Soundarya Krishnan

Hey! I am Soundarya Krishnan, a master's student in the Machine Learning Department at CMU. I work in the intersection of Machine Learning and Software Development. I was previously working as a research intern at Microsoft Research, where I was advised by Dr. Amit Sharma. Prior to that, I was a research affiliate at the Fluid Interfaces lab at MIT Media Lab, where I was advised by Prof. Pattie Maes.

I did my undergraduation in Physics and Computer Science at BITS Pilani Goa. During the course of my undergraduation, I was a researcher at APPCAIR in collaboration with TCS Research, where I was advised by Prof. Ashwin Srinivasan . Our work was largely in collaboration with Dr. Lovekesh Vig from TCS Research and Innovation Labs , and our research focus was AI for Healthcare.

I’m broadly interested in leveraging the power of Machine Learning to develop deployable solutions for social impact. I'm especially interested in improving public healthcare systems, and building interpretable and explainable systems for the same. Additionally, I'm very passionate about bridging the gender gap in technology, and co-founded the BITS Goa Women in Tech organisation!


  • August 2021: Started graduate study at CMU!
  • August 2021: Received the Bhushan Bhatia Graduate Application Scholarship!
  • July 2021: Started working at the ACMI lab as a Research Assistant!
  • June 2021: Reviewing for the CA2MH Workshop at ICML 2021!
  • April 2021: Awarded a 100% scholarship for the Fall 2020 semester!
  • March 2021: Very happy to announce the release of the new version of DiCE. This version now supports the generation of counterfactuals for sklearn models, multiclass classification problems, regression problems and more!
  • February 2021: Poster at WiDS Cambridge 2021 was selected for a lightning talk (Top 10 among 50 accepted posters)!
  • February 2021: Selected as a reviewer and mentor for the AI for Public Health Workshop at ICLR '21!
  • January 2021: Very excited to be an instructor for the BITS Pilani CTE course, 'An Introduction to Causal Inference'! You can view the course website here.
  • January 2021: Extremely thrilled to note that our submission at YRS, CODS-COMAD 2021 won an Honourable Mention! Check out our presentation and Extended Abstract!
  • January 2021: Started my thesis at Microsoft Research!
  • December 2020: Preprint on Evaluating Explanations for COVID-19 Chest X-Rays out!
  • November 2020: Ranked 2nd in the Ingenuity Challenge organized by the University of Adelaide at CAISS 2020!
  • October 2020: Extended Abstract on Network Community Analysis based enhancement of Online Discussion forums accepted at Young Researchers' Symposium, CODS-COMAD 2021!
  • September 2020: Ranked 7th among participating women in India in Code-Hers 1.0, organised by NIT Warangal!
  • September 2020: Presented my work on social networks for streamlining information flow in chats at YCCE MEDIA!
  • September 2020: Awarded 1st place in ACM-W India Celebrations of Women in Computing Poster Competition!
  • August 2020: Featured on a Times of India article on the pre-placement offers at BITS Goa!
  • August 2020: Started my undergraduate thesis at MIT Media Lab!
  • August 2020: Paper on the detection of COVID-19 from chest X-rays accepted to the TIA Workshop at MICCAI 2020!
  • August 2020: One of 50 students selected throughout India for the prestigious Google AI Summer School for the HCI + AI4SG track
  • August 2020: Received a pre-placement offer from Uber to join full time!
  • August 2020: Paper on knowledge transfer in lesions accepted to the MIL3ID Workshop at MICCAI 2020!
  • July 2020: Received the prestigious Grace Hopper Celebration India Scholarship 2020 for women students from computing, engineering and IT backgrounds!
  • May 2020: Co-founded the BITS Goa Women in Tech organisation !
  • May 2020 Mentioned in MILA's whitepaper as a contributor for the software of a Peer to Peer COVID tracing app for use in Canada!
  • May 2020: Started an internship at Uber as a software developer
  • Jan 2020: Received 100% scholarship from BITS Pilani Goa for excellent performance in academics (Ranked 6 among 660 students in the batch, Ranked 1 among 56 students in the Physics Department).
  • Nov 2019:1st Runner-up in India for the NETAPP SheCode hackathon
  • May 2019: Started my internship as a MITACS Globalink Scholar in mathematics at Dalhousie University, Halifax!


Research Intern @ Microsoft Research

Jan 2021 to June 2021

Working under the guidance of Dr. Amit Sharma at Microsoft Research on model explainability using counterfactuals. One of the major contributors for the Diverse Counterfactual Explanations (DiCE) for ML library. Added support for non-gradient based models and efficient generation of counterfactuals. New release of the library out soon!

Software Developer Intern @ Uber

May 2020 to July 2020

Worked in the AdServer team. Used ideas in Reinforcement Learning (Bayesian Thompson Sampling for the Multi Arm Bandit problem) to solve the Explore-Exploit Problem in picking Advertising. Worked with Java, Python, Hive, Apache Spark, SQL, HDFS, Amazon AWS Lambda.

Researcher @ APPCAIR & TCS Research

Jan 2020 to Dec 2020

Working under the supervision of Prof. Ashwin Srinivasan and Dr. Lovekesh Vig on projects involving building interpetable and explainable Deep Learning models for healthcare.

MITACS Globalink Scholar @ Dalhousie University

May 2019 to July 2019

Was advised by Prof. Neil Julien Ross at Dalhousie University for a project on optimisation of Quantum circuits. Worked on utilising ideas in Group Theory and Linear Algebra (primarily the Lempel Algorithm) to reduce the number of expensive gates in a quantum circuit.

Summer Research Intern @ CEERI

May 2018 to July 2018

Advised by Prof. Sundaresan Balasubramaniam at CEERI Chennai . Developed an automated leather defect detection and analysis system using tensorflow in python for object detection and classification. Used heavy Image Processing in OpenCV for feature extraction, and Visual C++ for GUI, including MYSQL 5.7 for the database. Also used a uEye camera compatible with OpenCV API functions for real time classification.


FASCIA: An Open-Source Web-Based SleepStaging Tool for Researchers

Under Review

In this work, we built CNN-LSTM models (with explanations) for automatic sleep scoring, along with signal processing to aid sleep researchers in sleep staging. We further integrated the pipeline on a real-time open-source web-based interface using socket programming, Node.js, Express.ejs for the website, D3.js for the visualization, and MongoDB for the database. We also obtained feedback regarding the efficacy of the various explanations and tools that we provide from sleep researchers. Preprint out soon!

Constructing and Evaluating an Explainable Model for COVID-19 Diagnosis from Chest X-rays

Under Review

In this work, our focus is on constructing models to assist a clinician in the diagnosis of COVID-19 patients in situations where it is easier and cheaper to obtain X-ray data. We use a new COVIDr dataset with important radiological annotations from a practicing radiologist. We build a deep neuro-symbolic model to diagnose COVID-19 and provide visual and textual explanations, with no significant loss in predictive accuracy compared to an end-to-end model. We find that the radiologist prefers simple representations, both visual and textual to aid in diagnosis.

CovidDiagnosis: Deep Diagnosis of COVID-19 Patients using Chest X-rays

Accepted at TIA Workshop at , MICCAI 2020

Built a segmentation model in order to isolate the lung region from the rest of the X-ray, and built an interpretable model (with symptoms checking) to detect COVID-19 in chest X-Rays. Our model has an ROC of 99.8. Currently working on generating LIME-style explanation for the COVID-19 predictor in terms of the symptoms, so as to have an explainable model.

A Case Study of Transfer of Lesion-Knowledge

Accepted at MIL3ID Workshop , MICCAI 2020
Evaluated the efficacy of transfer of a brain-lesion model to the lung, and the transfer of a lung-lesion model to the brain by comparing against a model constructed: (a) without model-transfer (i.e. random weights); and (b) using model-transfer from a lesion-agnostic dataset (ImageNet). In all cases, our lesion models were found to perform substantially better.

Online Learning Assistant with Network Community Analysis

1st place at ACM-W India Celebration Poster Competition , Extended Abstract won a Honourable Mention at Young Researchers' Symposium, CODS-COMAD 2021!

Built an NLP & Social Networks-based Python tool that scrapes data off the Telegram chats, classifies users according to activity, and suggests experts as well as timings for various topics, using tools such as Gephi. Tested on Ubuntu IRC chat logs, and has been implemented for a university chat group.

ECG Signal Analysis on an Embedded Device for Sleep Apnea Detection

Part of the work was accepted as a full paper at ICISP, 2020, another part accepted for oral presentation at IVSP, 2020

Developed a portable, cost-effective and customisable Electrocardiograph(ECG) Signal analyser for real time sleep apnea detection. We analysed our proposed implementation through a complete run on the MIT-Physionet dataset. Due to the low computational complexity of our proposed method, we find that it is well suited for deployment on embedded devices such as the Raspberry Pi.

Secure, fast, and efficient optimization of quantum circuits

View project report here!

Quantum circuits model a sequence of operations to be performed by a quantum computer. CNOT Dihedral is an important class of such quantum circuits. The project demonstrated that the cost of a quantum circuit could be optimized by reducing the # of T gates and replacing them with less expensive gates such as (S, CS or CCZ). This was shown by noting that every CNOT Dihedral circuit can be modeled by a phase polynomial, which in turn can be represented as a tensor. We can then use the Lempel algorithm to factorize this matrix, and thus reduce the T-count (details are given in the report).


Our Story: Why we started

BITS Goa Women in Tech (BGWiT) is an organisation that I co-founded along with some of the most brilliant and hardworking women I've met. Here's a quick blog post about why we started! To find out more about us, check out our website!

My experience as a MITACS Globalink Scholar

I had the best experience as a MITACS exchange student pursuing research at Dalhousie University, Halifax under Prof. Neil Julien Ross (one of the best professors that I've had the opportunity of working under)! Check out this blog post to know more about the MITACS application procedure, and my experience there!