CV

Education

• M.Tech in Electrical Engineering, Indian Institute of Technology (IIT) Madras, 2023-2025
• M.Sc in Physics, Indian Institute of Technology (IIT) Bhubaneswar, 2021-2023
• B.Sc in Physics, Mathematics, and Statistics, KTHM College (Pune University), 2017-2020

Achievements

• All India Rank - 617 in IIT-JAM 2021 Entrance Examination conducted by IISc Bangalore.
• First Prize in Poster Presentation Competition Held at Sandip University, Nashik.

Work Experience

2024-2025: M.Tech Thesis

• IIT Madras
• 3D High Dynamic Range (HDR) Reconstruction of Dynamic Images using Gaussian Splatting - Supervisor: Prof. Kaushik Mitra
  • Identified the problem of 3D HDR Dynamic Scene Reconstruction from 2D Multi-View images.
  • Explored NeRF and its limitations for 3D HDR scene reconstruction from static and dynamic multi-view images.
  • Working on 3D HDR Dynamics and Static Scene Rendering using Gaussian Splatting with Deep Learning.

2022-2023: M.Sc Thesis

• IIT Bhubaneswar
• Analysis and Implementation of Machine Learning Model on CERN’s Big Datasets - Supervisor: Prof. Seema Bahinipati
  • Handled petabyte-scale datasets from CERN, performed Exploratory Data Analysis to extract meaningful insights.
  • Identified key features, optimized model input, and enhanced the performance of the Boosted Decision Tree algorithm.
  • The Boosted Decision Tree model achieved a 0.98 ROC value, effectively classifying signal and noise.

2018-2019: B.Sc Project

• K.T.H.M. College
• The Exponentially Changing Periodic Probability Density Function (PDF)
  • Developed the Sinex distribution, a novel PDF with multiple peaks, using Laplace Transforms and MGF functions.
  • Derived the Sinex distribution’s mean and variance using the gamma function and Inverse Laplace Transforms.
  • Analyzed the Sinex distribution, showing it approximates the Gamma Distribution under certain conditions.

Skills

Software & Tools

• Microsoft Excel, Microsoft PowerPoint, Microsoft Word, Power BI

Programming Languages

• Python, SQL, C++, MATLAB

Libraries & Frameworks

• Pandas, NumPy, Matplotlib, TensorFlow, Scikit-Learn, PyTorch, Keras, NLTK, spaCy, OpenCV

Personal Projects

Lung Cancer Detection Using CNN

• Developed a CNN for lung cancer classification, achieving 92% validation accuracy on microscopic lung images.
• Achieved 97%, 87%, and 91% F1-scores for three lung cancer types, demonstrating strong model performance.
• Boosted efficiency with regularization & augmentation, achieving 92% macro-average precision, recall, & F1-score.

Autocorrect System

• Engineered an autocorrect system that enhances text accuracy and user experience by suggesting correct words.
• Increased data processing efficiency by 15% by developing a scalable Python script for handling large text files.
• Devised a word variant production method to provide accurate spelling corrections by generating possible words.

Movie Recommendation System

• Built a content-based movie recommendation system using 4,800+ movies to provide personalized suggestions.
• Carried out data pre-processing and feature engineering on text and numerical data, improving accuracy.
• System retrieves and ranks the top 10 similar movies using a similarity matrix, enhancing the user experience.

Chatbot Creation

• Designed a Chatbot model using TensorFlow and Keras, achieving over 94% accuracy in intent classification.
• Mapped user input patterns to specific intents using a JSON-based dataset, enabling content-aware responses.
• Trained the model using embeddings, pooling, and dense layers, with tokenizer and sequence padding.

Relevant Coursework

IIT Madras

• Pattern Recognition and Machine Learning (PRML)
• Natural Language Processing
• Data Analysis & Visualization in R/Python/SQL (DAV)
• Probability Foundations for Electrical Engineers
• Computational Photography
• Image Signal Processing (ISP)

Online/Other Courses

• Data Structures and Algorithms in Python (Udemy)
• Computer Vision with OpenCV and Deep Learning (Udemy)
• Machine Learning, Data Science, and Deep Learning (Udemy)
• Data-Driven Astronomy (University of Sydney, Coursera)
• Linear Algebra (B.Sc. + M.Sc. Course)
• Atomistic Simulations with Python (M.Sc. Course)

Course Projects

Pattern Recognition and Machine Learning (PRML)

• Built Classification models like Naive Bayes Classifier, KNN Classifier, Logistic Regression & Random Forest.
• Implemented Ridge Regression, Lasso Regression, K-Means Clustering, PCA, DBSCAN, and Gaussian Mixture Model (GMM).

Image Signal Processing (ISP)

• Executed various Image Processing tasks in Python, such as:
  • Geometric Transformations
  • Image Mosaicing
  • Shape From Focus
  • Blurring (Space-Variant and Invariant)
  • Otsu’s Thresholding
  • Occlusion Detection

Data Analysis & Visualization (DAV)

• Built a Neural Network from Scratch for handwritten digit recognition achieving 87% train and 86% test accuracy.

Atomistic Simulations (AS)

• Wrote Python Scripts from scratch for creating constrained coordinates of water and gas molecules for visualization.

Service and Leadership

• Student Placement Coordinator: Managed placement season for 200+ students at IIT Bhubaneswar.
• Assistant Coordinator, Counseling Service Team: Guided 80+ freshers on campus at IIT Bhubaneswar.
• Teaching Assistance for Modern Computer Vision course by Prof. Kaushik Mitra , IIT Madras