Hi , I am
Bharath
Challa .

Software Development Engineer /
Machine Learning Engineer / Researcher

Resume

about me

With over 7 years of professional experience, I've honed my skills as a software engineer, specializing in designing and developing various software systems, including Machine Learning, Android, Back-end, and Full-stack applications, as well as proficiency in CI/CD tools. I've had the privilege of working within teams of varying sizes across the globe, where my strong communication skills and collaborative spirit have consistently made a significant impact.

I am passionate about learning and growing in the field of software. and I possess a quick understanding of various technologies, and I am skilled in breaking down complex problems into smaller manageable parts, which I can solve by producing clean, production-grade code. Additionally, I am capable of improving application performance, resulting in timely and efficient project delivery that meets the project's scope and exceeds expectations. I have experience in working with Agile Methodologies, and practicing SDLC process in day-to-day life.

phone

972-804-6333

email

bharathchalla5@gmail.com

website

bharathchalla.github.io

education

2021 - 2023

Master of Science(Thesis)
Computer Science (CS)

The University of Texas at Dallas

Richardson, TX, USA

Thesis topic "Deep Probabilistic Models for Step Recognition and Step Localization in Egocentric Videos."

2010 - 2014

Bachelor of Technology
Computer Science and Engineering (CSE)

Sri Venkateswara University

Andhra Pradesh, India

Specialization on Open Source System and Cloud Computing

skills

Deep Learning

95%

App development

90%

Web Development

85%

Research

90%

Database

95%

Distributed Systems

80%

Creativity

95%

Communication

95%

experience

  • Aug 2022 - Dec 2023

    Research Assistant / Teaching Assistant

    The University of Texas at Dallas
    Erik Jonsson School of Engineering & Computer Science

    Richardson, TX, US

    Engaged in groundbreaking research alongside Dr. Vibhav Gogate, I am actively involved in pioneering Neuro-Symbolic Methods and Perceptually-Enabled Task Guidance (PTG). My current focus revolves around the development of an innovative Neuro-symbolic based Augmented Reality system for Hololens2, leveraging action recognition technology to provide unparalleled task guidance. Additionally, I have played a pivotal role in the collection and streamlining of data for the CaptainCook4D dataset, implementing rigorous pre-processing methodologies to glean insights into procedural errors.

    In my capacity as a Teaching Assistant for ML, Database, and Algorithms, I assume a multifaceted role encompassing the meticulous grading of assignments, hosting informative office hours, and meticulously preparing comprehensive homework solutions. This academic endeavor underscores my dedication to fostering a deeper understanding of complex concepts and empowering students to excel in their academic pursuits.

  • Samsung Research Institute India

    Bangalore, India

    Development of the Samsung Neural Keyboard, a specialized input solution for flagship devices. Utilizing Statistical Language Modeling, we achieved precise touch-point prediction. By integrating advanced techniques like Character Language Model and Word Language Models, I optimized the keyboard's performance, ensuring an intuitive user experience across diverse devices.

    Crafted a compact 0.5 MB Android app employing Deep Neural Network technology for efficient information extraction. This initiative underscored my commitment to innovation and streamlined functionality in software development. Additionally, my research presented at ICSC-2021 stood out as a top contender for the best paper award, highlighting my dedication to advancing information extraction technologies.

    Mar 2018 — Jul 2021

    Lead Software Engineer

  • Mar 2016 - Feb 2018

    Senior Software Engineer

    Samsung R&D Institute India

    Bangalore, India

    Spearheaded the development of modules aligned with design specifications, focusing on implementing flagship device features. My role also encompassed thorough debugging, where I conducted root cause analysis to identify and rectify defects efficiently. With proficiency in module development, flagship device feature implementation, and adept debugging skills backed by root cause analysis, I ensured the seamless integration of cutting-edge functionalities into the flagship devices.

    Developed machine-learned natural language models aimed at enhancing accuracy by incorporating variations and ensuring balanced data distribution across classes. This involved meticulous data balancing techniques and introducing diverse variations within the machine-learned models to bolster their accuracy and robustness.

  • Samsung R&D Institute India

    Bangalore, India

    Developed a UI Web portal tailored for deployment and monitoring of development status, build progress, and results. This involved designing and implementing a MySQL database schema meticulously crafted for seamless integration within the Dashboard project. Leveraging technologies such as Spring Boot and Micro Services facilitated efficient web development, while CI/CD tools like Jenkins and QuickBuild streamlined the deployment pipeline.

    Performance optimization for the S-Health app, significantly reducing response time and memory usage while enhancing the overall user interface. Applying advanced concepts such as Object-Oriented Analysis and Design (OOAD) principles played a pivotal role in improving app performance and delivering an enhanced user experience.

    Jul 2014 — Feb 2016

    Software Engineer

profiles

Linkedin
Linkedin
GitHub
GitHub
Google Scholar
Google Scholar
leetcode
leetcode
Kaggle
Kaggle
HackerRank
HackerRank
CodeChef
CodeChef

Projects

Publications & Patents

CaptainCook4D: A dataset for understanding errors in procedural activities

DMLR @ICML 2023: 10.48550/arXiv.2312.14556

Deep Probabilistic Models for Step Recognition and Step Localization in Egocentric Videos.

 

LiteMuL: A Lightweight On-Device Sequence Tagger using Multi-task Learning

ICSC 2021: 10.1109/ICSC50631.2021.00007

Emplite: A lightweight sequence labeling model for emphasis selection of short texts

ICON 2020 conference: 10.48550/arXiv.2101.03025

Methods and systems for predicting keystrokes using a unified neural network

Patent: US20210173555A1

Certifications

contact me

Bharath Challa

Software Development Engineer /
Machine Learning Engineer /
Researcher

phone

972-804-6333

email

bharathchalla5@gmail.com

website

bharathchalla.github.io