SWASTIK NATH

Enhanced customer support experience through the implementation of Natural Language Processing (NLP), Computer Vision (CV), Large Language Models (LLM), Audio Processing, and Multi-modal large-scale models. Have hands-on experience in training in-house LLMs, fine tuning LLMs and deploying in production.

Developed computer vision applications focused on facial and voice recognition, leveraging cutting-edge technologies. Led the design and implementation of ETL pipelines utilizing Scrapy, BigQuery, and Airflow on the Google Cloud Platform (GCP).

Led the development of the database design and data collection pipeline for Intelligent Retail Pvt Ltd's distribution business. Spearheaded the creation of the backend infrastructure for RIPPLR's Champion Distribution Management system, utilizing a tech stack that included Node.js, MySQL, PostgreSQL, MongoDB, Nest.js, and React. Created Reenforcement Learning models to optimize FMCG warehouse products and delivery of them.

Designed and developed a human emotion decoding system utilizing Computer Vision, Face Detection, Feature Extraction, Emotion Detection, Machine Learning, Deep Learning, and Django frameworks.

Completed Data Science online course provided by Springboard with deep learning specialisation. During this period, I made many projects on data wrangling, story telling, recommender systems, handwritten digit recognition.

Completed a Data Analytics course sponsored by Ministry of Environment Forest & Climate Change (MoEF & CC), Govt. of India. During this period I had exposure to R Programming, statistics, statistical learning, big data, hadoop, GIS etc.

Studied subjects including C, MATLAB, Data Structure and Algorithms, High performance Scientific Computing, Linux and Unix Operating System, Networking, Software Development, Computer Science, Statistics, Physics, Chemistry, Biology, Bio Technology.