• University of California San Francisco
  • UCSF Medical Center
  • Search UCSF
  • About UCSF

Bakar Institute

Generic selectors
Exact matches only
Search in title
Search in content
person
page
post
tribe_events
  • ABOUT
    • Mission & Vision
    • Contact
  • RESEARCH
  • PEOPLE
    • Faculty
    • Staff
  • RESOURCES
  • EDUCATION
  • EVENTS
  • NEWS
You are here: Home / Archives for Karen

March of Dimes Launches New Data-Focused Prematurity Research Center at UCSF

March of Dimes Launches New Data-Focused Prematurity Research Center at UCSF
Source: March of Dimes
June 23, 2022

BCHSI faculty Marina Sirota et al will focus on data sharing, computational drug discovery, leveraging real world data to help prevent preterm birth.

Read Article

New Biomarker Classifications May Improve Treatment for High-Risk Breast Cancer Patients

New Biomarker Classifications May Improve Treatment for High-Risk Breast Cancer Patients
Source: UCSF
June 3, 2022

BCHSI faculty Laura van’t Veer & team findings will guide treatment prioritization.

Read Article

Peterson, Thomas

June 2, 2022 By Karen

Thomas A. Peterson, PhD

Digital and Computational Health Science

Application of statistical and computational methodologies to prospective and retrospective clinical datasets for finding meaningful statistical associations and creating state-of-the-art tools for precision medicine

Two Artificial Intelligence / Machine Learning Demonstration Projects Awarded

Two Artificial Intelligence / Machine Learning Demonstration Projects Awarded
Source: Bakar Institute
May 31, 2022

BCHSI, CTSI and UC Health award two AI/Machine Learning Demo Pilot projects.

Read Article

Towards Continual Monitoring & Updating AI algorithms in Healthcare

Towards Continual Monitoring & Updating AI algorithms in Healthcare
Source: Nature
May 31, 2022

Jean Feng, Romain Pirracchio, et al published on Quality Improvement for Clinical AI.

Read Article

UCSF Awarded $67.5 Million to Develop New Antiviral Therapies

UCSF Awarded $67.5 Million to Develop New Antiviral Therapies
Source: UCSF
May 18, 2022

BCHSI Faculty, Andrej Sali, Brian Shoichet, Michael Keiser, are investigators for this QBI Coronavirus Research Group.

Read Article

Informations Commons Day at UCSF

UCSF Information Commons Day
Source: Bakar Institute
April 28, 2022

As researchers who depend on data, join us on Monday, May 9 to learn how to deepen your research inquiry.

See Details

UCSF Researchers Use Gene Expression Data to Map Cell Types in the CNS

UCSF Researchers Use Gene Expression Data to Map Cell Types in the CNS
Source: Bakar Institute
April 12, 2022

Ashish Raj co-led the development of a computational pipeline, Matrix Inversion and Subset Selection.

Read Article

Single-Cell Seq Study Uncovers Blood Cell Type Features for Lupus

Single-Cell Seq Study Uncovers Blood Cell Type Features for Lupus
Source: Science
April 8, 2022

Jimmie Ye, et al, published in Science on how they deployed mux-seq to profile 1.2M immune cells for lupus.

Read Article

Olshen, Adam

April 8, 2022 By Karen

Adam B. Olshen, PhD

Developing tools for the analysis of genomic data and identifying biomarkers in cancer

Dr. Olshen has helped develop tools in such area as DNA copy number, mutation hotspot detection, and integration of data from multiple genomic assays. He is currently developing biomarkers to predict cancer outcomes in pediatric cancers.

A Biomedical Open Knowledge Network Harnesses the Power of AI

A biomedical open knowledge network harnesses the power of AI
Source: AI Magazine
March 31, 2022

Sharat Israni, et al and collaborators publish on knowledge networks identified by NSC as a core component of AI frameworks.

Read Article

Rudrapatna, Vivek

January 10, 2022 By Karen

Vivek Rudrapatna, MD, PhD

The Real-World Evidence Laboratory

Our group uses a variety of machine learning and biostatistical methods, such as natural language processing, deep learning, and causal inference, to transform electronic health records data into real-world evidence on treatment effects.

Atul Butte Testifies before Congress

Atul Butte Congressional Testimony
Source: Bakar Institute
December 8, 2021

Butte articulated priorities to Energy & Commerce Subcommittee on Health “Future of Biomedicine” Hearing.

Read Article

An Entirely New Approach to Drug Discovery for AD

An Entirely New Approach to Drug Discovery for AD
Source: Bakar Institute
November 17, 2021

UCSF BCHSI data scientist’s research draws attention to an entirely new approach to drug discovery for Alzheimer’s.

Read Article

Precision Medicine to Address Prostate Cancer in Veterans

Franklin Huang, MD, PhD
Source: Bakar Institute
November 16, 2021

Franklin Huang: Providing precision oncology solutions for veterans using data science and focusing on disparities.

Read Article

Could an antidepressant prevent more COVID deaths?

Could an antidepressant prevent more COVID deaths?
Source: UCSF
November 15, 2021

A UCSF-Stanford data analysis shows a strong association between taking SSRIs and surviving the virus.

Read Article

Lazar, Ann

November 3, 2021 By Karen

Ann A. Lazar, PhD

Biostatistics, Data Science and Precision Health

Dr. Lazar’s research focuses on biostatistics, data science and precision health. She has secured grant funding as PI from NIH, foundations and the University of California Office of the President, including grants for the HBCU initiative.

Computational Precision Health Program Funded by $50M Gift Launches

Ida Sim, MD, PhD
Source: UCSF
October 20, 2021

Ida Sim, MD, PhD and new UCSF program faculty will be affiliated with the BCHSI.

Read Article

Disparities Research in Chronic Diseases with $22.5M Grant

Stuart Gansky, MS, DrPh and William Brown III, PhD, DrPH
Source: UCSF
October 18, 2021

Stuart Gansky, MS, DrPh, co-director, and William Brown III, PhD, DrPH as associate unit director.

Read Article

Can an Already Approved Drug Treat Alzheimer’s Disease?

Marina Sirota, PhD
Source: Gladstone Institutes
October 11, 2021

Marina Sirota, PhD (co-senior author) published a study using computation to pinpoint an existing drug that may prevent Alzheimer’s Disease.

Read Article

Operational Excellence

Operational Excellence

August 31, 2021 By Karen

Optimize and sustain delivery of BCHSI programs and services through implementation of best practices that promote efficiency, effectiveness, and quality.

Policy & Advocacy

Policy & Advocacy

August 31, 2021 By Karen

Champion the benefits and potential impact of computational health sciences; advocate priorities to advance the field; and promote data-driven solutions to key challenges faced by UCSF, UC Health and the […]

Training

Training

August 31, 2021 By Karen

Train and educate innovators and thought leaders in computational health sciences at UCSF.

People

August 31, 2021 By Karen

Attract, nourish and retain the best talent, reflecting the rich diversity of our global community, to enable research in UCSF departments while providing a home to data-driven thought leaders and […]

Knowledge Assets

Knowledge Assets

August 31, 2021 By Karen

Develop and enable safe and respectful access to the latest AI tools and relevant data assets of interest to all researchers in UCSF and beyond, while remaining attentive to social […]

Research

Research

August 31, 2021 By Karen

Build and apply tools and methods in computational science to advance the field and support research in biomedical disciplines, with a focus on advancing equitable precision medicine.

UCSF SPOKE featured at NSF Convergence Accelerator Expo

Source: Bakar Institute
July 6, 2021

Learn about UCSF’s knowledge network project and other innovative work supported by NSF Convergence Accelerator.

Watch Video

AIMBE honors two Bakar Faculty

AIMBE
Source: Bakar Institute
March 19, 2021

Katie Pollard and Duan Xu are inducted into the prestigious American Institute for Medical and Biological Engineering College of Fellows.

Read Article

Kornblith, Aaron

February 12, 2021 By Karen

Aaron Kornblith, MD

Accurate and Consistent Advanced Diagnostic Strategies for Injured Children

Dr. Kornblith is focused on novel diagnostic strategies to enhance the care of injured children. He uses
a modern data science framework to develop accurate, consistent, and interpretable advanced analytic
models for rapid detection of intra-abdominal bleeding using clinical decision rules, computer vision,
and device design.

Fragiadakis, Gabriela

February 10, 2021 By Karen

Gabriela K. Fragiadakis, PhD

Characterizing immune organization and patient immune state using single-cell methods

Dr. Fragiadakis’s research focuses on analyzing immune state in diverse sets of patient cohorts using high-dimensional single-cell technologies, including single-cell sequencing and CyTOF. She uses multi-modal data integration methods to evaluate patient differences and infer broader principles of immune organization.

Semere, Wagahta

February 10, 2021 By Karen

Wagahta Semere, MD, MHS

Promoting Quality and Safety by Engaging Diverse Diabetes Patients and their Caregivers in Secure Messaging

Dr. Semere is using machine learning and novel computational linguistics techniques to characterize secure message communication between racially/ethnically diverse patients with diabetes, their caregivers, and providers. She is applying this information to develop family-centered technology based communication strategies that promote effective diabetes management.

Spitzer, Matthew

February 2, 2021 By Karen

Matthew H. Spitzer, PhD

Systems approaches to understand immune responses, particularly to cancer

We focus on understanding how the immune system coordinates responses with an emphasis on tumor immunology. We combine experimental and computational methods to understand how the immune system responds to tumors and to rationally initiate curative immune responses against cancer.

Feng, Jean

February 2, 2021 By Karen

Jean Feng, PhD

Developing reliable and interpretable machine learning algorithms for clinical decision making

Dr. Feng has developed machine learning and deep learning algorithms that accurately quantify their uncertainty and are appropriate for high dimensional datasets. Her current research is in developing safe machine learning algorithms that learn and recalibrate using streaming Electronic Health Records data.

Wesson, Paul Douglas

February 2, 2021 By Karen

Paul Douglas Wesson, PhD

The science for the last mile: Enhanced epidemiologic surveillance to accelerate HIV elimination

The objective of this NIAID-funded K01 award is to identify the residual drivers of HIV infection in Fast Track cities. Methods from semi-parametric
statistical modeling, HIV phylogenetics, and minority stress theory will be used to augment surveillance data.

Spetz, Joanne

December 16, 2020 By Karen

Joanne Spetz, PhD

Health workforce and the organization and delivery of healthcare services

Dr. Spetz uses econometric and mixed methods to study the organization of the health workforce and delivery of healthcare services, primarily with large secondary and survey-based datasets.

Sarkar, Urmimala

December 16, 2020 By Karen

Urmimala Sarkar, MD, MPH

Innovating for Health Equity

Dr. Sarkar’s research focuses on: (1) Ambulatory patient safety, (2) Digital health innovations to improve the safety and quality of outpatient care, (3) Social media research for behavior change, (4) Safety-net implementation of evidence-based digital health in real-world settings.

Hswen, Yulin

September 2, 2020 By Karen

Yulin Hswen, ScD

Social and Computational Epidemiology

Dr. Hswen current research seeks to identify authentic attitudes, feelings and beliefs that influence behaviors and drive populations. Through the collection of unconventional and underground online social networks, Dr. Hswen captures unfiltered conversations to further understand the connections between social experiences and health.

Yao, Keluo

September 2, 2020 By Karen

Keluo Yao, MD

Improving Research and Operational Software for Laboratory Medicine

Pathology and laboratory medicine provide 70% of the information in most patient care settings. Therefore, using the best software is the best way to deliver that information to the clinicians on the front lines. I am interested in developing these software solutions by utilizing the best practices from the cutting edge artificial intelligence technologies to traditional methods.

Ushizima develops image recognition algorithms to diagnose COVID-19

Daniela Ushizima develops image recognition algorithms to diagnose COVID-19
Source: BERKELEY LAB COMPUTING SCIENCES
June 1, 2020

Dani Ushizima explores algorithms and a data analysis pipeline to help accurately distinguish COVID-19 abnormalities in CT scans and chest X-rays.

Read Article

UCSF and AWS Collaboration

UCSF & AWS Collaboration
Source: Bakar Institute
May 12, 2020

Facilitated by BCHSI, AWS connected with the laboratory of Charles Chiu to enable two COVID-19 projects.

Read Article

Ushizima, Daniela

April 16, 2020 By Karen

Daniela Ushizima, PhD

Algorithms for Multimodal and N-Dimensional Imaging Experiments

Dr. Ushizima research focuses on computer vision algorithms for monitoring diseases progression while exploring information from multiple imaging techniques. Together with Grinberg’s lab, developed quantitative histological analysis of whole human brains using multiple instruments.

UC Health Data Initiative Launches Daily Updates on COVID-19 Tests

Source: University of California
April 6, 2020

UC Health will distribute daily updates about SARS-CoV-2 testing volume, the # of positive tests & age distribution of confirmed cases gathered from its 5 medical centers.

Read Article

Bakar Institute Develops COVID-19 County Tracker App

COVID-19 County Tracker
Source: Bakar Institute
APRIL 3, 2020

Butte lab developed a COVID-19 County Tracker app to track cases nationwide. It features plots of total cases by states and county, with interactive exploration.

See Details

Acid Reflux Drug Is a Surprising Candidate to Curb Preterm Birth

Acid Reflux Drug Is a Surprising Candidate to Curb Preterm Birth
Source: UCSF
February 13, 2020

Marina Sirota uses a computational study to identify a dozen of other drugs to reduce inflammation.

Read Article

Jiang, Fei

January 14, 2020 By Karen

Fei Jiang, PhD, MS

High quality statistical and computational publications focusing on addressing practical problems in the medical domain

Dr. Jiang’s research interest lies in machine learning methods, high dimensional models, functional data analysis and their applications in analyzing neurological, image, genetics data, and in designing adaptive randomization clinical trials. Her efforts yield high quality statistical and computational publications, which focus on addressing practical problems in the medical domain.

Scheffler, Aaron

January 14, 2020 By Karen

Aaron Scheffler, PhD, MS

Analysis of complex datasets to better understand biological systems and inform meaningful clinical decisions

Dr. Scheffler develops statistical methods for high-dimensional signals produced by his collaborators in neurology and orthopedics. The proper interrogation of this data will lead to improved health outcomes at both the patient and population level.

Abbasi-Asl, Reza

January 14, 2020 By Karen

Reza Abbasi-Asl, PhD

Interpretable machine learning to understand brain functions and related disorders

The Abbasi Lab aims to understand functions of the brain and related disorders by leveraging principles in machine learning and statistics. The lab studies large-scale single-cell level neurophysiological datasets as well as medical images and structured and unstructured healthcare data.

BCHSI Faculty Named on Forbes’ 30 under 30

Forbes' 30 Under 30
Source: UCSF
DECEMBER 10, 2019

Vijay Ramani has been named to Forbes magazine’s annual 30 Under 30 list of rising stars in healthcare.

Read Article

Unprecedented Partnership to Advance Data in Biomedicine

Baranzani and Israni lead the NSF Award
Source: UCSF Precision Medicine
November 7, 2019

Sergio Baranzini and Sharat Israni will lead the NSF award & collaborate with Google, Lawrence Livermore Library, and Institute Systems for Biology.

Read Article

Data Science Health Innovation Fellows announced

Data Science Health Innovation Fellows
Source: Bakar Institute
November 4, 2019

BCHSI and BIDS welcome the 2019 Data Science Health Innovation Fellows.

See Details

Julia Adler-Milstein Elected to the National Academy of Medicine for 2019

Julia Adler-Milstein Elected to the National Academy of Medicine for 2019
Source: UCSF
October 21, 2019

Four UCSF faculty members are among the 100 new members elected to the National Academy of Medicine this year, including BCHSI affiliate faculty Julia Adler-Milstein.

Read Article

Lyles, Courtney

October 18, 2019 By Karen

Courtney Lyles, PhD

Reinforcement Learning Algorithm for Motivating Physical Activity among Patients with Diabetes and Depression

We are developing & testing smartphone apps that use reinforcement learning models to personalize text-messages to encourage physical activity. The apps are designed for English & Spanish speaking individuals diagnosed with depression and diabetes, being treated at the ZSFGH.

Rankin, Kate

October 18, 2019 By Karen

Kate Rankin, PhD

Building Strategic Clinical Informatics Tools to Bridge Precision Medicine Research and Patient Care

Dr. Rankin investigates the underpinnings of human socioemotional behavior in aging and neurodegenerative disease with quantitative brain imaging, and develops tools for harmonizing cross-disciplinary data and analytic processes to facilitate scientific collaboration and clinical care.

Phillips, Kathryn

October 18, 2019 By Karen

Kathryn Phillips, PhD

Examining Health Services and Health Economics, focusing on new technologies to improve healthcare

Dr. Phillips focuses on the value of new technologies and how to effectively and efficiently implement them into health care. Her core specialty is precision medicine. Her work spans multiple disciplines, including basic, clinical & social sciences

Glymour, Maria

October 18, 2019 By Karen

Maria Glymour, ScD, MS

Causal Inference, Artificial Intelligence and Health Research

Dr. Glymour is exploring approaches of causal inference methods for research on health inequalities, stroke, and Alzheimer’s disease and how Artificial Intelligence can accelerate health research.

Murray, Sara

October 18, 2019 By Karen

Sara Murray, MD

Using EHR data for quality and value improvements

Dr. Murray is leading the Advanced Analytics & Innovation team, she is involved in large analytic projects using EHR data to inform quality and value improvement efforts at the medical center. She is interested in predictive analytics and has done research in EHR phenotyping.

Sanders, Stephan

October 18, 2019 By Karen

Stephan Sanders, PhD

Using genomics and bioinformatics to understand the etiology of developmental disorders

Sanders Lab aims to identify the etiology of developmental disorders through the discovery of genetic risk factors. They aim to continue progress, leverage findings to build a complete understanding of ASD, & extend this approach to other human disorders, including congenital malformations.

Hong, Julian

October 17, 2019 By Karen

Julian Hong, MD, MS

Developing and implementing computational tools in oncology to improve patient care

Dr. Hong’s research program focuses on combining clinical domain knowledge with data science to generate insights from real world data, develop actionable computational tools, and evaluate the benefit of these advances in personalized cancer care.

Li, Jingjing

October 17, 2019 By Karen

Jingjing Li, PhD

From Big Data to Big Mind: Building Data-Driven Frameworks to Solve Complex Diseases

The main theme of our research is large-scale analysis of disease genomes by integrating multi-omics data, evolutionary insights, electronic health records, as well as digitized clinical traits from imaging and wearable sensor readouts. The ultimate goal is to build data-driven frameworks to detect diseases before symptoms emerge and to achieve precision health management.

Brain Maps Allow Individualized Predictions of FTD Progression

Brain Maps Allow Individualized Predictions of FTD Progression
Source: UCSF
October 14, 2019

Seeley and colleagues used maps of brain connections to predict how brain atrophy would spread in individual patients with frontotemporal dementia.

Read Article

UCSF Launches Artificial Intelligence Center to Advance Medical Imaging

UCSF Launches Artificial Intelligence Center to Advance Medical Imaging
Source: UCSF
October 11, 2019

Majumdar will run the Center for Intelligent Imaging’s operations to accelerate the application of artificial intelligence (AI) technology to radiology.

Read Article

FDA approves Artificial Intelligence Algorithm That Reads Chest X-Rays

FDA approves Artificial Intelligence Algorithm That Reads Chest X-Rays
Source: UCSF
September 12, 2019

Callcut led the product development of the new AI screening tool, known as Critical Care Suite, which is being licensed by UCSF Innovation Venture to GE Healthcare.

Read Article

Genetic Test Found a Life-Saving Therapy for an Infant’s Rare Cancer

Genetic Test Found a Life-Saving Therapy for an Infant's Rare Cancer
Source: UCSF
September 11, 2019

Alejandro Sweet-Cordero, explains how the UCSF500 test can identify inherited predispositions to cancer and help patients design prevention and surveillance strategies.

Read Article

Mobile Devices and Health

Mobile Devices and Health
Source: New England Journal of Medicine
September 5, 2019

UCSF, Cornell Tech, Sage Bionetworks, Open mHealth and The Commons Project are collaborating to integrate EHR data to Android smartphones.

Read Article

Alzheimer’s Disease Destroys Neurons that Keep Us Awake

Alzheimer’s Disease Destroys Neurons that Keep Us Awake
Source: UCSF
August 12, 2019

Study suggests tau tangles, not amyloid plaques, drive daytime napping that precedes dementia.

Read Article

AI For All — Data-Driven Summer Program Energizes a New Generation

AI For All — Data-Driven Summer Program Energizes a New Generation
Source: UCSF Precision Medicine
August 14, 2019

BCHSI faculty Marina Sirota led the first cohort of the AI4All program, focused on promoting greater diversity and inclusion in the field of AI in biomedicine.

Read Article

Tison, Geoff

August 7, 2019 By Karen

Geoff Tison, MD, MPH

Applying machine learning and deep-learning techniques to large-scale electronic health data

Dr. Tison applies machine learning and deep-learning techniques to large-scale electronic health data from heterogeneous sources in order to achieve the goal of personalized cardiovascular prognosis and disease prevention.

Rosner, Benjamin

August 5, 2019 By Karen

Benjamin Rosner, MD, PhD

Understand use of CLIIR to improve quality and value of healthcare

Audit-log data captures moment to moment clinical care processes within EHR. It makes these labor-intensive approaches obsolete, providing more comprehensive data faster with more accuracy. Taking this audit-log data and combining it with clinical data enables us to research the impact of provider workflows, behaviors and interactions with the EHR on patient outcomes.

University of California announces data science collaboration with Janssen

UC & Janssen Collaboration
Source: University of California
June 28, 2019

New fellowship program from UCSF’s BCHSI, UC Berkeley’s BIDS, and Janssen Research & Development to recruit data scientists for innovative, high-impact, data-driven healthcare research

Read Article

Ramani, Vijay

June 27, 2019 By Karen

Vijay Ramani, PhD

Novel molecular technologies to study gene regulation

Ramani Lab invents molecular tools to study biology, e.g. devising ways to molecularly tag nucleic acids and proteins with unique genomic or proteomic identifiers, then using these to quantify biological phenomena at the level of single cells and single molecules, using high-throughput sequencing and cutting-edge mass spectrometric techniques.

Huang, Franklin

June 24, 2019 By Karen

Franklin Huang, MD, PhD

Understanding how to use digital tools to improve quality and value of healthcare

Dr. Huang studies biological processes relating to cancer disparities with a focus in prostate cancer. His lab uses cancer genomics including single-cell approaches to understand mechanisms that drive lethal, aggressive disease. A major focus is to identify and uncover roles for cancer genes and identify new cancer vulnerabilities.

Whooley, Mary

June 24, 2019 By Karen

Mary Whooley, MD

Learning Health Systems & Cardiovascular Outcomes Research

Dr. Whooley’s work focuses on applying the methods of health services research (including data science, implementation science, and program evaluation) to accelerate the adoption of evidence-based practices within the context of a national learning healthcare system. One of her specific interest areas is in the domain of cardiovascular health outcomes.

Larson, Peder

June 24, 2019 By Karen

Peder Larson, PhD

Developing new MRI scanning and reconstruction technology for improved clinical outcomes

Dr. Larson’s research program focuses on developments aimed at several applications: Metabolic imaging methods using hyperpolarized carbon-13 MRI; Semi-solid tissue MRI, for imaging of tendons, cortical bone, myelin, and lung tissue; and PET/MRI systems that combine the exceptional soft-tissue contrast of MRI with the functional contrast of PET.

Pirrachio, Romain

June 24, 2019 By Karen

Romain Pirrachio, MD, PhD

Applied biostatistical research, machine Learning and predictive analytics in critical care

Dr. Pirracchio focuses on three clinical research areas including evaluation and optimization of daily cares in the intensive care unit. He is also broadly interested in problems of causal inference and prediction, particularly developing novel methodologies for addressing scientific questions using complex observational data subject to sampling biases.

New Collaboration To Advance Patient Safety In The Digital Era

New Collaboration To Advance Patient Safety In The Digital Era
Source: CISION PR Newswire
May 7, 2019

Julia Adler-Milstein will lead the new partnership between UCSF and The Doctor’s Company to make substantive advances in patient safety and digital health.

Read Article

Seo, Youngho

November 9, 2018 By Karen

Youngho Seo, PhD

Using quantitative SPECT/CT, PET/CT, and PET/MR molecular imaging tools for a broad range of research areas

Dr. Seo applies his expertise in radionuclide and x-ray imaging physics and instrumentation to develop quantitative imaging techniques for everything from small animal research to analysis of clinical research data.

Pedoia, Valentina

November 9, 2018 By Karen

Valentina Pedoia, PhD

Using machine learning to extract features from MRI to study degenerative joint disease

Dr. Pedoia develops analytics to model the complex interactions between morphological, biochemical and biomechanical aspects of the knee joint as a whole; deep learning convolutional neural network for musculoskeletal tissue segmentation and for the extraction of silent features from quantitative relaxation maps for a comprehensive study of the biochemical articular cartilage composition; with ultimate goal of developing a completely data-driven model that is able to extract imaging features and use them to identify risk factors and predict outcomes for Osteoarthritis.

Goldstein, Ted

November 9, 2018 By Karen

Ted Goldstien, PhD

Applying Bioinformatics to Precision Medicine

Dr. Goldstien uses the tools of big data, statistics and machine learning to answer questions related to Precision Medicine such as: How can we learn from the inventory of genomic test and knowledge in the EMR about patient outcomes and the data associated with individual patients to better direct their care? How can we better use repeatable animal models to translate knowledge to human patients? How can we integrate existing knowledge and high throughput data? Can we use genomic data to bring new therapies to bear?

Zaitlen, Noah

March 12, 2018 By Karen

Noah Zaitlen, PhD

Understanding genetic and environmental underpinnings of common disease

The Zaitlen lab develops statistical and computational tools to discover the genetic basis of complex phenotypes, with particular interest in human disease, variation in drug/treatment response, and disease outcomes. Current projects primarily focus on incorporating environmental context into medical genetics.

Van t’Veer, Laura

March 10, 2018 By Karen

Laura Van t’Veer, PhD

Characterizing biomolecular signatures for precision cancer treatments

Dr. van ‘t Veer’s research focuses on personalized medicine, to advance patient management based on knowledge of the genetic make-up of the tumor as well as the genetic make-up of the patient. This allows clinicians to optimally assign systemic therapy for those patients in need of such treatment, and to ensure the selection of the therapy that is most effective.

Hess, Christopher

March 10, 2018 By Karen

Christopher Hess, MD, PhD

Developing and translating biomedical imaging to diagnose and treat neurological disease

Dr. Hess’s research interests lie in the development and translational application of magnetic resonance imaging techniques for diagnosis and treatment monitoring in neurologic disease. His scientific background is in MRI acquisition, reconstruction and image analysis, focusing on diffusion and high-field MRI. His primary clinical interests are in neurovascular disease, dementia, brain development, and epilepsy.

Goodarzi, Hani

March 2, 2018 By Karen

Hani Goodarzi, PhD

Identification and characterization of key regulatory programs that underlie cancer progression

The Goodarzi laboratory employs a systems biological and multidisciplinary approach that integrates computational and experimental strategies to identify and characterize key regulatory programs that underlie cancer progression.

Arnaout, Rima

February 20, 2018 By Karen

Rima Arnaout, MD

Improving the resolution and accuracy of cardiovascular phenotypes to develop novel insights and therapies

Dr. Arnaout’s lab is currently developing computational methods to bring precision phenotyping to echocardiography, and also using the zebrafish animal model to study cardiovascular developmental gene function and to model human cardiovascular disease.

Raj, Ashish

February 20, 2018 By Karen

Ashish Raj, PhD

Mathematical modeling and data science in neurology and radiology

Ashish’s team develops novel image processing and analysis algorithms for MRI. His lab also works to model brain connectivity networks using graph theory, and investigates how these networks are disrupted with disease and trauma.

Baranzini, Sergio

February 20, 2018 By Karen

Sergio Baranzini, PhD

Genetics and molecular mechanisms underlying complex neurological disease

Dr Baranzini’s current research involves immunological studies using the EAE model, sequencing of whole genomes and transcriptomes from patients with multiple sclerosis and developing bioinformatics tools to integrate this information with that coming from other high throughput technologies. Dr Baranzini uses a combination of “wet lab” methods including DNA microarrays, proteomics, and laser capture microdissection, in combination with “dry lab” analytical approaches encompassing bioinformatics, complexity theory, and mathematical modeling.

Adler-Milstein, Julia

November 16, 2017 By Karen

Julia Adler-Milstein, PhD

Examining the use of IT in healthcare delivery

Dr. Adler-Milstein’s research assesses the progress of health IT adoption; the impact of such adoption on healthcare costs and quality; and the relationships between market, organizational, and team structure and health IT use. A core focus of her work is on health information exchange and interoperability.

Grinberg, Lea

July 14, 2017 By Karen

Lea Grinberg, MD, PhD

Computational approaches to imaging the human brain at the macro and micro level

The Grinberg Lab processes whole human brains for state-of-the-art quantitative histological analysis, digitize all of the results, and precisely registers to MRI. They are developing advanced tools for analysis of microscopic images that enable more comprehensive and higher-throughput studies of human brain tissue.

Brown, William

July 14, 2017 By Karen

William Brown, III, PhD, DrPH

Using informatics, mHealth, and New Media-based technologies to promote health among vulnerable populations and in underserved communities

Dr. Brown uses knowledge engineering, health informatics, comparative-effectiveness research, semantic harmonization, and integration of datasets (including EHR) to examine health disparities and develop patient-centered health information tools.

Sweet-Cordero, Alejandro

April 13, 2017 By Karen

Alejandro Sweet-Cordero, MD

Functional genomics to identify novel cancer therapeutics

The lab seeks to discover new therapeutic approaches to target the genetic mutations and altered signaling networks that are specific to cancer cells. Using functional genomics applied to mouse and human systems, we work to understand the transcriptional networks that regulate the outcome of specific oncogenic mutations and to understand how cancers become resistant to chemotherapy. This work relies heavily on computational genomic analysis, generating and using high-throughput datasets and next-generation sequencing for gene and network discovery. Our primary disease focus is lung cancer and pediatric sarcomas.

Kober, Kord

April 13, 2017 By Karen

Kord Kober, PhD

‘Omics data to understand mechanisms underlying common symptoms in chronic conditions

Dr. Kober uses ‘omics data (i.e., genotype and expression arrays, DNAseq — genome, exome, RNAseq, methylation arrays) to improve our understanding of the molecular mechanisms underlying common symptoms (e.g., fatigue, pain) or treatment failure experienced by patients with chronic medical conditions (e.g., cancer, HIV infection).

Tosun, Duygu

February 27, 2017 By Karen

Duygu Tosun, PhD

Developing algorithmic approaches for multi-modal data analysis

Dr. Tosun develops new algorithmic approaches for processing and analysis of multi-disciplinary/modal data including neuroimages, genetics, proteomics, as well as cognitive functioning measures in a unified framework. The primary aim is to identify multi-disciplinary/modality biomarkers for detecting the changes associated with disease specific neuropathology, improving understanding of pathophysiological progression and potentially providing a means of monitoring the efficacy and regional specificity of drug therapy for neurodegenerative diseases.

Majumdar, Sharmila

February 27, 2017 By Karen

Sharmila Majumdar, PhD

Developing image processing and analytics for musculoskeletal research

Dr. Majumdar’s research work on imaging, particularly magnetic resonance and micro computed tomography, and development of image processing and analysis tools, has been focused in the areas of osteoporosis, osteo-arthritis and lower back pain. Her research is diverse, ranging from technical development to clinical trials.

Nagarajan, Srikantan

January 12, 2017 By Karen

Srikantan Nagarajan, PhD

Brain imaging analysis and brain computer interfaces for diagnosis and assessment in various patient populations

Dr. Nagarajan has multiple research interests, including understanding human brain plasticity associated with learning and disease, and determining neural mechanisms of controlling speech. He focuses on the development and refinement of multimodal structural and functional brain imaging and brain computer interfaces, for diagnosis and assessment in various patient populations. His current translational research program includes conducting multimodal brain imaging studies in people with Autism, Dementia, Tinnitus, Brain Tumors, Epilepsy, Traumatic Brain Injury, Stroke and Voice Disorders.

Lupo, Janine

January 12, 2017 By Karen

Janine Lupo, PhD

Developing novel methods for MRI data collection and analysis in neurological research

Dr. Lupo is focused on developing novel methods for acquisition, reconstruction, post-processing, and quantitative analysis of magnetic resonance brain images. Using a combination of multiparametric structural, physiological, and metabolic MRI techniques, her goal is to quantitatively characterize heterogeneity within malignant brain tumors, monitor response to novel treatment regimens, and investigate the long-term effects of therapy on healthy brain tissue structure and cognitive function. Many of the methodologies we develop initially to evaluate patients with brain tumors are also being applied to other neurological diseases.

Xu, Duan

January 12, 2017 By Karen

Duan Xu, PhD

Developing new MRI techniques

Dr. Xu’s research focuses on investigating new MRI techniques with primary applications in pediatric neuroradiology. Another research focus is the development of new techniques on ultrahigh field MR scanners for small animal imaging, both in vivo and ex vivo. Techniques include high resolution MR anatomic, diffusion, and spectroscopy are being developed in collaboration with various colleagues in Neurodevelopment Biology, Neurology, Pediatrics, Neonatology, and Physiology.

Kalendarian, Elsbeth

January 12, 2017 By Karen

Elsbeth Kalendarian, DDS, MPH, PhD

Developing electronic dental health records for the information age

Elsbeth works on development and implementation of the Dental Diagnostic System (DDS) in EHR, and is providing leadership in the creation of international standards in dental health records.

Lazar, Ann

January 12, 2017 By Karen

Ann Lazar, MS, PhD

A Tailored Approach to Reducing Oral Health Disparities

Dr. Lazar is working to develop an analysis framework and software tools to help understand how patient characteristics interact with dental treatments in order to improve treatment decisions for individual patients and develop targeted treatments to reduce oral health disparities.

Blum, Michael

January 12, 2017 By Karen

Michael Blum, MD

Cardiology and Digital Health Technology

Dr. Blum is a cardiologist who specializes in the care of patients with congestive heart failure, valvular heart disease and preventative cardiology. He is dedicated to the early detection of heart disease and prevention through a heart-healthy lifestyle that includes diet, exercise and stress reduction. He has a special research interest in clinical decision support technology, social media and collaborative workspaces and their impact on the quality, effectiveness, and cost of care delivery.

ICHS & UCSF Library team up to sponsor Software Carpentry workshops

Source: ICHS
September 14, 2016

ICHS teamed up with the UCSF Library Data Science Initiative to offer a series of Software Carpentry workshops on campus.

Read Article

Gansky, Stuart

September 7, 2016 By Karen

Stuart Gansky, MS, DrPH

Oral health and health disparities

Dr. Gansky’s research concentrates on oral health, health disparities, applied statistical analyses and related method­ological issues. Balancing these components is essential to successful and practical population health research. Methodological examination helps ground health research and build convincing argu­ments, while collaborative health research generates opportunities for innovative statistical practice and provides challenges for developing ways to solve real world problems.

  • 1
  • 2
  • Next Page »

UCSF Mission Bay
490 Illinois St, Floor 2, Box 2933
San Francisco, CA 94143

CONTACT US

  • Twitter
  • YouTube

Copyright © 2022 ·The Regents of the University of California