Artificial Intelligence Researcher. Research interests span Deep Learning, Recommendation Engines, Topic models, Deep Reinforcement Learning
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DataSaurus Rex Pvt Ltd
Data Scientist
June 16, 2026 – Present
llms_from_scratch_spring2026
March 12, 2026 – Present
llms_from_scratch_spring2026 — GitHub repository
View Projectdatastructures
April 7, 2022 – April 15, 2022
Python implementations of classical data-structures and algorihms
View ProjectHierarchical-Attention-Networks
August 2, 2018 – August 6, 2018
Implementation of Hierarchical Attention Network model for text classification
View ProjectOptimal-bidding-policy-using-Policy-Gradient-in-a-Multi-agent-Contextual-Bandit-setting
March 9, 2018 – March 9, 2018
We use policy gradient to help agents learn optimal policies in a competitive multi-agent contextual bandit setting
View ProjectCS294
January 21, 2018 – January 21, 2018
Solutions to Deep RL assignments from CS294's Fall 2017 iteration
View ProjectRecommender-Systems-for-Implicit-Feedback-datasets
September 2, 2017 – November 2, 2017
Matrix Factorization augmented with customer item meta data
View ProjectReinforcement-Learning-Easy21
August 31, 2017 – September 2, 2017
Reinforcement Learning for Easy21 (from David Silver's RL course)
View ProjectTree_LSTMs-for-Aspect-based-Sentiment-Analysis
August 13, 2017 – August 16, 2017
Tree Structured LSTM model for sentence level aspect based sentiment analysis
View ProjectCultural Fit Analysis
The candidate's projects are primarily academic or personal, focusing on advanced ML/DL topics. While this demonstrates strong technical interest, there is limited evidence of experience in diverse team environments or large-scale production systems. The projects are highly relevant to a Data Scientist role, indicating a good technical fit, but the lack of varied project types or team-based work limits the assessment of broader cultural fit. The single professional experience is current, but no details are provided.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions are concise, but there is no information on collaboration, problem-solving approach, or communication style in a team setting. No psychometric test results are available.