I am an Associate Professor in Residence in the Department of Radiological Sciences and part of the UCLA Medical Imaging Informatics Group. I am also a faculty affiliate of the Department of Bioengineering, the Jonsson Comprehensive Cancer Center, and the Institute of Quantitative and Computational Biosciences (QCB). I actively collaborate with faculty members in the Center for Domain Specific ComputingClinical & Translational Science Institute, and UCLA-PKU Joint Research Institute. I am the chair-elect of the AMIA Biomedical Imaging Informatics Working Group. In addition to being a core faculty member for the Medical Imaging Informatics training program, I lead a UC-HBCU Summer Pathways Grant and serve as a faculty mentor for the Cross-disciplinary Scholars in Science and Technology program.

Academic/Research Positions

  • Present2017

    Associate Professor

    UCLA, Department of Radiological Sciences

  • 20172010

    Assistant Professor

    UCLA, Department of Radiological Sciences

  • 20102009

    Assistant Researcher

    UCLA, Department of Radiological Sciences

  • 20092008

    Graduate Student Researcher

    UCLA, Medical Imaging Informatics Group, Biomedical Engineering IDP

  • Summer2006

    Research Intern

    Lister Hill National Center for Biomedical Communications, National Library of Medicine, National Institutes of Health

  • 20082004

    National Library of Medicine Predoctoral Fellow

    UCLA, Medical Imaging Informatics Group, Biomedical Engineering IDP

Education & Training

  • Ph.D. 2009

    Biomedical Engineering

    Medical Imaging Informatics track
    University of California, Los Angeles

  • B.S. 2004

    Biomedical Engineering

    Johns Hopkins University

Grants, Awards, and Milestones

  • June 2018
    Congratulations New PhD Graduates!
    Congratulations to my students who recently passed their PhD defenses!

    Edgar A Rios Piedra (with Alex Bui)

    Development of Segmentation Variability Maps to Improve Brain Tumor Quantitative Assessment Using Multimodal Magnetic Resonance Imaging

    Shiwen Shen (with Alex Bui)

    Characterizing Pulmonary Nodules using Machine and Deep Learning Methods to Improve Lung Cancer Diagnosis

    Nicholas Matiasz (with Alcino Silva)

    Planning Experiments with Causal Graphs

  • May 2018
    3rd Place Poster Award @ SIIM 2018

    We recently received an honorable mention award for our poster entitled “Improving the Robustness of Deep Learning Models: Application in Lung Nodule Detection” at the 2018 Society for Imaging Informatics in Medicine annual meeting in Washington D.C.

    Press release:

  • 2017-2021
    NSF Funds Project on Learning Optimal Diagnostic Pathways from Data

    The National Science Foundation recently awarded a 4-year, $1.3M grant to discover optimal sequences of diagnostic tests from electronic health record data. Read more about the project here and here.

  • April 2017
    Nick Matiasz's Talk on the Robot Scientist is a Finalist at the UCLA Grad Slam

    Congratulations to Nicholas Matiasz for making it into the finals at UCLA Grad Slam. See his 3-minute talk entitled “Building the Brain of a Robot Scientist” here.

  • Dec 2016
    Source Code: Automated Lung Segmentation Using Bidirectional Chain Codes
    My student Shiwen Shen has released the Matlab source code of the algorithm presented in “An automated lung segmentation approach using bidirectional chain codes to improve nodule detection accuracy“. You can find the code on his public GitHub repository.
  • Nov 2016
    Presentation: Imaging Informatics Year in Review 2016
    Charles Kahn (University of Pennsylvania) and I presented the 2016 “Imaging Informatics: Year in Review” at AMIA and RSNA. We have created a public resource with a listing and description of the papers summarized in this review. You can also view my presentation by clicking here.
  • Nov 2016
    AMIA Pre-Symposium on Quantitative Imaging and Imaging Informatics

    We had a wonderful crowd of AMIA attendees for the Biomedical Imaging Informatics Working Group sponsored pre-symposium entitled, “Quantitative Imaging and Imaging Informatics in the Era of Precision Medicine”, co-organized by Ashish Sharma (Emory) and me. Thank you Fred Prior (University of Arkansas for Medical Sciences), Lee Cooper (Emory), and Jayashree Kalpathy-Cramer (Harvard/MGH) for providing the keynotes. The program can be found here. 

  • Nov 2016
    Book Chapter: Medical Imaging Informatics for Precision Medicine
    Ricky Taira, Suzie-El Saden, and I published a chapter entitled “Medical Imaging Informatics” in the book “Translational Biomedical Informatics“, published by Springer Singapore. In this chapter, you will find our vision for the role of imaging informatics in advancing our understanding of disease biology and improving how radiology is practiced. You can read the chapter on SpringerLink.
  • Sept 2016
    Early Lung Cancer Detection in the Setting of Indeterminate Pulmonary Nodules
    I am an investigator on a pair of newly awarded research grants from the National Institutes of Health related to early detection of lung cancer and the classification of indeterminate pulmonary nodules as benign or malignant. Both awards are a collaboration between Boston University and UCLA.
  • July 2016
    Prediction of Idiopathic Pulmonary Fibrosis using Clinical & Imaging Data in the Elderly
    I am an investigator on a team (PI, Grace Kim) funded by a research award from Genentech Inc to build a multivariate Cox regression model of IPF to predict disease course, stratifying by age group and incorporating quantitative imaging features extracted from chest computed tomography images.
  • Jun 2016
    Congratulations New MSc/PhD Graduates!
    Congratulations to my students who recently passed their PhD defenses!

    Kyle Singleton, PhD (now a Research Associate, Mayo Clinic, AZ)
    Investigating Predictive Disease Model Transportability through Cohort Simulation and Causal Analysis

    Juan “Anna” Wu, PhD
    A Methodology to Apply Evidence from Scientific Literature to Guide Individually-tailored Evidence-based Medicine

    And PhD/MSc students for whom I served on their committees.

    Yong Bai, PhD — w/Xiao Hu (now a Postdoctoral Fellow, University of California, San Francisco)
    SuperAlarm: System and Methods to Predict In-Hospital Patient Deterioration and Alleviate Alarm Fatigue

    Jinsung Yoon, MS — w/Mihaela van der Schaar (now a PhD student at UCLA)
    Discovery and Clinical Decision Support for Personalized Healthcare

  • Nov 2015
    Nova Smedley's Poster Nominated for Award
    My student Nova Smedley’s poster entitled “A platform for generating and validating breast risk models from clinical data: Towards patient-centered risk stratified screening” was nominated for a Distinguished Poster Award at AMIA.
  • Aug 2015
    Building Research Maps for Catalyzing Translational Medicine
    Role: Principal Invesigator

    Summary: The objective of this proposal is to create an open-source software application called ClinResearchMaps that facilitates clinical translational research by systematically and collaboratively capturing results of experimental studies reported in biomedical literature in a sharable, machine-readable way. We will build upon the concept of research maps, a graph-based representation where nodes represent biomedical entities and edges represent causal assertions, to formalize causal relations based on a taxonomy of clinical experiments and rules for integrating evidence from multiple studies.

  • Jun 2015
    UCLA Research in Informatics Summer Experience
    Role: Principal Investigator

    Summary: The Research in Informatics Summer Experience (RISE) is an internship program that engages undergraduate students from minority or underprivileged backgrounds to pursue advanced degrees in engineering and the health sciences. This grant fosters collaborations between UCLA and Florida A&M University, a Historically Black Colleges and Universities (HBCU)-designated campus, and funds the participation of three undergraduate students to participate in a summer internship program with the Medical Imaging Informatics group.

  • Jan 2015
    Chair, AMIA Biomedical Imaging Informatics Working Group
  • Nov 2014
    Kyle Singleton Nominated for Student Paper Award
    My student Kyle Singleton’s paper entitled “Motivating the additional use of external validity: Examining transportability in a model of glioblastoma multiforme” was nominated as a Student Paper Award finalist and also received 1st place in the AMIA Knowledge Discovery and Data Mining (KDDM) Working Group student paper competition. Congrats!
  • Oct 2014
    Population-Based Patient-Centered Risk Stratified Breast and Lung Cancer Screening
    Role: Co-investigator

    Summary: Cancer screening is a large population based intervention that costs billions of dollars and is often the center of great debate. Despite the enormous resources invested, better targeting is needed to drive down incidence and mortality of cancer as well as decrease the unintended consequences of cancer screening, over-diagnosis and overtreatment. The objective of this Impact Award is to pilot a novel multi- and inter-disciplinary approach towards risk-stratified screening that incorporates scientific evidence and novel imaging and genomic biomarkers to determine an individualized screening regimen for patients. The driving hypothesis is that tailoring cancer screening will substantially reduce cost, the rate of benign biopsies, and overtreatment.

    Collaborators: Arash Naeim, MD PhD

    Funding: Jonsson Comprehensive Cancer Center

  • 2013-2014
    Utilization and Value of Imaging in the Elderly Population
    Role: Principal Investigator

    Summary: The successful completion of this study will result in several key contributions: 1) a longitudinal research database of approximately 66,000 elderly patients imaged at UCLA from 2007-2012 that may be used for secondary analyses; 2) a methodology for analyzing observational clinical data to characterize trends in imaging utilization that can be generalized to other institutions; and 3) findings that elucidate the utilization of imaging in an elderly population for different diseases and provide the basis for defining the appropriate use of imaging.

    Funding: American College of Radiology

  • 2012-2017
    A Predictive Prognostic Model for Glioblastoma Multiforme
    Role: Co-Investigator

    Summary: Each year, almost half of all diagnosed primary brain tumors in the United States are Grade IV glioblastoma multiforme (GBM). While recent discoveries have elucidated the cancer pathways involved in the cancer’s etiology, no specific prognostic model has arisen (nor sufficiently validated) to provide widespread usability and individually tailored predictions about a patient’s prognosis. The objective of this project is to develop a Bayesian belief network for predicting outcomes for GBM patients.

    Funding: NIH/NCI R01 CA1575533

  • 2011-2012
    Data Exchange Platform for Structuring and Sharing Clinical Data
    Role: Principal Investigator

    Summary: Enabling the secondary use of clinical data provides opportunities to derive new knowledge about complex diseases and improving public health surveillance and education directly from data that are routinely generated in clinical practice. This effort created a data exchange platform for searching radiological text and imaging exam information for research.

    Funding: UCLA Institute of Digital Research and Education (IDRE)