World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
5373
World Ranking
9872
National Ranking
104

Overview

Balaraman Ravindran is affiliated with the Indian Institute of Technology Madras in India. Their research work is primarily situated within the field of Computer Science, with a substantial focus on several subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Management Science and Operations Research, and Electrical and Electronic Engineering.

The scientist has contributed notably to a variety of topics encompassing advanced and specialized areas such as:

  • Reinforcement Learning in Robotics
  • Advanced Graph Neural Networks
  • Complex Network Analysis Techniques
  • Bioinformatics and Genomic Networks
  • Machine Learning and Data Classification
  • Advanced Bandit Algorithms Research
  • Adversarial Robustness in Machine Learning

Their publication record includes papers in multiple venues, reflecting diverse research interests. Frequent publication venues include:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Frontiers in Artificial Intelligence
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • ACM Computing Surveys

Recent research contributions consist of:

  • A Survey of Adversarial Defenses and Robustness in NLP (2023, ACM Computing Surveys)
  • Hypergraph clustering by iteratively reweighted modularity maximization (2020, Applied Network Science)
  • Understanding Convolutions on Graphs (2021, Distill)
  • Scalable multi-product inventory control with lead time constraints using reinforcement learning (2021, Neural Computing and Applications)
  • EMPIR: Ensembles of Mixed Precision Deep Networks for Increased Robustness against Adversarial Attacks (2020, arXiv (Cornell University))

Balaraman Ravindran has worked with several frequent co-authors, including:

  • Srinivasan Parthasarathy
  • Sriraam Natarajan
  • Karthik Raman
  • Gokul Krishnan
  • Milind Tambe

Best Publications

  • An Autoencoder Approach to Learning Bilingual Word Representations

    Sarath Chandar A P;Stanislas Lauly;Hugo Larochelle;Mitesh Khapra

  • EPOpt: Learning Robust Neural Network Policies Using Model Ensembles

    Aravind Rajeswaran;Sarvjeet Ghotra;Balaraman Ravindran;Sergey Levine

  • Efficient computation of the shapley value for game-theoretic network centrality

    Tomasz P. Michalak;Karthik V. Aadithya;Piotr L. Szczepanski;Balaraman Ravindran

  • Latent dirichlet allocation based multi-document summarization

    Rachit Arora;Balaraman Ravindran

  • Diversity driven Attention Model for Query-based Abstractive Summarization

    Preksha Nema;Mitesh M. Khapra;Anirban Laha;Balaraman Ravindran

  • Correlational neural networks

    Sarath Chandar;Mitesh M. Khapra;Hugo Larochelle;Balaraman Ravindran

  • Accurate mobile robot localization in indoor environments using bluetooth

    Aswin N Raghavan;Harini Ananthapadmanaban;Manimaran S Sivamurugan;Balaraman Ravindran

  • Improving legal information retrieval using an ontological framework

    M. Saravanan;B. Ravindran;S. Raman

  • Model Minimization in Hierarchical Reinforcement Learning

    Balaraman Ravindran;Andrew G. Barto

  • SMDP homomorphisms: an algebraic approach to abstraction in semi-Markov decision processes

    Balaraman Ravindran;Andrew G. Barto

  • An algebraic approach to abstraction in reinforcement learning

    Balaraman Ravindran;Andrew G. Barto

  • Adaptive network intrusion detection system using a hybrid approach

    R Rangadurai Karthick;Vipul P. Hattiwale;Balaraman Ravindran

  • A tutorial survey of reinforcement learning

    S Sathiya Keerthi;B Ravindran

  • Overtaking Maneuvers in Simulated Highway Driving using Deep Reinforcement Learning

    Meha Kaushik;Vignesh Prasad;K Madhava Krishna;Balaraman Ravindran

  • COMMIT: A Scalable Approach to Mining Communication Motifs from Dynamic Networks

    Saket Gurukar;Sayan Ranu;Balaraman Ravindran

  • Latent Dirichlet Allocation and Singular Value Decomposition Based Multi-document Summarization

    R. Arora;B. Ravindran

  • Efficient computation of the shapley value for centrality in networks

    Karthik V. Aadithya;Balaraman Ravindran;Tomasz P. Michalak;Nicholas R. Jennings

  • Hierarchical activity recognition for dementia care using Markov Logic Network

    K. S. Gayathri;Susan Elias;Balaraman Ravindran

  • Towards Transparent and Explainable Attention Models

    Akash Kumar Mohankumar;Preksha Nema;Sharan Narasimhan;Mitesh M. Khapra

  • Recovering from Random Pruning: On the Plasticity of Deep Convolutional Neural Networks

    Deepak Mittal;Shweta Bhardwaj;Mitesh M. Khapra;Balaraman Ravindran

  • Symmetries and Model Minimization in Markov Decision Processes

    B. Ravindran;A. G. Barto

Frequent Co-Authors

Milind Tambe
Milind Tambe Harvard University
Ahmed A. Moustafa
Ahmed A. Moustafa Bond University
Srinivasan Parthasarathy
Srinivasan Parthasarathy The Ohio State University
Anand Raghunathan
Anand Raghunathan Purdue University West Lafayette
Andrew G. Barto
Andrew G. Barto University of Massachusetts Amherst
Nicholas R. Jennings
Nicholas R. Jennings Loughborough University
Hugo Larochelle
Hugo Larochelle Google (United States)
Jeffrey Xu Yu
Jeffrey Xu Yu Chinese University of Hong Kong
Anupam Joshi
Anupam Joshi University of Maryland, Baltimore County
Sven Bergmann
Sven Bergmann Swiss Institute of Bioinformatics

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

If you're interested in studying Computer Science in the USA, there are several related fields you can explore online. Programs in mechanical engineering, data science, physics, and electrical engineering are becoming increasingly accessible through distance learning.

Affordability is a major concern for many students. If you are cost-conscious, learning about the cheapest online mechanical engineering degree options can help you plan financially. Similarly, many wonder: can you get a physics degree online? The answer is yes—many institutions now offer flexible online physics programs.

For those leaning toward tech and analytics, check out the cheapest data science masters in usa to compare tuition and program features. Electrical engineering is another popular pathway that is available online, but tuition varies by school. Learn more about electrical engineering online tuition costs before applying.

Exploring these affordable online degrees can broaden your career possibilities and help you find the right fit for your goals and budget.

Best Scientists Citing Balaraman Ravindran

Trending Scientists