AC.

Hi, I am Apoorv Chandrakar

And this is One Life, FYI!

A Graduate Scholar

Passionate about data science, machine learning, and artificial intelligence. I specialize in building predictive models and developing efficient algorithms to solve complex problems. My expertise includes Python, machine learning frameworks, and database management.

Resume

Education

Graduate Professional Certificate in Databases

Stevens Institute of Technology, Hoboken, NJ

Sept 2022 – May 2024

Master of Science, Computer Science

Stevens Institute of Technology, Hoboken, NJ

Sept 2022 – May 2024

Bachelor of Engineering, Computer Science and Engineering

Chhattisgarh Swami Vivekanand Technical University, Bhilai, CG

Sept 2015 – May 2019

Projects

Extended SQL

Developed a custom extension of SQL engine aimed at enhancing the performance of OLAP (Online Analytical Processing) queries. Achieved a significant reduction in query execution time by 20% through the implementation of an efficient single-pass algorithm for computing aggregates. Additionally, designed and implemented a query parsing and arithmetic operations module, enabling SQL-like querying within the project environment.

  • SQL
  • Python
  • Database Optimization

Project Homie

Led the ideation and system design of Homie, a web application centered around roommate matching utilizing a sophisticated recommender system. Recognized for achieving exceptional results, including a best-in-class score of 103/100 in CS546. Key contributions include the development of a unique recommendation engine, REST APIs, and other essential functions crucial for seamless roommate matching.

  • Recommendation Systems
  • REST APIs
  • Web Development

University Admit Predictor

Engineered a sophisticated predictive analytics model leveraging ensemble learning techniques to forecast university admissions without relying on external essay inputs. The model achieved remarkable accuracy of approximately 72% in cross-validation tests, showcasing its effectiveness in predicting admissions outcomes. Notable contributions include the implementation of Gradient Boosting Machine (GBM) and advanced tuning strategies to optimize predictive performance.

  • Machine Learning
  • Predictive Analytics
  • GBM

Experience

Graduate Lab Assistant

Stevens Institute of Technology

Feb 2023 – Present

Developed backend modules for data ingestion and automated daily digests for stock performance and media sentiment analysis. Contributed to research in applying Reinforcement Learning to financial systems.

AI Research Fellow

Stevens Institute for Artificial Intelligence

Jun 2023 – Aug 2023

Led the development of a health-focused chatbot, processed data from fitness trackers and surveys, and utilized time series analysis techniques for insights. Implemented explainable AI methods for model interpretation.

Data Engineer / ML Consultant

Tata Consultancy Services

Jun 2019 – Aug 2022

Spearheaded the development of data pipelines for large-scale data processing and analysis. Designed and implemented machine learning models for various client projects, including predictive analytics and recommendation systems. Collaborated with cross-functional teams to deliver high-quality solutions to clients.

Skills

Contact

Email me