Introduction to Programming with MATLAB

Explainable Machine Learning with LIME and H2O

NVIDIA-Certified Professional: Accelerated Data Science

Sequence Models

Neural Networks and Deep Learning

Structuring Machine Learning Projects

Facial Expression Recognition with Keras

Machine Learning

Deep Learning Specialization

Speech Signal Processing

Using Git and Github

Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization

Fundamentals of Scalable Data Science

Convolutional Neural Networks

Accelerating End-to-End Data Science Workflows

Technothlon is an international school championship organized by the student fraternity of Indian Institute of Technology Guwahati. Through a series of events involving mental aptitude, logic, and dexterity, it seeks to provide school students a platform to build fundamental experience and knowledge, to exercise coordination skills, and to think out of the box.

City Representative

Guiding first-year students, bridging the gap between students and faculty

Academic Representative

Bachelor of Technology (B.Tech.)

Master's degree

High School

- Project description: To study the role of thermostat, OLP, PTC, PCB in double door (FF) refrigerators and design approaches to reduce their FFR (Field Failure Rate)
- Developed conceptual understanding of quality management and assessment techniques by participating in practical demonstrations in the factory.
- Learnt about the interplay of and gained hands-on-experience on usage of various electronic components like PCB, thermostats, OLP, PTC etc in refrigerators produced by LG
- More details on the project can be accessed here- http://kunal-dhawan.weebly.com/lg-india.html

Summer Internship

Deep Learning Applied Research intern with the NeMo team https://github.com/NVIDIA/NeMo

Applied Research Intern

Member of the Speech and Vision team, Reliance Jio AI CoE. Worked on multiple interesting problem statements which had direct impact on various Jio businesses-

Speech and Audio processing:
- Developed text-to-speech (TTS) solutions for Indian languages, responsible for the entire process from system design to deployment. Solution developed was used in Jio Machli application which was awarded the AEGIS Graham Bell Award, 2019.
- Built novel speaker and style transfer TTS systems for Hindi, Tamil and Telugu languages which are currently being used across multiple businesses in the Jio fraternity like Retail, Fashion and Healthcare.
- Developed a robust speech based keyword recognition system to be integrated with Jio Retail mobile application. The system enables users to search for products, add them to cart and communicate with the app using their voice.
- Built a virtual call center assistant from ground up which separates customer and operator segments from a single channel input and

Data Scientist

Project title: Microcontroller based embedded system design
Advisor: prof. Dhananjay Gadre

- Learnt about the working and design of microcontrollers and studied about related concepts like memory management, JTAG, clocks, timer, comparator, communication protocols, ADC.
- Obtained practical experience on PCB designing and Fabrication using EagleCAD for schematic and board file design and Toner transfer method for fabrication.
- Worked on three main projects during internship: MSP430 Framework, analog color mixer and switching power supply design.

Winter Research Intern

Research Scientist II

Graduate Teaching Assistant for the course 10-605/10-805 'Machine Learning with Large Datasets' with prof. Ameet Talwalkar and prof. Henry Chai
Topics: Spark, Distributed Computing, Hashing Theory, Cloud Computing, Large-Scale Optimization, Parallel/Distributed DL, Optimization for DL, Model Compression, Neural Architecture Search, Federated Learning 
Course website: https://10605.github.io/fall2022

Graduate Teaching Assistant

Advisor: prof. Arun Kumar

Project description:
- Worked on improving the accuracy of Inertial Navigation System (INS) equations by implementing
differential equation based solution in the discrete-time domain instead of the classical linearized
approximation.
- Developed a novel Kalman Filter based Multi-Sensor Data Fusion algorithm for utilizing GPS data available at low frequency and merging it with IMU sensor output to improve the accuracy of vehicle tracking
- Evaluated the implemented MATLAB code with Monte-Carlo Simulations to demonstrate its performance under varying initial conditions and trajectories
- Keywords: Signal Processing, Multisensor Data Fusion(MSDF), Kalman Filter, MATLAB

Summer Research Intern

Solving some complex Conversational AI and Natural Language Understanding problems in the Indian context

- Led project for SOP step adherence and customer satisfaction detection from raw telephonic speech. Built a robust system from scratch, right from problem understanding with the client (TataSky), data collection & labelling, and defining KPIs to system deployment for processing daily volume of 100+ Hrs of telephonic conversation. The system performed 1) customer problem identification, 2) tracking SOP steps followed (text-based approach on ASR output, used fine-tuned RoBERTa),  3) estimating time taken for each SOP step (to detect anomalies, aid training of customer care executives), and finally 4) detected customer sentiment (speech + text). 

- Developed systems for telecom domain ASR for 5 Indian languages: Hindi, Telugu, Tamil, Marathi, and Bengali from scratch. Worked on the entire pipeline starting from data procurement, coming up with creative ways for data annotation to ge

Project Title: An i-vector based Non-Negative Matrix Factorization approach towards Noise Robust Automatic Speech Recognition
Advisor: prof. Shrikanth Narayanan

Motivation: Given the rise of consumer-centric applications like voice interaction with mobile devices and home entertainment systems, it is imperative for Automatic Speech Recognition systems to be robust to the full range of real-world noise and other acoustic distorting conditions.

Project description:
- Explored the efficacy of non-negative matrix factorization based time-activations as acoustic features for building an Automatic Speech Recognition System
- Proposed a novel noise robust non-negative matrix factorization approach based on the concept of total variability modelling, which comfortably outperforms the state of the art on the challenging Aurora-4 dataset

Undergraduate Research Fellow

Conversational AI and LLM applied research @ NVIDIA NeMo

Research Scientist

Senior Research Scientist

Building multimodal LLMs

Know about Kunal Dhawan's work experience, education, bootcamps, certifications, and much more. Kunal Dhawan