A5101715118- Particle physics theoretical and experimental studies
- High-Energy Particle Collisions Research
- Quantum Chromodynamics and Particle Interactions
- Particle Detector Development and Performance
- Computational Physics and Python Applications
- Scientific Computing and Data Management
- Distributed and Parallel Computing Systems
- Advanced Data Storage Technologies
- Medical Imaging Techniques and Applications
- Cosmology and Gravitation Theories
- Dark Matter and Cosmic Phenomena
- Cancer Genomics and Diagnostics
- AI in cancer detection
- Cloud Computing and Resource Management
- Parallel Computing and Optimization Techniques
- Research Data Management Practices
- Breast Cancer Treatment Studies
- Neutrino Physics Research
- Astrophysics and Cosmic Phenomena
- Radiomics and Machine Learning in Medical Imaging
- Genetic factors in colorectal cancer
- Machine Learning in Materials Science
- Nuclear Physics and Applications
- Breast Lesions and Carcinomas
- Molecular Biology Techniques and Applications
University of Chicago
2018-2024
Cancer Genetics (United States)
2021-2024
Fermi National Accelerator Laboratory
2020-2023
University of Illinois Chicago
2019-2022
University of Notre Dame
2014-2022
Argonne National Laboratory
2010-2019
High-level programming languages such as Python are increasingly used to provide intuitive interfaces libraries written in lower-level and for assembling applications from various components. This migration towards orchestration rather than implementation, coupled with the growing need parallel computing (e.g., due big data end of Moore's law), necessitates rethinking how parallelism is expressed programs. Here, we present Parsl, a scripting library that augments simple, scalable, flexible...
Gene expression-based recurrence assays are strongly recommended to guide the use of chemotherapy in hormone receptor-positive, HER2-negative breast cancer, but such testing is expensive, can contribute delays care, and may not be available low-resource settings. Here, we describe training independent validation a deep learning model that predicts assay result risk using both digital histology clinical factors. We demonstrate this approach outperforms an established nomogram (area under...
While the Machine Learning (ML) landscape is evolving rapidly, there has been a relative lag in development of "learning systems" needed to enable broad adoption. Furthermore, few such systems are designed support specialized requirements scientific ML. Here we present Data and Hub for science (DLHub), multi-tenant system that provides both model repository serving capabilities with focus on applications. DLHub addresses two significant shortcomings current systems. First, its self-service...
Exploding data volumes and velocities, new computational methods platforms, ubiquitous connectivity demand approaches to computation in the sciences. These must enable be mobile, so that, for example, it can occur near data, triggered by events (e.g., arrival of data), offloaded specialized accelerators, or run remotely where resources are available. They also require design which monolithic applications decomposed into smaller components, that may turn executed separately on most suitable...
Abstract Black women across the African diaspora experience more aggressive breast cancer with higher mortality rates than white of European ancestry. Although inter-ethnic germline variation is known, differential somatic evolution has not been investigated in detail. Analysis deep whole genomes 97 cancers, RNA-seq a subset, from Nigeria comparison The Cancer Genome Atlas (n = 76) reveal rate genomic instability and increased intra-tumoral heterogeneity as well unique subtype defined by...
funcX is a distributed function as service (FaaS) platform that enables flexible, scalable, and high performance remote execution. Unlike centralized FaaS systems, decouples the cloud-hosted management functionality from edge-hosted execution functionality. funcX's endpoint software can be deployed, by users or administrators, on arbitrary laptops, clouds, clusters, supercomputers, in effect turning them into serving systems. provides single location for registering, sharing, managing both...
To externally evaluate a mammography-based deep learning (DL) model (Mirai) in high-risk racially diverse population and compare its performance with other mammographic measures. A total of 6435 screening mammograms 2096 female patients (median age, 56.4 years ± 11.2 [SD]) enrolled hospital-based case-control study from 2006 to 2020 were retrospectively evaluated. Pathologically confirmed breast cancer was the primary outcome. Mirai scores predictors. Breast density Imaging Reporting Data...
Python is increasingly the lingua franca of scientific computing. It used as a higher level language to wrap lower-level libraries and compose scripts from various independent components. However, scaling moving programs laptops supercomputers remains challenge. Here we present Parsl, parallel scripting library for Python. Parsl makes it straightforward developers implement parallelism in by annotating functions that can be executed asynchronously parallel, scale analyses laptop thousands...
The ${}^{30}$S($\ensuremath{\alpha},\phantom{\rule{-0.16em}{0ex}}p$)${}^{33}$Cl reaction may have a significant impact on final elemental abundances and energy output of type I X-ray bursts, as well influencing observables such double-peaked luminosity profiles, because it could bypass the ${}^{30}$S waiting point. This has been studied experimentally for first time in inverse kinematics via time-inverse ${}^{1}$H(${}^{33}$Cl,${}^{30}$S)$\ensuremath{\alpha}$ with ${}^{33}$Cl radioactive ion...
Growing data volumes and velocities are driving exciting new methods across the sciences in which analytics machine learning increasingly intertwined with research. These require approaches for scientific computing computation is mobile, so that, example, it can occur near data, be triggered by events (e.g., arrival of data), or offloaded to specialized accelerators. They also design monolithic applications decomposed into smaller components, that may turn executed separately on most...
The CMS Remote Analysis Builder (CRAB) is a distributed workflow management tool which facilitates analysis tasks by isolating users from the technical details of Grid infrastructure. Throughout LHC Run 1, CRAB has been successfully employed an average 350 distinct each week executing about 200,000 jobs per day.
The variety of instance types available on cloud platforms offers enormous flexibility to match the requirements applications with resources. However, selecting most suitable type and configuring an application optimally execute that can be complicated time-consuming. For example, parallelism flags must cores problem sizes tuned memory. As search space configurations enormous, we propose automated approach, called ParaOpt, automatically explore tune arbitrary instances. ParaOpt supports...
Abstract Gene expression-based recurrence assays are strongly recommended to guide the use of chemotherapy in hormone receptor-positive, HER2-negative breast cancer, but such testing is expensive, can contribute delays care, and may not be available low-resource settings. Here, we describe training independent validation a deep learning model that predicts assay result risk using both digital histology clinical factors. We demonstrate this approach outperforms an established nomogram (area...
In this paper we introduce the Data and Learning Hub for Science (DLHub). DLHub serves as a nexus publishing, sharing, discovering, reusing machine learning models. It provides flexible publication platform that enables researchers to describe deposit models by associating model-specific metadata assigning persistent identifier subsequent citation. also supports scalable model inference, allowing execute inference tasks using distributed execution engine, containerized models, Kubernetes....
The reproducibility of scientific results increasingly depends upon the preservation computational artifacts. Although preserving a computation to be used later sounds easy, it is surprisingly difficult due complexity existing software and systems. Implicit dependencies, networked resources, shifting compatibility all conspire break applications that appear work well. To investigate these issues, we present case study complex high energy physics application. We analyze application attempt...
Publishing scientific results without the detailed execution environments describing how were collected makes it difficult or even impossible for reader to reproduce work. However, configurations of are too complex be described easily by authors. To solve this problem, we propose a framework facilitating conduct reproducible research tracking, creating, and preserving comprehensive with Umbrella. The includes lightweight, persistent deployable environment specification, an engine which...
Hundreds of physicists analyze data collected by the Compact Muon Solenoid (CMS) experiment at Large Hadron Collider using CMS Remote Analysis Builder and global pool to exploit resources Worldwide LHC Computing Grid. Efficient use such an extensive expensive resource is crucial. At same time, collaboration committed minimizing time insight for every scientist, pushing fewer possible access restrictions full sample supports free choice applications run on computing resources. Supporting...
The high energy physics (HEP) community relies upon a global network of computing and data centers to analyze produced by multiple experiments at the Large Hadron Collider (LHC). However, this does not satisfy all research needs. Ambitious researchers often wish harness resources that are integrated into network, including private clusters, commercial clouds, other production grids. To enable these use cases, we have constructed Lobster, system for deploying intensive throughput applications...
The computing needs of high energy physics experiments like the Compact Muon Solenoid experiment at Large Hadron Collider currently exceed available dedicated computational resources, hence motivating a push to leverage opportunistic resources. However, access resources faces many obstacles, not least which is making complex software stack typically associated with such computations. This paper describes framework constructed using existing packages distribute needed without need for job...