
Graduate Research Assistant at Biocomplexity Insititute, Indiana University.
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Indiana University
Data Scientist
June 26, 2026 – Present
Langgraph-Blog-Generator
August 8, 2025 – August 9, 2025
Langgraph-Blog-Generator — GitHub repository
View Projectmakemore
July 29, 2025 – August 14, 2025
Make More Inspired by Andrej Carpathy's make more
View ProjectAutograder
February 25, 2023 – February 25, 2023
Implemented hough transformation and canny edge detection to extract OMR regions from answer sheet. Used K means clustering to detect filled regions. Encrypted and injected correct answers in the answer sheet using barcodes
View Projectimage-transformations
February 25, 2023 – February 25, 2023
Created transformation matrices based on options from command line including Translation, Eucledian/ Rigid Transformation, Affine transform. Created an inverse wrap by multiplying a homogeneous point with inverse translation matrix and used Bilinear interpolation to fill in the remaining gaps
View ProjectSemi-supervised-abusive-language-detection
June 13, 2022 – June 13, 2022
Semi-supervised-abusive-language-detection — GitHub repository
View Projectunsupervised-scene-segmentation
May 11, 2022 – May 11, 2022
I explore and compare different techniques for unsupervised scene segmentation. I try to answer these research questions: 1.) Can unsupervised convolutional neural networks learn enough structure from data to generate good quality segments? 2.) Is spatial continuity important to generate good quality clusters? 3.) Can we improve results from CNN and GMMs using K-means?
View ProjectImproving-Image-Captioning-using-Depth-Maps-on-Visual-Genome-Dataset
May 11, 2022 – May 11, 2022
In this project, I experiment with the hypothesis that adding depth map information to visual genome dataset generates better scene graphs. The newly generated relations (subject - predicate - object) are used to train an image captioning model. The relations are generated using a Fully Connected Network which takes class labels, visual features, depth features and bounding box locations as inputs and generates a relation between subject and object in the image. The depth features are extracted using a ResNet-18 inspired model. Visual features are extracted from a VGG model pertained on Imagenet. Depth maps are generated by passing visual genome dataset and NYU-depth-v2 dataset as input to a Reset-50 based architecture
View Projectfetch-and-slide-HRE-PRE
April 5, 2022 – April 30, 2022
In this project, I attempt to solve fetch and slide open gym environment with Hindsight Experience Replay and the I experiment with Prioritised experience replay to see if there are any performance improvements
View ProjectAI-Researcher-Interview-Prep
March 11, 2022 – March 11, 2022
Repository contains leetcode questions, mathematical concepts and applied machine learning, reinforcement learning techniques codes
View ProjectCultural Fit Analysis
The candidate's project portfolio shows a strong inclination towards research and experimentation in AI/ML, which aligns well with an innovative and learning-oriented culture. The diversity of projects (image processing, NLP, reinforcement learning) suggests adaptability and a broad interest in the field. However, the lack of team projects or professional experience beyond a current role at a university (with no details) makes it difficult to fully assess cultural fit in a corporate environment.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions indicate a proactive and experimental approach to problem-solving, but there is no information on collaboration, communication style, or stress handling.