• Exoplanet Detection
• +۶ مورد دیگر

Cullen Blake is an Associate Professor in the Department of Physics and Astronomy at the University of Pennsylvania School of Arts & Sciences. His primary research focuses on exoplanet detection around low-mass stars and the astrophysics of low-mass stars and brown dwarfs. He is deeply involved in observational astronomy, developing techniques to detect Earth-like planets and improving stellar characterization through precision radial velocity measurements and synoptic surveys. Blake plays a key role in projects like the NEID Earth Twin Survey and the Brown Dwarf Kinematics Project, leveraging instrumentation such as the NEID spectrograph and robotic telescopes. Education: Ph.D. (Astronomy) Harvard University (2009), A.M. (Astronomy) Harvard University (2006), A.B. (Astrophysics) Princeton University (2003). Research Interests: Search for Earth-like planets around low-mass stars Stellar astrophysics of low-mass stars and brown dwarfs Instrumentation development for exoplanet surveys Robotic telescopes and synoptic survey strategies Stellar activity mitigation in radial velocity data He has contributed to major collaborations including the APOGEE survey, the MINERVA telescope array, and the design of the NEID spectrometer. His work emphasizes bridging observational techniques and theoretical models to advance our understanding of planetary systems and stellar evolution. Key projects include the NEID Sun-as-a-Star program and the development of algorithms to reduce noise from telluric and stellar variability. Blake's research also extends to brown dwarf kinematics and the analysis of transient phenomena in stellar systems.

Tom Purdyمشاهده پروفایل

استادیار

• Quantum Optics
• Optomechanical Systems
• Quantum Sensors
• +۳ مورد دیگر

Tom Purdy is an Assistant Professor in the Department of Physics & Astronomy at the University of Pittsburgh, affiliated with the Dietrich School of Arts and Sciences. His research focuses on quantum optomechanics, leveraging quantum effects in light-matter interactions to advance measurement and metrology. Prior to his academic role, he worked at NIST (Quantum Optics Group) and held postdoctoral positions at JILA and UC Berkeley. He leads the PurdyLab, a quantum optics group specializing in quantum sensors and transducers. His educational background includes graduate studies at UC Berkeley and postdoctoral research at JILA. Key research areas include optomechanical systems, quantum thermometry, and photonic sensors. His lab's recent work explores applications in quantum-based vacuum metrology and room-temperature quantum systems. Dr. Purdy advises graduate students Shan Hao, Angad Gupta, and Mihir Khanna. His lab maintains a website at purdylab.org , highlighting ongoing projects and collaborations. Recent lab milestones include a 2024 Optica article on back-action evasion and Shan Hao's thesis defense in March 2024.

Danielle G. Lemayمشاهده پروفایل

دانشیار مدعو

• Nutrition
• Microbiome
• Dietary Components
• +۷ مورد دیگر

Danielle G. Lemay, Ph.D. is a Research Molecular Biologist at the USDA Agricultural Research Service's Western Human Nutrition Research Center (WHNRC) and an Associate Adjunct Professor affiliated with the University of California, Davis. She holds a position in the Diet, Microbiome and Immunity Research unit at WHNRC, where she conducts cutting-edge research at the intersection of nutrition, microbiome science, and computational biology. Dr. Lemay's primary research interests focus on how dietary components, especially fermentable carbohydrates, affect host response and whether these responses are modulated by the functional capabilities of resident microbiota. Her work prominently features the application of big data techniques, including sequencing technologies and machine learning, to understand the complex effects of diet on human health. A significant portion of her research examines human milk oligosaccharides, gut microbiota composition, and their interactions in both infants and adults. Her publication record demonstrates strong expertise in microbiome analysis, with numerous papers on metatranscriptome analysis pipelines (SAMSA and SAMSA2) that have become valuable tools in the field. Her research spans multiple disciplines including nutrition science, microbiology, computational biology, and molecular biology, with applications in neonatal nutrition, gut health, and precision nutrition approaches. Dr. Lemay has collaborated extensively with researchers at UC Davis and other institutions, particularly in the areas of milk composition, infant gut microbiome development, and the relationship between diet and microbial communities. Her work often bridges basic science with potential clinical applications, particularly in understanding how dietary components can be optimized for health benefits.

Jaime Llorcaمشاهده پروفایل

استاد پژوهشی

• Network Algorithms
• Network Optimization
• Distributed Control
• +۵ مورد دیگر

Jaime Llorca is a Research Professor at the New York University (NYU) Tandon School of Engineering's Electrical and Computer Engineering Department. He holds affiliations with NYU WIRELESS, a research center focused on 6G and beyond. His work bridges network algorithms, optimization, and distributed control with applications in edge computing, cloud networks, and content delivery. Prior roles include Senior Research Scientist at Nokia Bell Labs and positions at Alcatel-Lucent Bell Labs and the University of Maryland's Center for Networking of Infrastructure Sensors. Education: M.S. and Ph.D. in Electrical and Computer Engineering from the University of Maryland, College Park (MD). Research Focus: Llorca pioneers advancements in network-coded caching, distributed cloud control, and edge-cloud integration. Notable contributions include 'cache-aided coded multicasting' and 'cloud-network flow' frameworks. His work addresses latency constraints, resource allocation, and service orchestration in next-generation networks. Key Achievements: Over 100 peer-reviewed publications and 20 patents. Awarded the 2007 IEEE Sensors Best Paper Award, 2016 IEEE ICC Best Paper Award, and the 2015 Jimmy H.C. Lin Award for Innovation. Co-developed foundational technologies for content delivery and distributed cloud networks. Advising & Grants: Advises on distributed computing networks and edge-cloud systems. His research is supported by grants focused on 6G, network optimization, and IoT integration. Collaborates closely with NYU WIRELESS on projects like the Vineyard Digital Twin initiative leveraging UAV imaging. Labs & Teams: Active member of NYU WIRELESS, advancing 6G, mmWave/terahertz networks, and cross-layer network programmability. Leads teams exploring morphable networks and end-to-end service orchestration.

Jacqui Shawمشاهده پروفایل

استاد

• Liquid Biopsies
• Translational Cancer Genetics
• Molecular Diagnostics
• +۲ مورد دیگر

Professor Jacqui Shaw holds multiple leadership positions at the University of Leicester as Head of the Department of Genetics and Genome Biology, Co-Director of the Institute for Precision Health, and Professor of Translational Cancer Genetics. Her internationally recognized expertise focuses on developing blood-based 'liquid biopsy' tests for monitoring breast and lung cancers. Shaw's landmark research demonstrated that blood tests can detect breast cancer recurrence up to two years earlier than conventional methods, contributing to the FDA's 'Breakthrough Device' designation for Natera's Signatera™ test. During the COVID-19 pandemic, she established asymptomatic campus screening using LAMP technology to detect outbreaks. Her research group specializes in molecular diagnostics for precision oncology, maintaining extensive national and international clinical collaborations to advance cancer monitoring technologies.

Hans Martin Kjerمشاهده پروفایل

دانشیار

• Ultrasound Imaging
• Super-Resolution Imaging
• Biomedical Image Analysis
• +۷ مورد دیگر

Hans Martin Kjer is an Associate Professor in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU), where he is affiliated with the UltraSound and Biomechanics group within the Visual Computing Center and the Center for Fast Ultrasound Imaging. His research bridges engineering and medical imaging, with a strong emphasis on developing and validating advanced ultrasound techniques for biomedical applications. Research Interests: His work focuses on super-resolution ultrasound imaging, microvascular analysis, 3D reconstruction of biological structures, and image registration. He applies computational methods to improve the resolution and accuracy of ultrasound, particularly in renal and lymph node vasculature imaging. His research contributes to the UN Sustainable Development Goals in health and well-being through innovative diagnostic tools. Publication Trends: Over the past several years, Kjer has consistently published in high-impact journals and conferences in biomedical engineering and imaging. His recent work emphasizes the validation of super-resolution ultrasound against micro-CT, realistic 3D blood flow simulation, and the application of AI in enhancing imaging resolution. These studies reflect a strong trend toward quantitative, reproducible, and clinically relevant imaging solutions. Scientific Contributions: While no specific awards are listed, his leadership in major research projects and frequent collaborations with leading experts in ultrasound (e.g., Jørgen Arendt Jensen) underscore his significant role in the field. Advising and Funding: Kjer serves as a supervisor and principal investigator in several funded research initiatives, including AI for Extreme Super-Resolution CT , 3DIM: 3D Imaging Center , and QIM: Center for Quantification of Imaging Data from Max IV . He mentors PhD students and collaborates across disciplines, contributing to both biomedical and materials science imaging projects. Laboratories and Teams: He is an integral member of the Center for Fast Ultrasound Imaging and the Visual Computing Center at DTU. These teams focus on cutting-edge ultrasound technologies, image processing algorithms, and multimodal imaging integration, positioning Kjer at the forefront of computational biomedical imaging in Denmark.

Vincy Fonمشاهده پروفایل

استاد

• Law and Economics
• Applied Microeconomics
• Game Theory
• +۴ مورد دیگر

Vincy Fon is a Professor of Economics at The George Washington University, affiliated with the Department of Economics within the College of Arts and Sciences. Her academic work bridges economics and legal theory, with a strong focus on institutional design and international law. She has held influential positions as a program director at the National Science Foundation and as a consultant for the World Bank. Research Interests: Her primary research areas include law and economics, applied microeconomic theory, game theory, and the economic analysis of legal institutions. She investigates how legal rules shape behavior, the dynamics of treaty formation, and mechanisms for fair and efficient decision-making in legal and political contexts. Her theoretical work often incorporates strategic interaction and institutional incentives. Publication Trends: Her recent publications (2007–2011) reveal a consistent focus on the intersection of economics and law, particularly in contract theory, treaty law, and electoral systems. The body of work demonstrates a deep engagement with foundational legal institutions through rigorous economic modeling, with recurring themes of incentive alignment, rule design, and international cooperation. Professional Recognition: Program Director, National Science Foundation Consultant, World Bank Advising and Grants: While specific advisees are not listed, her leadership roles at the NSF suggest extensive involvement in guiding research funding and academic programs. Her consultancy with the World Bank indicates applied policy engagement, particularly in institutional and legal reforms. These roles reflect significant contributions beyond traditional teaching and research. Labs and Research Teams: Although no formal lab or research group is mentioned in the text, her publication record and professional affiliations suggest active collaboration in interdisciplinary research networks focused on law, economics, and international institutions.

Krishna Teja Chitty-Venkataمشاهده پروفایل

پژوهشگر

• Deep Learning
• Systems and Machine Learning
• Neural Network Optimization
• +۷ مورد دیگر

Krishna Teja Chitty-Venkata is a Postdoctoral Researcher at the Argonne Leadership Computing Facility (ALCF), Argonne National Laboratory, USA, where he works in the AI/ML team (formerly Data Science group). His research lies at the intersection of systems and machine learning, focusing on optimizing neural network training, finetuning, and inference on general-purpose and AI-specific hardware platforms. He is actively involved in AI for science applications and high-performance computing for AI (HPC for AI). Education: PhD in Computer Engineering, Iowa State University, 2017–2023 Bachelor of Engineering in Electronics and Communication Engineering, University College of Engineering, Osmania University, Hyderabad, India, 2013–2017 Research Interests: Krishna's research spans hardware-aware inference optimization of deep neural networks, enhancing training and finetuning of large language models (LLMs) and vision-language models (VLMs), neural architecture search (AutoML), pruning and quantization techniques, performance modeling, and AI for science. He is particularly interested in efficient adaptation methods such as LoRA-NAS integration, structured pruning (e.g., WActiGrad), and KV cache optimization (e.g., Paged Compression). Publication Trends: His recent work emphasizes benchmarking and optimization of LLMs on diverse AI accelerators (e.g., LLM-Inference-Bench), developing scalable frameworks for CNN and ViT evaluation (ConVision Benchmark), and advancing structured pruning and mixed-precision search methods. His publications span high-impact journals and conferences in computer science, AI, and systems, reflecting a strong focus on practical, hardware-aware solutions for deep learning efficiency. Scientific Contributions: Developed LLM-Inference-Bench for evaluating LLM performance across hardware and frameworks. Created ConVision Benchmark for standardized evaluation of CNNs and Vision Transformers. Proposed WActiGrad, a structured pruning method for efficient LLM finetuning and inference. Introduced Paged Compression for efficient KV cache management in vLLM. Designed LangVision-LoRA-NAS for optimizing VLMs via NAS-integrated adapters. Professional Experience and Advising: Krishna has been mentored by Prof. Arun K. Somani (Iowa State) and supervisors Murali Emani and Venkatram Vishwanath at Argonne. He has interned at AMD, Intel, and Argonne, contributing to deep learning optimization projects. While no formal students are listed, he has co-authored multiple papers with researchers and students, indicating collaborative advising. He has no publicly listed grants, but his work at Argonne is likely supported by institutional and DOE funding. Labs and Teams: He is part of the AI/ML team within the Argonne Leadership Computing Facility, a premier HPC and AI research division. His work involves close collaboration with teams developing AI accelerators and scientific applications, positioning him at the forefront of AI for science initiatives.