Deepak Vijaykeerthy

Title

Research Engineer

Bio

My research interests are in Machine Learning, specifically Bayesian Learning, Probabilistic Modelling, and Optimization for Machine Learning. My focus at IBM Research has been on incorporating trust into the ML lifecycle. Recently, I have been working on building foundation models that can reason over tabular data.

Previously I was a Research Assistant in the Programming Languages and Tools Group at Microsoft Research, Bangalore, where I worked on probabilistic programming.

Publications

A Framework for Learning Ante-hoc Explainable Models via Concepts
- - Anirban Sarkar
  - Deepak Vijaykeerthy
  - et al.
- 2022
- CVPR 2022
Verifying individual fairness in machine learning models
- - Philips George John
  - Deepak Vijaykeerthy
  - et al.
- 2020
- UAI 2020
An ADMM based framework for AutoML pipeline configuration
- - Sijia Liu
  - Parikshit Ram
  - et al.
- 2020
- AAAI 2020
Hardening Deep Neural Networks via Adversarial Model Cascades
- - Deepak Vijaykeerthy
  - Anshuman Suri
  - et al.
- 2019
- IJCNN 2019

Visit Google Scholar

Patents

- 03 Mar 2025
- US
- 12242980
Machine Learning With Multiple Constraints
- 17 Feb 2025
- US
- 12229509
Contextual Impact Adjustment For Machine Learning Models
- 23 Sep 2024
- US
- 12099805
Generation Of Causal Explanations For Text Models
- 28 Aug 2023
- US
- 11741296
Automatically Modifying Responses From Generative Models Using Artificial Intelligence Techniques
- 24 Apr 2023
- US
- 11636331
User Explanation Guided Machine Learning
- 16 Jan 2023
- US
- 11556747
Testing Bias Checkers
- 14 Nov 2022
- US
- 11500671
System For Operationalizing High-level Machine Learning Training Enhancements From Low-level Primitives
- 03 Aug 2020
- US
- 10732883
Storage Layer Selection Based Upon Information Assignment
- 03 Aug 2020
- US
- 10733287
Resiliency Of Machine Learning Models

Top collaborators

Parikshit Ram

Research Staff Member

Sameep Mehta

IBM Distinguished Engineer and Senior Manager. Data and AI Platforms. IBM Research AI