
CSE student trying to make AI less artificial and more intelligent
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SRM University
Data Scientist
June 21, 2026 – Present
PySR-Molecular-Potentials
February 21, 2026 – Present
PySR-Molecular-Potentials — GitHub repository
View Projectfire-density
July 24, 2025 – July 24, 2025
This project presents a robust foundation for advanced video-based fire and safety monitoring, combining state-of-the-art models and real-time analytics logic.
View ProjectDA-GNN
July 11, 2025 – July 11, 2025
This repository extends my research on crime prediction using CNN-LSTM to make it more accurate and novel. This will ensure better results and optimisation
View ProjectCalm-Connect
July 11, 2025 – July 11, 2025
Built a responsive website offering stress relief therapies and consultation features. Implemented smooth scroll navigation, animated landing effects, interactive therapy sections. Optimized website structure for faster load, used ML for therapy recommendations
View Projectlidar-vizualiser
June 24, 2025 – July 22, 2025
LiDAR Visualizer A simple and interactive Gradio app for visualizing and processing LiDAR images. Upload your LiDAR data to apply FFT and median filtering, view raw vs processed images side-by-side, and see basic statistics like mean, median, and standard deviation. Built with Python, OpenCV, and NumPy, ideal for quick analysis and demos.
View ProjectQVAO-MLLM-Optimization
June 24, 2025 – June 26, 2025
This repository archives my research on enhancing MLLMs with a Quantum-Inspired Variational Attention Optimizer (QVAO). It includes a classical baseline using LLaVA-1.5-7B and VQAv2 on Kaggle, plus a quantum outline for IBM Quantum Labs. Though incomplete due to resource limits, it offers a foundation for future work.
View ProjectCrime-Prediction-Using-CNN-LSTM
April 30, 2025 – June 24, 2025
We use deep learning models — including LSTM and CNN-LSTM architectures — to forecast daily crime counts using the publicly available Chicago Crime Dataset (2001–2023). Our work combines time-series modeling, model optimization (via grid search), ablation analysis, and fairness evaluation.
View ProjectChurn-Prediction-for-SaaS
April 5, 2025 – April 5, 2025
This project focuses on predicting customer churn for a SaaS (Software as a Service) platform using Machine Learning techniques. Customer churn refers to the scenario where a customer discontinues using a company's service.
View ProjectPassword-Strength-Analyser
April 3, 2025 – June 24, 2025
The project analyzes password strength using AI and data-driven insights based on the RockYou dataset, a real-world collection of leaked passwords. The goal is to classify passwords into three categories: Weak, Medium, and Strong, using password length and character patterns as primary criteria.
View ProjectCultural Fit Analysis
The candidate's project portfolio demonstrates a strong passion for data science and machine learning, aligning well with a research-oriented or innovative team culture. The diversity of projects, from crime prediction to molecular potentials and MLLM optimization, suggests intellectual curiosity and a drive for continuous learning. However, the lack of team-based projects or professional experience beyond a current 'Data Scientist' role at a university (with a future start date) makes it challenging to fully assess cultural fit in a corporate environment. The experience level is listed as 0, which contradicts the 'Data Scientist' role, indicating a potential mismatch or early career stage.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and self-driven individual, capable of initiating and executing complex technical projects. The variety of projects suggests adaptability and a willingness to explore different problem domains within data science. However, without specific assessment data on communication, logical reasoning, or teamwork, it is difficult to fully assess soft skills and operational fit.