Skip to Content

Rama Chellappa, PhD

Bloomberg Distinguished Professor
Rama Chellappa
Research Focus Area(s): Biomedical Data Science, Computational Medicine, Imaging and Medical Devices
Research Interests: Computer vision, pattern recognition, machine learning, artificial intelligence, signal and image processing
Publications: From Google Scholar
Clark 301
Research Interests

Research Interests

My research interests span computer vision, pattern recognition, machine learning and artificial intelligence. We integrate concepts from 3D geometry, illumination models, sensor physics, differential geometry, knowledge representation and reasoning methods, sparse and deep representations for addressing problems in these areas. In the area of computer vision, my group has worked on Markov random fields and extensions, recovering 3D structure from a single image, and from long sequences using discrete and continuous approaches, hyperspectral and radar image analysis. We are also interested in computer vision approaches to medicine. Specifically, we are interested in marker less motion capture methods and gait analysis with applications in diagnosing movement-related disorders. We have also developed registration methods that help electrophysiologists perform efficient ablation procedures. We are currently working on geolocation of images, media forensics and medical image reconstruction.

In the area of pattern recognition and machine learning, my group is working on many problems related to object/face/action detection and recognition from still images and videos. We use novel approaches based on shallow and deep representations to build robust end-to-end systems for face, expression, gesture, object and action detection and recognition. We are currently working on many current topics such as unsupervised domain adaptation, domain generalization, multi-task learning, learning from few samples, Generative Adversarial Networks (GANs) and defending attacks on machine learning algorithms and systems. We are also working on bias mitigation approaches for designing fair machine learning systems.

In the area of artificial intelligence, we have worked on topics such as knowledge representation, random forests, stochastic petri nets, non-monotonic reasoning and ontologies with potential applications in computer vision and medicine. We are currently working on the “deepfakes” problem and knowledge representation in deep learning networks.

Titles & Affiliations


  • PhD, Electrical Engineering, Purdue University, 1981
  • MSEE, Purdue University, 1978
  • Master of Engineering (Distinction), Electrical and Communication Engineering, Indian Institute of Science, 1977
  • Bachelor of Engineering (Honours), Electronics and Communication Engineering, University of Madras, 1975
Faculty News

Recent Highlights

  • December 8, 2020
    Rama Chellappa and Nitish Thakor, faculty in the Johns Hopkins Department of Biomedical Engineering, have been elected as fellows of the National Academy of Inventors.
  • July 13, 2020
    Bloomberg Distinguished Professor Rama Chellappa joined the Department of Biomedical Engineering with a joint appointment in the Department of Electrical and Computer Engineering in the spring of 2020. In this interview, he discusses his inspiration for pursuing a career in engineering, his research in computer vision and medical imaging, his goals for the future, and how he enjoys spending his time while outside the lab.

Read the Johns Hopkins University privacy statement here.