Summary
Experienced Machine Learning Research Intern with a demonstrated history of working in the space research industry. Skilled in data analysis, predictive modeling, and machine learning algorithms. Strong research professional with a Master's degree focused on Computer and Information Sciences.
Experience
Machine Learning Research Intern
Indian Space Research Organisation, Space Application Centre
2024 – 2024
- Engineered an advanced machine learning framework to reconstruct ocean chlorophyll concentrations at 10km pixel resolution from satellite-simulated geospatial data reducing synthesis time by over 75%. Preserving seasonal and spatial variability with a minimal prediction error of 0.169 mg/m³.
- Conducted comprehensive analysis on 600+ million flattened ROMS data, utilizing advanced feature engineering, automated pipelines, and grid search to optimize predictive accuracy and accelerate execution. Applied multi-layer correlation checks, spatial-temporal RMSE plots, time series visualizations, and rigorous sensitivity analysis to extract granular insights into the model’s feature adaptability.
- Collaborated with ISRO scientists, synthesized research outcomes into a peer-reviewed research paper, presenting findings through high-fidelity visualizations and technical reports, culminating in project completion within 50% of the allocated research timeline.
Data Science Intern
Maxgen Technologies
2021 – 2022
- Analysed real estate data encompassing 30+ attributes across Sydney and Melbourne, developing predictive models to forecast property price trends, enabling clients to assess market dynamics and economic indicators for potential investments.
- Applied robust statistical diagnostics, including outlier detection, feature transformations and advanced visual analytics using Seaborn and Matplotlib to enhance data quality and interpretability.
- Constructed a systematic modelling framework integrating XGBoost, Support Vector Regression, Random Forest, and Polynomial Regression, applying iterative hyperparameter refinement to attain 93% predictive accuracy in price forecasting.
Skills
Programming Languages
Data Analysis
Machine Learning
AWS
Data Handling
Data Visualization
Generative AI
Communication
Teamwork
Personal Attributes
Project Management
Projects
Cardiovascular Disease Prediction System
Led development of ML models for heart failure prediction achieving 92% accuracy using ensemble methods like Boosting Regression.
HyPrioriTEA: Intelligent Email Prioritization
Engineered an automated pipeline leveraging Google Email API to process over 1,000 emails with custom prioritization rules.
Story Generation from Multiple Images using NLP
Developed ML pipeline integrating BLIP and Falcon models for image understanding and text generation.
Education
Master of Computer and Information Sciences
The University of Texas at Dallas, Richardson, TX
2026
Bachelor of Technology in Computer Science and Engineering
Indus University, Ahmedabad, India
2024
GPA: 9.84/10