A5034729795- Particle physics theoretical and experimental studies
- High-Energy Particle Collisions Research
- Quantum Chromodynamics and Particle Interactions
- Dark Matter and Cosmic Phenomena
- Particle Detector Development and Performance
- Neutrino Physics Research
- Astrophysics and Cosmic Phenomena
- Computational Physics and Python Applications
- Cosmology and Gravitation Theories
- Gamma-ray bursts and supernovae
- Distributed and Parallel Computing Systems
- Pulsars and Gravitational Waves Research
- Black Holes and Theoretical Physics
- Scientific Computing and Data Management
- Radio Astronomy Observations and Technology
- Atomic and Subatomic Physics Research
- Research Data Management Practices
- Particle Accelerators and Free-Electron Lasers
- Radiation Detection and Scintillator Technologies
- Parallel Computing and Optimization Techniques
- Stochastic processes and financial applications
- Nuclear Physics and Applications
- Nuclear reactor physics and engineering
- Laser-Plasma Interactions and Diagnostics
- Random Matrices and Applications
University of California, San Diego
2023-2025
University of California System
2024-2025
University of California, Santa Barbara
2021-2025
A. Alikhanyan National Laboratory
2022-2024
Institute of High Energy Physics
2022-2024
University of Antwerp
2024
UC San Diego Health System
2024
University of Kansas
2022-2023
California Institute of Technology
2023
Pennsylvania State University
2014-2019
Abstract The findable, accessible, interoperable, and reusable (FAIR) data principles provide a framework for examining, evaluating, improving how is shared to facilitate scientific discovery. Generalizing these research software other digital products an active area of research. Machine learning models—algorithms that have been trained on without being explicitly programmed—and more generally, artificial intelligence (AI) models, are important target this because the ever-increasing pace...
Extreme data rate scientific experiments create massive amounts of that require efficient ML edge processing. This leads to unique validation challenges for VLSI implementations algorithms: enabling bit-accurate functional simulations performance in experimental software frameworks, verifying those models are robust under extreme quantization and pruning, ultra-fine-grained model inspection fault tolerance. We discuss approaches developing validating reliable algorithms at the such strict...
Recent cross-section measurements of top pair production, single-top and rare associated production by the CMS ATLAS collaborations are presented. These results include very first Run III at $\sqrt{s}$=13.6 TeV as well most precise inclusive differential top-quark cross sectional observations to date in II $\sqrt{s}$=13 TeV. This includes observation four-top both evidence tWZ production. diverse set showcase sensitive beyond historical expectations that driven improved analysis strategies...
The findable, accessible, interoperable, and reusable (FAIR) data principles serve as a framework for examining, evaluating, improving sharing to advance scientific endeavors. There is an emerging trend adapt these machine learning models—algorithms that learn from without specific coding—and, more generally, AI models, due AI’s swiftly growing impact on engineering sectors. In this paper, we propose practical definition of the FAIR models provide template program their adoption. We...
Extreme data rate scientific experiments create massive amounts of that require efficient ML edge processing. This leads to unique validation challenges for VLSI implementations algorithms: enabling bit-accurate functional simulations performance in experimental software frameworks, verifying those models are robust under extreme quantization and pruning, ultra-fine-grained model inspection fault tolerance. We discuss approaches developing validating reliable algorithms at the such strict...
The findable, accessible, interoperable, and reusable (FAIR) data principles provide a framework for examining, evaluating, improving how is shared to facilitate scientific discovery. Generalizing these research software other digital products an active area of research. Machine learning (ML) models -- algorithms that have been trained on without being explicitly programmed more generally, artificial intelligence (AI) models, are important target this because the ever-increasing pace with...
The standard model production of four top quarks is predicted to have a cross section the order 12fb. CMS Collaboration presents new results on this rare mechanism for Run 2 data collected in 2016 through 2018 at 13 TeV, considering event signatures containing zero electrons or muons. This first time all-hadronic channel investigated study quarks, made possible novel machine learning based data-driven background estimation techniques.