Final-year student at IIT Kharagpur (Integrated Dual Degree, Chemical Engineering and micro-specialization in Artificial intelligence and Application & High performance computing, graduating April 2027). I build production ML systems and do speech/NLP research — the kind that ships with monitoring, gets measured, and defends its numbers. Research → Wav2Vec2 + WavLM-BiLSTM fusion for native language identification from L2 English speech. 0.88 val accuracy across 5 Indian languages. Competitions → Top 0.5% globally, Amazon ML Challenge 2025 (50,000+ teams). 1st place, GC OpenSoft '25 (Deloitte-sponsored). 1st place, GC Data Anytics'25 (Evva health). Math/Algorithms → Codeforces Expert (peak 1612 · _Badassium). AIR 135, Integral Cup 2026 S1 across Probability and Statistics, Linear Algebra & Integral Analysis, Optimization Techniques.

Advanced Technology Development Centre (ATDC), IIT Kharagpur  ·  May – Jul 2025
Supervisor: Prof. Shyamal Kumar Das Mandal

Benchmarked 7 deep learning architectures on the NISP dataset — from CNN and ResNet-18/50 baselines to transformer-based SSL fusion models — across 5 Indian L1 languages (Hindi, Telugu, Tamil, Kannada, Malayalam). Final model: Frozen Wav2Vec2 + WavLM encoder layers → BiLSTM head. 0.88 validation accuracy, state-of-the-art on this task. UMAP embeddings revealed tight, well-separated Telugu/Malayalam clusters and quantifiable Hindi-Tamil phonetic overlap — interpretable signal beyond the classification score.

Technology	Name
NLP / Speech AI
ML / Deep Learning
MLOps & Infrastructure
Backend / Serving
Languages
Cloud & Tools