Ngan Le

Principal Investigator

Personal Website
https://www.nganle.net/
Google Scholar
Ngan Le

Overview

Dr. Le is the director of the Artificial Intelligence and Computer Vision Lab and an Assistant Professor in the Department of Computer Science & Computer Engineering at the University of Arkansas. She was a research associate in the Department of Electrical and Computer Engineering (ECE) at Carnegie Mellon University (CMU) in 2018-2019. She received a Ph.D degree in ECE at CMU in 2018, ECE Master degree at CMU in 2015, CS Master Degree at the University of Science, Vietnam in 2009 and CS Bachelor degree at the University of Science, Vietnam in 2005.   Her current research interests focus on Image Understanding, Video Understanding, Computer Vision, Robotics, Artificial Intelligence (Machine Learning, Deep Learning, Reinforcement Learning), Biomedical Imaging, SingleCell-RNA.   Dr. Le is currently an Associate Editor of Elsevier Machine Learning with Applications, a Guest Editor of Scene Understanding in Autonomous (Frontier, a Guest Editor of Artificial intelligence in Biomedicine and Healthcare (MDPI), and a Program Chair of Asilomar 2022. 

She co-organized the Deep Reinforcement Learning Tutorial for Medical Imaging at MICCAI 2018, Medical Image Learning with Less Labels and Imperfect Data workshop at MICCAI 2019, 2020, 2021, Visual Detection, Recognition and Prediction at Altitude and Range at ICCV 2022. Dr. Le is instructor lead of the Google Machine Learning Bootcamp 2021.

Her publications appear in the top-tier conferences including CVPR, MICCAI, ICCV, SPIE, IJCV, ICIP etc, and premier journals including IJCV, JESA, TIP, PR, JDSP, TIFS, etc. She has co-authored 75+ journals, conference papers, and book chapters, 9+ patents and inventions. She has served as a reviewer for 10+ top-tier conferences and journals, including TPAMI, AAAI, CVPR, NIPS, ICCV, ECCV, MICCAI, TIP, PR, TAI, IVC, etc

Education

  • PhD, Electrical and Computer Engineering, Carnegie Mellon University (2018)
  • MS, Electrical and Computer Engineering, Carnegie Mellon University (2015)
  • MS, Computer Science, University of Science (2009)
  • BS, Computer Science, University of Science (2005)

Publications

Please refer to the google scholar page for the up to date publication list.

Patents

  • Ngan T.H. Le, Michael Kidd, “Chicken Processing Plant With Automated Computer Vision”, P2757US00, UADA 2021-020 (UAF 2021-032)
  • Ngan T.H. Le, Michael Kidd, “Artificial Intelligence And Vision-Based Broiler Body Weight Measurement System And Process”, P2736US00, UADA 2021-009 (UAF 2021-017)
  • Ngan T.H. Le, Marios Savvides, ”Simultaneously Detecting and Classifying Abnormal Pap on the Cervix”, CMU Invention Disclosure - under review
  • Ngan T.H Le, Marios Savvides, ”Reformulating Level Sets as Deep Recurrent Neural Network Approach to Semantic Segmentation”, CMU Invention Disclosure No. 2018-01
  • Ngan T.H. Le, Marios Savvides, Boyiadzis Michael, Contis Lydia, Methods and Systems for Disease Classification, This application claims the benefit under 35 U.S.C.119 of U.S.Provisional Application Serial No. 61/967,316, filed on March 17, 2014, which is incorporated by reference herein in its entirety.
  • Ngan T.H. Le, K. Luu and M. Savvides, ”SparCLeS: Dynamic L1 sparse Classifiers with Level Sets for Robust Beard/Moustache Detection and Segmentation”, 2013 Grands: DAAD19- 02-1-0389 and W911NF-09-1-027 from the Army Research Office and by cooperative agreement W911NF-10-2-0028 from the Army Research Laboratory
  • K. Luu, S. Venugopalan, Ngan T.H. Le and M. Savvides,” Sparse Class Dependent Feature Analysis”, 2012
  • Ngan T.H. Le, Utsav Prabhu, Marios Savvides, ”Automatic Eyebrow Detection, Segmenta- tion, and Matching System - EDMS”, 2013 Grands: DAAD19-02-1-0389 and W911NF-09-1-027 from the Army Research Office and by cooperative agreement W911NF-10-2-0028 from the Army Research Laboratory
  • Ngan T.H. Le, M. Savvides, ”Facial Aging and Asymmetry Decomposition Based Approaches to Identification of Twins”, 2013Grands: DAAD19-02-1-0389 and W911NF-09-1-027 from the Army Research Office and by cooperative agreement W911NF-10-2-0028 from the Army Research Laboratory

Scholarships and Awards

  • NIH Travel Award, MICCAI 2018 conference in Spain, Sep. 2018
  • PhD Scholarship in Carnegie Mellon University, U.S., from Sep. 2011 - 2018
  • PhD Scholarship in Concordia University, Canada in 4 years from May 2010
  • Scholarship of Vietnamese Government for Graduated Students, 2008-2010 .
  • Best paper award, International Symposium on Electronic Commerce and Security, China, 2008.
  • Second Prize of Vietnamese Talents Competition of Dantri Newspaper, 2007.
  • First Prize of Light the Hope of Vietnamese Government for helping disable people 2007. First Prize of Nationwide Student’s Research Competition 2005.
  • First Prize of VIFOTEC (Vietnam Fund for Supporting Technology) 2005.
  • Scholarship of Tuong Minh Company, 2004.

Work Experience

Jul.2018 - Aug.2019: Work with Cylab Biometrics Center, Carnegie Mellon University as Research Associate on projects of Detecting and Classifying Abnormal Pap on the Cervix

Sep.2011 - May.2018: Work on machine learning for computer vision projects, particularly face recognition, hand on wheel recognition, grammar-aware based parsing (facial decomposition, driver parsing).

Sep.2013 - Sep.2015: CMU Driver Behavioral Situational Awareness System (DB-SAW), sponsored by Federal Highway Administration, U.S. Department of Transportation, Exploratory Advanced Research Program.

Feb.2013 - Feb.2015: Enhanced Level II Detail Facial Soft Biometrics for an Automatic Forensic- style approach to Facial Matching/Sorting, sponsored by Army Research Lab, $720,000.

Oct.2011 - Oct.2013: Soft Biometric Indexing with Matcher Fusion for Robust Identification, spon- sored by Army Research Lab, $695,000.

May.2010 - Sep.2011: Work with IMDS Company in Document Analysis project.

Aug.2009 - May.2010: Being IT executive of PMDC Corp. and have been working on E-Government project (sponsor: the World Bank) and MIS project (sponsor: UNDP).

Jan.2009 - May.2010: Being as a Lecturer in Department of Computer Sciences, Faculty of Information Technology, University of Sciences, 227 Nguyen Van Cu St., Dist. 5, HCM City, Vietnam.

Aug.2008 - Jan.2009: Being as a Teaching Assistant in Computer Sciences Department, DaYeh University, Dacun, Chunghua, Taiwan.

Jan.2008 - Jan.2009: Being as a Researcher MSN Lab, Feng Chia Unversity, Taichung, Taiwan.

Aug.2005 - Jan.2008: Teaching Assistant in Faculty of Information Technology, University of Sciences – 227 Nguyen Van Cu St., Dist. 5, HCM City, Vietnam.

Teaching

Invited Talk

  • Deep Reinforcement Learning in Medical Imaging, MICCAI 2018, , Granada, Spain, Sep. 2018

Seminars

  • University of Arkansas, Deep Learning - based Semantic Segmentation, Oct. 2018
  • University of Arkansas, Deep Learning in Medical Imaging, Oct. 2018
  • University of Arkansas, Fundamentals of Deep Learning, Sep. 2018
  • University of MSU, Reformulating LevelSet in Deep Learning Framework, (Planning)

Guest Lecturer

  • CSCE4013 at Department of CSCE, in University of Arkansas Review of Deep Learning
  • CSCE5683 Department of CSCE, in University of Arkansas
    • Image Segmentation - part 1(Thresholding, Region-based methods)
    • Image Segmentation - part 2 (Clustering, Graph-based methods)
    • Image Segmentation - part 3 (Level Sets, Machine Learning-based)

Teaching Assistant

  • 18551 - Digital Communication and Signal Processing Systems Design, Carnegie Mellon University
  • 18792 - Pattern Recognition Theory, Carnegie Mellon University
  • Computer Graphics, University of Science, Vietnam
  • Data Structures and Algorithms, University of Science, Vietnam
  • Artificial Intelligence, University of Science, Vietnam
  • Digital Image Processing, University of Science, Vietnam

Lecturer

  • Data Hiding and Secret Sharing, University of Science, Vietnam

Academic Services

Conference Reviewer

  • Conference on Computer Vision and Pattern Recognition(CVPR)
  • Conference on Neural Information Processing Systems, NIPS
  • Medical Image Computing and Computer Assisted Intervention Society (MICCAI)
  • International Conference on Document Analysis and Recognition (ICDAR)

Journal Reviewer

  • Transactions on Signal Processing.
  • Transactions on Image Processing.
  • Pattern Recognition Letters.
  • Pattern Recognition.
  • Journal of Digital Signal Processing.
  • Journal of Image and Vision Computing