About me

I am a Software Engineer with a strong foundation in technology and a relentless passion for solving complex problems through elegant software solutions. Currently, I am pursuing a Master's degree in Information Science with a specialization in Data Science at the University of Texas at Austin. My journey in the field of technology revolves around my ability to break down intricate challenges into intuitive sub-problems, ultimately leading to innovative and efficient software solutions.

In my current role, I serve as a Natural Language Processing (NLP) Machine Learning Engineer and a dedicated Teaching Assistant. I am committed to imparting knowledge to aspiring programmers, introducing them to the dynamic world of Artificial Intelligence within the healthcare domain. My professional background spans the development of deep learning models for Natural Language Processing, computer vision, and time-series radar data analysis. Additionally, I excel in the creation of high-performance computational (HPC) software solutions.

I am deeply committed to research and development, knowledge sharing, mentorship, and continuous learning. I have a proven track record of developing intricate deep learning software that runs seamlessly on System on Chips (SoC). My colleagues often commend my profound understanding of technology and my unwavering commitment to ethical practices.

Beyond my technical expertise, I hold a profound vision for a world where trust and unity are strengthened. My mission is to harness my skills to unravel the complexities of our world, simplifying it and making it a better place for everyone. I am steadfast in my quest to turn this vision into a tangible reality.

What's going on currently

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    NLP Machine learning Engineer

    Working on Large Language Models for developing resume screening software using NLP.


    Teaching Assistant

    Working with Dr. Ying Ding for application of deep learning in healthcare domain.

  • Master of Science

    Masters of Science (MS)

    Currently pursuing Masters of Science at University of Texas at Austin. Majoring in Information Science specializing in Data Science and Applied Machine Learning.

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Employers

Experience

  1. NLP Machine Learning Engineer, Vee Ventures

     June'23 — December'23
    • Led a team of 3 for fine-tuning LLM on distributed GPU clusters using Snowflake to transform text into knowledge graph utilizing graph and Vector DB, improving existing recommender system by 65%.
    • Orchestrated data modeling, algorithm development cycle and deployed an end-to-end NLP pipeline on the AWS platform processing 14,500 resumes per hour on an average and reduced cycle time by approximately 54%.
    • • Engineered chatbot using RAG, powered by Langchain and Mistral 7B enabling recruiters to identify candidates.

  2. Teaching Assistant - College of Natural Science, UT Austin

     Aug'23 — ongoing
    • Assisted Dr. Ying Ding in developing the curriculum to 700+ online graduate students. Provided individualized attention and assistance to 50+ students during office hours, clarified student's doubts on the active class forum, graded & designed exams, homework & programming assignments based on concepts from multiple domains of artificial intelligence applicable in healthcare sector.

  3. Deputy Engineer (Software - Machine Learning) Radars R&D

     Oct'18 - July'22
    • Multimodal System: Designed and developed CamRadNet, a multimodal deep neural network combining image and RADAR data for object detection and tracking. Improved mAP by 42% over single modal network.
    • Upgraded object detection and tracking system through training, fine tuning using Pytorch and deployed deep learning model on Tegra K1 SoC. Realized 14% improvement in mAP at 0.5 IoU threshold and 30 frames/second.
    • Optimized deep learning model for GPU platform using TensoRT by model quantization and layer fusion techniques. Reduced memory footprints and improved inference speed by 7 times while maintaining accuracy.
    • Synthesized images using Generative Adversarial Network to supplement training data for deep neural networks.
    • Signal Processing (Time Series data): Designed and developed CNN-LSTM deep learning architecture using Pytorch for time-series radar target classification on GPUs, capturing complex relationships between features and reduced computation time by 16 folds while maintaining accuracy, containerized using Docker. (Rank-1 acc: 93.2%)
    • Conducted large scale time series data analysis and visualization, utilized VARIMA for analyzing feature interdependency, spectral analysis, granger causality analysis, and clustering and improved tracking by 27%.
    • Implemented Interactive Multiple Model (IMM), fusing large scale sensor data from multiple radar systems on Linux, conducted unit testing and integrated testing and improved ground surveillance tracking by 55%.
    • Employed middleware using Java enabling efficient communication via ethernet packets in a Linux environment.
    • Conducted unit testing and integrated testing using GoogleTest and GitHooks for automation.
    • Utilized MLFlow and Jenkins for deployment, continuous training, and monitoring of ML models. Maintained inference codes and models using Git for version control.
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Education

  1. University of Texas at Austin

     2022 - Ongoing

    Masters of Science - Information Science (specialization in Data Science and Applied Machine Learning)
    GPA: 3.93 out of 4.00

    • Working as a Teaching Assistant for AI in Health at the Department of Computer Science, University of Texas at Austin.
    • Coursework: Computer Vision, Parallel Computing (ongoing), Machine Learning, Deep Learning and multimodal system, Natural Language Processing.
    • Technical Skills: C++, Python, PyTorch, NumPy, scikit-learn, jupyter notebook, JavaScript (learning).
    • Personal Skills: Problem solving, Time Management, Leadership.

  2. B.M.S College of Engineering

    2014 - 2018

    Bachelor of Engineering - ECE (minor in Mathematics)
    GPA: 9.04 out of 10.0

    • Served as Club President at BMSCE Fine Arts Club, organizing numerous events including cultural and technical fests BMSCE Utsav and Phase Shift.
    • Increased annual company participation (for career fair and campus recruitment) by 20% as Student Coordinator at Training and Placement Cell, BMSCE.
    • Participated in various national level technical Hackathons, technical workshops.
    • Coursework: Digital Signal processing, Operating Systems, Microcontroller programming, Unix Tools and Scripting, Data Structures & Algorithms, Computer Networks, Object Oriented Analysis & Design, probability theory, Linear Algebra.
    • Technical Skills: C++, C, Java, Web Technology (HTML, CSS, Bootstrap, Vanilla JavaScript), Embedded-C (Arduino), IoT devices (Arduino, IR Sensors, lidar, etc.).
    • Personal Skills: Problem solving, Communication, Personality Development.

Projects

Contact

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