Interactive Data Analysis & Machine Learning Lessons

I completed my graduation with a degree in Chemistry and went on to earn a degree in Computer Science and Engineering in Computer science and engineering at IIT Bombay. My academic journey began at Jai Academy, where I excelled with a 95.20% score in my intermediate studies. Throughout my academic career, I have garnered numerous achievements and accolades. I was honored with the Charpak Lab Scholarship, which included an internship offer from Sorbonne University, Marie & Curie Campus in Paris, ranked 48th globally. During my second year, I served as a Teaching Assistant for the ME119 course, mentoring over 180 students. I consistently demonstrated academic excellence by achieving the highest AA grade (10/10) in ten courses. Additionally, I mentored over ten students as a Student Mentor for the Summer of Science and Seasons of Code programs. My professional experience includes various internships that have enriched my expertise. At Qure.ai in Bengaluru, I worked as a Software Engineering Intern from May 2023 to September 2023. Here, I added a feature to the Qure App by integrating it with the National Health Authority's ABHA initiative, developing backend APIs using the Django Rest framework and frontend registration forms with ReactJS. At TCS Research & Innovation, I served as a Data Analysis Intern from November 2022 to December 2022, where I conducted detailed data analysis on India's organ transplantation trends using Python and Stata, highlighting significant gender disparities and regional distributions. During my tenure at Lex Res Pvt. Ltd. as a Software Engineering Intern from May 2022 to July 2022, I worked on a text summarization algorithm for a law-based application using NLTK, pre-trained BERT, and LSTM models. I also developed a scraping system on AWS and utilized various AWS services for data storage and deployment. At Feynn Labs, as a Machine Learning Intern from February 2022 to April 2022, I developed a credit risk model with impressive evaluation metrics, including an AUROC of 0.886 and a Gini score of 0.732, using advanced statistical techniques and machine learning models. In addition to internships, I have contributed to several research projects. At IIT Bombay's MEDAL lab, I worked on the Multi-organ Nuclei Segmentation challenge under the guidance of Prof. Amit Sethi, utilizing TensorFlow for digital pathology image processing. I also conducted a comprehensive analysis of hysterectomy prevalence in India, guided by Prof. Mithun Kumar Mitra, using data from the National Family Health Survey and various statistical software. Additionally, I implemented U-Net architecture for aerial imagery segmentation at the MRSLab, IIT Bombay, under Prof. Avik Bhattacharya's guidance. My key projects include developing an object detection algorithm using YOLO for autonomous driving car detection and driver behavior analysis, predicting credit card defaults with various machine learning models, and forecasting stock prices using ARIMA and LSTM models. As the Overall Team Head of the Data Analytics and Visualization Team at IIT Bombay, I led a team of ten, analyzing and presenting insights on institutional data and collaborating with startups and external organizations for real-life projects. My technical skills encompass a wide range of programming languages and frameworks, including C, C++, Python, R, SQL, PostgreSQL, MATLAB, HTML, CSS, JavaScript, and AWS. I am proficient in frameworks like ReactJS, Django Rest Framework, TensorFlow, PyTorch, Keras, Git/GitHub, Google Colab, and Jupyter. My coursework includes subjects such as quantum physics, calculus, differential equations, linear algebra, economics, and remote sensing.