Adv DS Associate Consultant @ ZS, IIT Alumni, 3 YOE, Ex Scho @ OSU-US, Ex-HPE, MTech-DSAI, BTech-CSE & 2 publications, Skilled in ML, NLP, DS, GenAI & EdgeAI..
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ZS Associates
Software Engineer
June 15, 2026 – Present
PowerBI-Uber-Data-Analytics
October 18, 2025 – October 18, 2025
This project is an Uber Ride Analytics Dashboard built using Power BI. It analyzes Uber NCR ride-booking data to provide actionable insights on booking trends, cancellations, customer satisfaction, and vehicle utilization.
View ProjectAdaptive-Split-Federated-Learning
February 11, 2025 – Present
Adaptive Split Federated Learning: Efficient Training and Robust against Distribution Shifts at Test Time
View ProjectLead_and_Interaction_Management_System_using_FastAPI_Streamlit_PostgreSQL_Docker_and_DockerCompose
January 3, 2025 – January 3, 2025
Designed and implemented an end-to-end Lead Management System for tracking leads, interactions, and performance metrics, integrating FastAPI for backend, Streamlit for frontend, and PostgreSQL for the database, in a scalable architecture using Docker and Docker compose, enabling seamless development, testing, & production workflows.
View ProjectDSP505Project
November 17, 2023 – November 30, 2023
The project implements an idea to detect tailgating into a restricted premise using computer vision techniques. The idea proposed here makes use of an automated system which makes use of a Single Shot Detector (SSD)
View ProjectCompany360---ML_pipeline_for_CompanyAnalysis_using_ETL_DataMining_LSTM_Transformer_and_PythonLibrary
November 8, 2023 – May 31, 2024
Built a machine learning pipeline for company analysis by integrating ETL, data mining, and predictive modeling using LSTM, Transformers, and Python libraries such as HuggingFace and Transformers, enabling insights about the company.
View ProjectDataAnalyticsProject_Customer_Churn_Prediction
October 16, 2021 – December 5, 2021
The primary problem to address is to investigate and give you a predictive version for predicting Credit Card Customer Churn so as to aid corporations tormented by customer churn such that they could hit upon Churning Customers as early as feasible and might take essential movement so as to maintain the Churning Customers
View ProjectApplications-of-AI-in-Fake-News-Mitigation
June 11, 2021 – May 29, 2024
This repository is the implementation for the paper titled: Automated and Interpretable Fake News Detection with Explainable Artificial Intelligence
View ProjectLifestyle_Management_App---An_Android_Application_in_Java
May 31, 2021 – May 29, 2024
An Android Application in Java for users to track their lifestyle with respect to their food and exercise habits using graphs and utility functions
View ProjectCoursera_Machine_Learning
January 11, 2021 – January 14, 2021
A collection of all answers to the assignments for Coursera course on Machine Learning by Andrew Ng
View ProjectTo-Do-PoC
April 23, 2020 – April 26, 2020
"This To Do app will help you to stay on top of your daily tasks" This project, no longer in active development, was a semester project, as a proof of concept of connecting a python server backend to a web based frontend without any web framework
View ProjectCultural Fit Analysis
The candidate's projects demonstrate a strong interest in diverse applications of AI and data science, from computer vision to natural language processing and traditional machine learning. This breadth suggests adaptability and a willingness to explore different domains, which can be a positive cultural fit for dynamic environments. However, the projects are all personal, and there is no information on team collaboration or contributions to open-source, which limits the assessment of cultural fit in a collaborative professional setting. The candidate's experience level is listed as 0, with a future start date for a Software Engineer role, which might indicate a recent graduate or someone transitioning, potentially requiring mentorship and integration into a team culture.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions indicate an ability to work on diverse technical challenges, but there is no information regarding collaboration, problem-solving approach, or communication style.