جست‌وجوی استاد و پژوهشگر

Syed Hani Hassan Abidiمشاهده پروفایل

دانشیار

• Virology
• Immunology
• Viral Oncology
• +۷ مورد دیگر

Syed Hani Hassan Abidi is an Associate Professor at the Department of Biomedical Sciences , School of Medicine , Nazarbayev University , Kazakhstan. His research integrates virology , immunology , viral oncology , and bioinformatics , with a focus on HIV molecular epidemiology , viral evolution , and drug resistance . He has led international projects across Pakistan, Kenya, Afghanistan, and Kazakhstan, and is recognized for innovative teaching and MOOC development. Education: PhD in Virology and Immunology Research Interests: His laboratory employs bioinformatics (machine learning, AI), genomics , and proteomics to study HIV phylodynamics , viral co-infections , and oncogenic viruses like EBV in prostate cancer. He also explores microbiome-immunity interactions and designs antiviral drugs/vaccines . Recent Research Trends: His 2025 publications emphasize COVID-19 immunopathology , HIV/syphilis epidemiology in Pakistan , and particle physics contributions via ATLAS , showcasing interdisciplinary impact. Awards & Recognition: Outstanding Teachers Award (2019, Aga Khan University) Fellowship of Higher Education (UK, 2022) Teaching & Grants: He pioneered Pakistan’s first MOOC on Computer-Based Drug Discovery (2014) and received a 2022 SoTL grant for MOOC-based molecular biology education. His teaching integrates animations , films , and flipped classrooms . Collaborations & Labs: Leads projects on HIV drug resistance , HCV genomics in Kazakhstan , and AI-driven dementia diagnostics (Kazakh Brain Atlas). His lab collaborates with global institutions to advance viral disease surveillance and therapeutic innovation .

Teruki Kamonمشاهده پروفایل

استاد

• Dark Matter
• Supersymmetry
• Particle Physics
• +۲ مورد دیگر

Teruki Kamon is a Professor at Texas A&M University affiliated with the Mitchell Institute for Fundamental Physics & Astronomy. As an active member of the CDF and CMS collaborations, he conducts experimental particle physics research at hadron colliders with focus on dark matter phenomenology. His research centers on testing particle physics models for cold dark matter, with Supersymmetry (SUSY) as a leading candidate. He pioneered SUSY searches in final states involving electrons, muons, and third-generation particles like tau leptons, specializing in: Compressed mass spectrum signatures Vector boson fusion topologies Soft tau lepton analyses Missing transverse momentum techniques Recent publications (2017-2020) demonstrate consistent leadership in LHC-based searches for supersymmetry and new physics, including unique contributions to CMS detector upgrades. His group dominates research on compressed-mass SUSY in vector boson fusion processes. No information regarding awards, student advising, or grant funding was provided in available sources.

Scott Hauckمشاهده پروفایل

استاد

• Reconfigurable Computing
• FPGA Architecture
• Quantum Computing Control
• +۵ مورد دیگر

Affiliation & Education Scott Hauck is a Professor at the University of Washington's Department of Electrical & Computer Engineering and an Adjunct Professor in Computer Science & Engineering. He leads the Adaptive Computing Machines and Emulators (ACME) Lab . He earned his BS in EECS from UC Berkeley (1990), and MS/PhD in CSE from the University of Washington (1992/1995). Research Focus Dr. Hauck specializes in FPGA-based reconfigurable computing with applications in: Quantum Computing: FPGA controllers for trapped-ion quantum systems enabling precise laser control and quantum state readout. Medical Imaging: Portable radiation sensors for personalized cancer therapy and PET scanner enhancements. High-Energy Physics: FPGA readout systems for ATLAS pixel detectors at CERN's Large Hadron Collider. AI Acceleration: Real-time machine learning inference for scientific applications via projects like hls4ml. His work bridges hardware innovation with computational physics, emphasizing real-time processing and low-latency systems. Publication Trends Recent research focuses on FPGA-accelerated machine learning for particle physics (e.g., transformer networks for LHC trigger systems) and quantum computing instrumentation. Earlier work established foundations in reconfigurable computing architectures and medical imaging electronics. Awards & Recognition Distinguished Teaching Award, University of Washington (2010) Advising & Funding Leads the ACME Lab with extensive funding from NSF, DARPA, NIH, DOE, and industry partners including Intel, Xilinx, and Microsoft. Mentored over 30 MS/PhD students in VLSI, reconfigurable systems, and scientific computing. Collaborations & Labs Directs the ACME Lab (EE1-307), collaborating with UW Radiology (Prof. Robert Miyaoka), UW Physics (Prof. Shih-Chieh Hsu), and Drexel University (Prof. Josh Agar). Projects include quantum control systems, LHC readout electronics, and medical sensor networks.

Serdar K. Gozpinarمشاهده پروفایل

دانشیار بالینی

• High Energy Physics
• Particle Physics
• Experimental Physics
• +۲ مورد دیگر

Serdar K. Gozpinar serves as a Clinical Associate Professor in the Department of Physics within the College of Arts and Sciences at the University at Buffalo, where he has been teaching faculty since 2013. His academic credentials include: Bachelor of Science in Electrical and Electronics Engineering from Baskent University (2006) Doctor of Philosophy in Experimental High Energy Physics from Brandeis University (2012) Professor Gozpinar specializes in experimental particle physics with deep involvement in the ATLAS collaboration at CERN's Large Hadron Collider. His research focuses on fundamental particle interactions and high-energy collision analysis, contributing to advancements in subatomic physics. His engineering background uniquely bridges theoretical physics with experimental instrumentation design. As a dedicated teaching faculty member, he delivers physics curriculum across undergraduate programs. His pedagogical approach integrates cutting-edge research methodologies with core physics principles, particularly in electromagnetism and quantum mechanics. The department leverages his CERN experience to provide students with real-world experimental physics perspectives.

Aram Harrowمشاهده پروفایل

استاد

• Quantum Information Science
• Quantum Algorithms
• Quantum Computing
• +۳ مورد دیگر

Aram Harrow is a Professor of Physics at the Massachusetts Institute of Technology (MIT) , affiliated with the MIT Center for Theoretical Physics and MIT Center for Quantum Engineering . He focuses on quantum information science and quantum algorithms , with additional interests in representation theory and optimization . His recent work explores quantum computing applications in chemical physics and statistical mechanics . Undergraduate and graduate degrees in Physics at MIT Faculty positions: MIT (2013-present), University of Washington (2010-12), University of Bristol (2005-10) Research Interests: His work bridges quantum information theory and many-body physics , including: Quantum algorithm design for chemistry and optimization Quantum circuit complexity and t-designs Entanglement dynamics in quantum systems Quantum-classical hybrid computing models Key Publications: Recent articles demonstrate quantum speedups for biomolecular free energy calculations , Hamiltonian simulation , and jet clustering algorithms . His research combines quantum complexity theory with practical implementations on near-term quantum devices. Scientific Awards: 2023 Simons Investigator 2018 APS Bennett Award 2017 IEEE Best Paper Award 2016 Kavli Frontiers Fellow Mentorship: He advises current PhD students Shankar Balasubramanian , Angus Lowe , and Norah Tan , with 12 former advisees including Anand Natarajan and Saeed Mehraban . His 2026 recruitment seeks one new graduate student.

André Rubbiaمشاهده پروفایل

استاد

• Neutrino Physics
• Astro-Particle Physics
• Dark Matter Detection
• +۳ مورد دیگر

Prof. Dr. André Rubbia is a Full Professor of Experimental Physics at ETH Zurich's Department of Physics, holding this position since December 2003 after serving as Associate Professor from 1998. His research spans neutrino physics, astro-particle physics, and dark matter detection through major international collaborations including CERN, Gran Sasso National Laboratory, and Fermilab. He currently serves as Co-Spokesperson for the billion-dollar DUNE neutrino project at Fermilab, managing over 900 scientists. His educational background includes: Diploma in Physics from the University of Geneva (1990), with thesis work on the L3 experiment at CERN's LEP accelerator Ph.D. in Physics from MIT (1993) under Nobel Laureate S.C.C. Ting, focusing on high-energy electron-positron collisions Rubbia's research centers on fundamental particle interactions, particularly neutrino oscillations and physics beyond the Standard Model. He pioneered liquid Argon Time Projection Chamber (LAr TPC) technology and dual-phase detection systems, enabling breakthroughs in neutrino mass measurements and dark matter searches. His work spans underground laboratories (Gran Sasso, Canfranc), the LHC's CMS detector, and neutrino beam experiments like T2K. Recent explorations include antimatter gravity tests, electron-positron bound states, and dark hidden sector searches. His 2025 publications reveal intense focus on neutrino oscillation parameter precision (T2K, Hyper-Kamiokande), FASER's LHC neutrino program, and DarkSide-20k dark matter detector development. Key themes include cross-section measurements, advanced detector technologies (SiPMs, emulsion tracking), and statistical methods for oscillation analysis, reflecting integration of theoretical modeling with cutting-edge instrumentation. Scientific recognition includes: Breakthrough Prize for Fundamental Physics (2016) awarded to the international team for discovering matter-anti-matter asymmetry in neutrino oscillations APS Viewpoint selection for editing the paper announcing first electron neutrino appearance at accelerators Rubbia has supervised over fifty PhD and Master's theses while securing substantial research funding as Principal Investigator for 20+ Swiss National Science Foundation projects and Coordinator of two EU FP7 Design Studies. His DUNE leadership involves complex international grant management across 30+ countries. He leads ETH Zurich's experimental particle physics group across multiple facilities: the ICARUS neutrino detector at Gran Sasso, CMS at CERN, DUNE at Fermilab, and DarkSide-20k for direct dark matter detection. His team developed the first underground ton-scale liquid argon detector and maintains collaborations with Japanese (Super-Kamiokande) and American (Fermilab) institutions.

Steven Hoekstraمشاهده پروفایل

دانشیار

• Atomic Physics
• Molecular Physics
• Stark Deceleration
• +۵ مورد دیگر

Prof. dr. Steven Hoekstra is an Associate Professor of Atomic and Molecular Physics at the University of Groningen's Faculty of Science and Engineering, within the Van Swinderen Institute. His research focuses on precision measurements using cold molecules to explore fundamental physics, including Stark deceleration, laser cooling, and searches for physics beyond the Standard Model. He leads the NL-eEDM program at Nikhef, investigating the electron's electric dipole moment. Hoekstra is also involved in educational innovation, having received the Teacher of the Year award (2020) and a Senior Teacher Qualification (2023). He has supervised over 11 PhD theses and currently mentors 5 students. His work combines experimental techniques with theoretical insights, addressing questions like symmetry violations and quantum dynamics. Key projects include manipulating BaF molecules with electrostatic fields and exploring levitated nanoparticles as sensors. Hoekstra has secured major grants, including NWO VICI (2022) and VIDI (2013), and collaborates internationally on projects like the European Strategy for particle physics. Recent articles highlight advancements in molecular beam control, spin-precession methods for EDM searches, and opportunities in radioactive molecules. He actively participates in the Physics Olympiad Netherlands as chair, contributing to science outreach and education.

Jens Jørgen Gaardhøjeمشاهده پروفایل

استاد

• High-Energy Physics
• Nuclear Physics
• Particle Physics
• +۳ مورد دیگر

Jens Jørgen Gaardhøje is a tenured Professor at the Niels Bohr Institute , University of Copenhagen, specializing in Experimental Particle Physics . He leads the Subatomic Physics Division and directs the Danish National Center for CERN Research (NICE) . He is a member of the management board of the ALICE experiment at CERN's Large Hadron Collider (LHC). Born in 1954 (Hørsholm, Denmark) Dr. Scient. (1993, University of Copenhagen) Cand. Scient. (1980, Niels Bohr Institute, UCPH) Baccalaureat (1972, Lyçée Français Charles Lepierre, Lisbon, Portugal) His research focuses on high-energy nuclear reactions , progressing from MeV to TeV scales. He pioneered studies on Giant Resonances and co-founded the BRAHMS experiment at RHIC (1997-2010), establishing the Quark Gluon Plasma (sQGP) . Currently, he leads the Forward Multiplicity Detector project for ALICE at LHC, advancing understanding of particle production and collective properties of sQGP. His work spans quark-gluon dynamics , heavy ion collisions , and detector development . Recent publications highlight ALICE experiment studies at LHC, including femtoscopy in pp collisions, direct photon production , hypernuclei , and J/ψ correlations . These articles emphasize quark-gluon plasma , strange baryons , and ultra-peripheral collision analyses. Scientific Awards : Knight of the Order of Dannebrog, Chevalier des Palmes Académiques, Professor Honoris Causa (University of Bucharest), Top 5 in Science in Denmark (Ingeniørens Ugeblad), Fellow of the Danish Academy of Natural Science Grants & Leadership : Over 300 MDKK in career funding, Exec-chair of CERN-UP , Founder of L’Oréal-UNESCO-KDVS Women in Science Prize International Roles : Vice-president of CERN Council, Member of Science Europe Advisory Board, Chair of ESFRI PSE Strategic Working Group He has supervised 24 PhD , 21 MSc , and 24 postdocs , and organized numerous international conferences on nuclear, particle, and societal impacts of science.

Carlos Cinelliمشاهده پروفایل

استادیار

• Causal Inference
• Statistical Methodology
• Machine Learning
• +۵ مورد دیگر

Carlos Cinelli is an Assistant Professor in the Department of Statistics at the University of Washington, where he conducts research at the intersection of causal inference, statistical methodology, machine learning, and artificial intelligence. He is also a data science fellow at the eScience Institute and affiliate faculty of the Center for Statistics and the Social Sciences, demonstrating his interdisciplinary approach to causal methodology. Dr. Cinelli received his Ph.D. in Statistics from the University of California, Los Angeles, advised by Chad Hazlett and Judea Pearl, two prominent figures in causal inference. His research focuses on developing new causal and statistical methods for transparent and robust causal claims in empirical sciences, with particular attention to challenges faced by social and health scientists. His work spans theoretical developments in causal identification, sensitivity analysis frameworks, and practical software implementations that enable researchers to assess the robustness of their causal conclusions. Cinelli's research program addresses fundamental questions about how unobserved confounding affects causal estimates and develops tools to quantify how sensitive findings are to potential violations of causal assumptions. His work on omitted variable bias frameworks has been particularly influential across multiple disciplines. Through his publications, Cinelli has established himself as a leading researcher in causal inference methodology, with papers appearing in top journals across statistics, machine learning, epidemiology, and social sciences. His work demonstrates both theoretical rigor and practical relevance, often accompanied by open-source software implementations that make his methods accessible to applied researchers. Best paper award at SBE 2024 in Econometrics Royalty Research Fund (RRF) Award recipient NSF/MMS research support As an advisor, Cinelli has successfully guided PhD students like Nick Irons to dissertation completion. He actively seeks new students with strong interests in causal inference. His research is supported by multiple funding sources including the National Science Foundation and the University of Washington's Royalty Research Fund. Cinelli contributes to the academic community through editorial work for the Journal of Causal Inference and by developing widely used software packages like sensemakr for sensitivity analysis.

Matej Vargaمشاهده پروفایل

پژوهشگر

• Geodesy
• Geomatics
• Physical Geodesy
• +۷ مورد دیگر

Matej Varga is a Scientific Assistant and Postdoctoral Researcher at ETH Zurich's Department of Civil, Environmental and Geomatic Engineering, working in the Geosensors and Engineering Geodesy group under Prof. Andreas Wieser since 2021. His research spans geometrical geodesy, physical geodesy, and satellite geodesy, with applications in both theoretical and practical domains. Dr. Varga's research interests focus on spatial, temporal and spectral analysis of geodetic data, with particular expertise in geodetic reference systems and frames, gravity and geomagnetic field modeling at all temporal and spatial scales, and multi-GNSS multi-frequency positioning and monitoring. His work integrates geometrical and physical aspects of geodesy to address complex Earth observation challenges, particularly in infrastructure monitoring and geophysical applications. His recent publications demonstrate a strong trend toward high-precision geodetic applications for major scientific infrastructure, most notably the Future Circular Collider project, alongside important contributions to earthquake impact analysis, geomagnetic network development, and gravity field modeling. His research bridges traditional geodetic methods with modern computational approaches, including machine learning applications for point cloud registration. Dr. Varga is actively involved in the GSEG research group at ETH Zurich, contributing to the development of geodetic infrastructure and reference systems. His work has practical applications in infrastructure monitoring, earthquake analysis, and scientific projects requiring extreme geodetic precision.

Louise Willingaleمشاهده پروفایل

دانشیار

• Laser-plasma interaction at relativistic intensities
• Ion acceleration with intense lasers
• High-energy-density physics
• +۳ مورد دیگر

Dr. Louise Willingale is an Associate Professor in the Department of Electrical Engineering and Computer Science at the University of Michigan. Specializing in high-intensity laser-plasma interactions, she leads experimental research at facilities including the ZEUS laser system and OMEGA EP. Her work combines experimental diagnostics with numerical modeling to advance understanding of relativistic plasma physics and ion acceleration mechanisms. Education: PhD in Physics from Imperial College London (2007) Research Focus: Investigates relativistic laser-plasma interactions through ion acceleration, magnetic field generation, and direct laser acceleration of electrons. Her work spans underdense/near-critical density plasmas, shock formation physics, and extreme electromagnetic field generation in laboratory astrophysics contexts. Recent Publication Trends: 2024-2025 studies emphasize ZEUS laser facility development, optimization of acceleration mechanisms (direct laser acceleration, wakefield acceleration), and magnetic field dynamics in multi-PW laser-solid interactions. Common subfields include collisionless shocks, radiation-driven plasma instabilities, and advanced diagnostics for relativistic charge particles. Labs & Collaborations: Affiliated with the Center for Ultrafast Optical Science (CUOS) and the Center for High-Energy-Density Laboratory Astrophysics Research (CHEDAR), working closely with the ZEUS laser facility team.

Pierre Baldiمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Bioinformatics
• +۷ مورد دیگر

Pierre Baldi is a Distinguished Professor of Computer Science and Director of the Institute for Genomics and Bioinformatics at the University of California, Irvine (UCI). He is affiliated with the Donald Bren School of Information and Computer Sciences. His research spans artificial intelligence, machine learning, bioinformatics, and communication networks, with notable projects in protein structure prediction, gene expression modeling, and neutrino physics collaborations like DUNE. Baldi’s work bridges theoretical foundations (e.g., neural network theory) and applied domains, including medical imaging and fusion technology. Key research interests include AI-driven biomedical applications, neural network theory, and interdisciplinary projects such as the DUNE neutrino experiment. His contributions to neural network engineering were recognized with the 2023 INNS Dennis Gabor Award, highlighting his paradigm-changing impact on computational neuroscience and physics. Baldi’s academic leadership includes directing UCI’s Institute for Genomics and Bioinformatics, fostering collaborations in computational biology and AI. His recent work explores AI’s role in healthcare, climate modeling (e.g., ClimSim-Online), and fundamental physics challenges like neutrino oscillation studies.

Jennifer Dyمشاهده پروفایل

استاد

• Machine Learning
• Computer Vision
• Explainable AI
• +۲ مورد دیگر

Jennifer Dy is a Distinguished Professor at Northeastern University with joint appointments in Electrical and Computer Engineering and Khoury College of Computer Sciences. As Director of AI Faculty at the Institute for Experiential AI, she leads research in machine learning, computer vision, and explainable AI. Her work spans biomedical applications (COPD phenotyping, neuroimaging) and fundamental algorithms (active learning, continual learning). She holds a PhD from Purdue University and is an AAAI Fellow. Research Focus: Dy develops methodologies for robust and interpretable machine learning, including techniques for model stability in continual learning, dependency-aware active learning, and axiomatic explanation frameworks. Her applied research advances diagnostic tools using Raman spectroscopy, CT imaging, and multi-omics biomarker discovery. Awards: Recognized with the NSF CAREER Award, Faculty Research Team Award, and AAAI Fellowship for contributions to unsupervised learning and medical AI. Publication Trends: Recent articles demonstrate strong cross-disciplinary integration, combining theoretical advances in explainability/robustness with applications in healthcare, wireless systems, and particle physics. Methodological themes include optimal transport theory, probabilistic modeling, and transformer architectures.

• Plasma Physics
• Laser-Plasma Acceleration
• Nanomaterials in Accelerators
• +۳ مورد دیگر

Aakash Sahai is an Assistant Research Professor in the CEDC-Electrical Engineering department at the University of Colorado Denver - Denver Campus. His research focuses on advancing plasma physics, laser-plasma interactions, and nanoplasmonic technologies for high-energy particle acceleration. He is actively involved in designing novel accelerator concepts, such as nanostructure-based plasmonic accelerators capable of achieving extreme electric fields (PetaVolts/meter). His work bridges theoretical, computational, and experimental approaches to address challenges in high-gradient acceleration, plasma wakefields, and extreme nanoscience. Key research interests include laser-driven plasma acceleration, plasmonic field enhancement in nanostructures, and applications of particle beams in medical and high-energy physics. He collaborates on projects like the EuPRAXIA design study, aiming to develop compact, cost-efficient particle sources. His contributions span experimental setups, computational modeling, and innovative methodologies for radio transmission through plasmas and particle beam processing. Notable achievements include pioneering studies on relativistic surface plasmons, PetaVolt plasmonics, and optimizing laser-plasma interactions for proton/ion acceleration. His research has implications for next-generation accelerators, compact X-ray sources, and advanced plasma diagnostics. Sahai’s interdisciplinary approach integrates electrical engineering, material science, and high-energy physics to push the boundaries of accelerator technology. Advising and grants: No formal advisees or grant details listed. His work is supported by collaborations and institutional resources, including participation in national and international initiatives like Snowmass workshops. Labs/Teams: Active contributor to the EuPRAXIA consortium and affiliated with plasma physics and accelerator research groups at University of Colorado Denver.

Jesse Liuمشاهده پروفایل

استادیار

• Particle Physics
• High Energy Physics
• Dark Matter
• +۵ مورد دیگر

Jesse Liu is an Assistant Professor of Physics at the New York University College of Arts & Science , joining in Spring 2025. He collaborates with the ATLAS Experiment at CERN and leads the NYU Experimental Particle Physics group. Research Interests: Liu's work bridges fundamental particle physics and detector innovation. He investigates Tau-lepton electromagnetic dipoles via photon collisions at the LHC High-luminosity LHC silicon tracker upgrades Dark matter searches through collider experiments and the BREAD axion detection project Cosmic ray physics using ATLAS data Recent Publications focus on tau magnetic moment measurements, detector thermal stress mitigation, and cosmic ray signature analysis. His work has been featured in Phys. Rev. D , Phys. Rev. Lett. , and JINST . Outreach & Mentorship: Liu actively engages in public science communication through Pint of Science talks The Conversation articles School visits to CERN First-gen student mentorship at NYU CU*iP Contact: Office at 726 Broadway, Room 852, New York City. Email: jesse.liu2@nyu.edu