Pre-final year CS (Data Science) student @ SRMIST | R&D Member @ ACM SIGAPP | Data Science & Web Dev enthusiast
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mcDJ
May 1, 2026 – Present
mcDJ is an AI-powered music mixing and DJ assistant that automatically analyzes songs and generates smooth transitions between tracks for seamless playback. It helps users create professional-style mixes by detecting tempo, beats, and timing, making music blending easier without advanced DJ skills 🎧🤖🎶
View ProjectMinor-project
April 27, 2026 – Present
Minor-project is a machine learning–based predictive analytics system that identifies students at risk of dropping out using academic performance and engagement patterns. It applies Logistic Regression, Random Forest, and XGBoost to generate risk scores with SHAP explainability and Streamlit visualization 📊🤖🎓
View ProjectADvision
April 17, 2026 – Present
ADVision is an AI-powered video marketing system that generates Instagram Reel ads from a product URL. It extracts product details, creates marketing scripts (hook–highlight–CTA), generates visuals and voiceovers, and assembles a ready-to-use promotional video using FastAPI and Next.js 🎬🤖🚀
View ProjectQuantum-CoughFreq-
March 31, 2026 – Present
Quantum CoughFreq is a Quantum Machine Learning–based healthcare system that detects Tuberculosis risk using cough sound analysis. It extracts acoustic features like MFCC and spectral patterns and applies hybrid quantum–classical models with a Variational Quantum Classifier for fast, non-invasive screening ⚛️🎧🧬
View ProjectAI-driven-CROSS-LAYER-FAULT-LOCALISATION-SYSTEM
March 18, 2026 – Present
Tanfinet Fault Detector is a modular, AI-driven monitoring ecosystem designed to automate and accelerate fault localization across multi-layer telecom networks. Utilizing a Temporal Fusion Transformer (TFT) backend, the system converts real-time telemetry into seconds-long, actionable diagnostics, reducing manual intervention from hours to seconds.
View Projectwind-prediction-for-power-generation
September 9, 2025 – September 10, 2025
wind-prediction-for-power-generation — GitHub repository
View Projectwind-prediction-for-power-generation-
September 1, 2025 – September 1, 2025
wind-prediction-for-power-generation- — GitHub repository
View ProjectCultural Fit Analysis
The candidate exhibits a strong passion for AI and Machine Learning, aligning well with an innovative and technology-driven culture. The diversity of personal projects, ranging from music AI to healthcare and telecom fault detection, shows a broad interest and willingness to explore different domains. This indicates a curious and adaptable individual who could thrive in a dynamic environment. However, the lack of team-based projects or formal experience makes it challenging to fully assess collaboration and cultural integration.
Soft Skills & Operational Fit
The candidate's project descriptions suggest a proactive and innovative mindset, tackling complex problems like AI-powered music mixing, student dropout prediction, and quantum healthcare diagnostics. The focus on personal projects indicates self-motivation and a drive to learn and apply new technologies. However, without formal work experience or psychometric test results, it's difficult to assess collaboration, stress handling, or direct operational fit.