People / Students / Class of 2025
Shashwat Hemant Kakkad holds a bachelor’s degree in Electronics and Instrumentation Engineering from Birla Institute of Technology and Science Pilani, India, obtained in 2021. During his junior year, he developed a strong foundation in data acquisition systems, data ingestion methods, and circuit designing for intelligent sensors, which enabled him to intern as a research associate at the Department of High Energy Physics, Tata Institute of Fundamental Research (TIFR), Mumbai, during his senior year. His research on cosmic muon detection involved engineering a compact muon tracker with extensive data collection and detection capabilities. This endeavour encompassed hardware design using KiCAD, data flow and collection logic in C++, and creating a mobile app for wireless data transmission to a NoSQL database. Exposure to big data and computing at TIFR inspired him to pursue diplomas in Data Science and Programming from the Indian Institute of Technology Madras, equipping him with foundational skills in machine learning, data management, and practical experience deploying machine learning pipelines. Before joining the MLDS program, Shashwat worked as a Data Scientist at Novartis, a global healthcare leader, for three years. At Novartis, he developed scientific solutions for Global Clinical Operations, addressing challenges such as data quality, predictive analytics, process optimisation, and risk mitigation. His role sparked a profound curiosity to unlock the full potential of data science, encouraging him to pursue an advanced degree in machine learning and data science. During his time at Novartis, he led several significant projects. One standout project, ‘Senti-Q’, leveraged sentiment analysis to enhance the management of clinical data queries and streamline communication efficiency. Built on QlikSense, Senti-Q was deployed across 1905 sites in 58 countries, covering 16 high-priority and critical mega trials in 5 therapeutic areas, achieving 84% sentiment prediction accuracy with the help of a large language model. Another critical project, ‘CheckMate’, involved developing a data-driven web application using the Streamlit application framework to streamline data validation and cleaning processes for 614 trials. This application integrated multiple data sources using Python and Pandas, reducing review time for clinical teams by 1.5 hours daily and saving 19% Full-Time Equivalent (FTE) consumption, amounting to $1 million annually. The Whole Brain Engineering philosophy of the McCormick School of Engineering resonates with Shashwat's academic and professional journey. He believes the MLDS program's industry-focused curriculum and interdisciplinary approach to Data Science, Data Engineering, Machine Learning, and Artificial Intelligence provide a distinctive perspective on the significance of data as an enterprise asset in various sectors. Shashwat is particularly enthusiastic about collaborating with peers in the Industry Practicum and the Capstone Design Project, as he enjoys experiential learning. His interests lie in building expertise in areas such as real-time model hosting, cloud model inference, NLP, and MLOps. Drawing upon his professional experience as a Data Scientist and his current studies in the MLDS program, he aims to lead product development as a Senior Data Scientist and deliver impactful human-centered data products to the market.
