Chandrahas Dewangan


Indian Institue of Science, Bangalore



I am a PhD student at the Department of Computer Science and Automation, Indian Institute of Science Bangalore. I am currently working under the guidance of Dr. Partha Pratim Talukdar in the area of Machine Learning and Natural Language Processing at Machine and Language Learning Lab. Previously, I have been masters student in the same department and worked under the guidance of Dr. Shivani Agarwal in the area of Machine Learning at Machine Learning and Learning Theory Lab.


Machine Learning

Natural Language Understanding

Reinforcement Learning

I am broadly interested in methods for Knowledge Graph(KG) creation and expansion and application of such background KGs for end tasks such as Question Answering, Document Classification etc. Currently, I am working on techniques for learning interpretable representations for KGs and Text.


Research Intern

IBM Research Lab, Bangalore

June 2016 – August 2016 (3 months)

Worked on Task Specific Knowledge Graph Construction.

Member of Technical Staff

Veveo India Private Limited, Bangalore

August 2013 – July 2015 (2 years)

Worked on conversation based searches on entertainment domain. It requires solving multiple sub-problems like named-entity recognition, user-intent detection etc. My work is focused on finding user intents and context management during conversation. I am also working on a template-based method which can be used for named-entity recognition and user-intent detection. It can also be used for generating suggestions as user types the query.


Inducing Interpretability in Knowledge Graph Embeddings

Chandrahas, Tathagata Sengupta, Cibi Pragadeesh, Partha Pratim Talukdar


Revisiting Simple Neural Networks for Learning Representations of Knowledge Graphs

Srinivas Ravishankar, Chandrahas, Partha Pratim Talukdar

Automated Knowledge Base Construction (AKBC) Workshop at NIPS 2017

Learning Score Systems for Predicting Patient Mortality in ICUs via Orthogonal Matching Pursuit

Aadirupa Saha, Chandrahas Dewangan, Harikrishna Narasimhan, Sriram Sampath, Shivani Agarwal

International Conference on Machine Learning and Applications (ICMLA) - 2014


Optimization for Machine Learning

Study of Parallel Coordinate Descent Algorithms


Coordinate Descent Algorithms form a class of simple optimization algorithms which has received attention of many researchers in last decade. There has been significant advancements in adapting these algorithms in parallel (multi-core) settings. In this project, we focused on studying parallel versions of Coordinate Descent Algorithms. We also implemented and conducted experiments with some of these algorithms.

Natural Language Processing

Entity Linking


Entity linking(EL) is a process of mapping textual mentions of named-entities in text to an entity in some knowledge base. EL is used in numerous areas of natural language processing to automate structured information retrieval from raw corpus. In this project, we focused on D2W (Disambiguation to Wikipedia) task, where we map textual mentions to corresponding Wikipedia pages. Specifically, we studied the effects of co-reference resolution (using Stanford CoreNLP) on the performance of Wikifier system for D2W task.

Machine Learning

Application of Machine Learning for predicting mortality in ICUs


This project aims to develop a technique for estimating the probability of patients' mortality in the Indian intensive care units. We apply different machine learning techniques (specifically, linear and non-linear logistic regression) to this problem. We also propose a boosting-style approach for predicting patient mortality rates, which automatically builds a score-based system for Indian patient data.

Program Analysis

Null Dereference Analysis in Java Programs


Null derefence is a common bug in programs. This project applies the abstract interpretation framework for the analysis of null dereferences in Java programs using Soot framework.

Expert Examination System

An automated question paper generation system


This project automates the question paper generation process for examinations. It covers the process of creation of questions database, selection of questions for exams meeting certain criteria and generation of encrypted paper and its decryption.

Graphics and OpenGL

Implementation of a Tetrahedral Mesh Viewer


The aim of the project was to implement a basic viewer which can render tetrahedral meshes read from a file. It also supports rendering of individual meshes and group of meshes at different scaling levels.


Indian Institute of Science, Bangalore

PhD, Computer Science and Engineering

Indian Institute of Science, Bangalore

Master of Engineering, Computer Science and Engineering

Bhilai Institute of Technology, Durg

Bachelor of Engineering, Computer Science and Engineering

JRD Higher Secondary School, Durg

AISSCE ( 12th ), Physics, Chemistry, Mathematics


Received Special Recognition Award while working at Veveo R&D

AIR-44 in GATE-2011

Honours in Bachelor of Engineering

Certificate of Excellence in Mathematics in 12th


Representation Learning for Text

CSA Summer School 2016

Introduction to Machine Learning

CSA Summer School 2013


Music (Playing Guitar)


Chandrahas Dewangan —