Open to Opportunities · 2026

Rajneesh
Babu

M.Tech CDS @ IISc Bengaluru

M.Tech student at IISc Bengaluru in Computational & Data Sciences. Building production-grade systems at the intersection of Edge AI, LLM Systems, and Computer Vision.

Rajneesh Babu
Rajneesh Babu
IISc Bengaluru · M.Tech CDS
About Me

Who I Am

A researcher and builder with a bias for production-ready AI systems.

I'm Rajneesh Babu, an M.Tech student in Computational and Data Sciences at the Indian Institute of Science (IISc), Bengaluru — one of India's premier research institutions.

My work spans Edge AI deployments on Raspberry Pi 5 with Hailo-8 NPU, production LLM systems with RLHF and multi-layer RAG pipelines, Speech AI for emotion recognition, and Computer Vision for real-time inference.

I bring a unique perspective from my background in Biotechnology (NIT Jalandhar) — combining rigorous scientific thinking with modern ML engineering to build systems that work in the real world, not just in notebooks.

Edge AI · Raspberry Pi 5 + Hailo-8 NPU
LLM Systems · RLHF · Multilingual RAG (50+ langs)
Computer Vision · Real-time Inference
Speech AI · Emotion Recognition
🎓
M.Tech — Computational & Data Sciences
Indian Institute of Science (IISc), Bengaluru
2024 – 2027 (Expected)
🔬
B.Tech — Biotechnology
NIT Jalandhar
2020 – 2024
📧
Contact
rajneeshb9458@gmail.com
IISc Bengaluru, Karnataka
What I Know

Skills

Programming, ML/DL, Computer Vision, NLP, Edge AI, Optimization Theory, and Mathematical Foundations.

💻
Programming & Tools
Python NumPy Pandas Scikit-learn Git Jupyter Streamlit DSA
🤖
ML Algorithms
Linear Regression Logistic Regression SVM Random Forest XGBoost LightGBM Ensemble Learning PCA t-SNE SMOTE Cross-Validation TF-IDF
🧠
Deep Learning
CNN RNN LSTM Transformers ResNet-50 MobileNetV2 Transfer Learning PyTorch Keras
👁️
Computer Vision
OpenCV YOLOv8 U-Net Semantic Segmentation Object Detection
💬
NLP & LLM Systems
NLP Multilingual RAG RLHF LangChain FAISS Vector Embeddings
Edge AI
Pruning Quantization Knowledge Distillation Federated Learning
📉
Optimization Theory
Gradient Descent SGD Momentum AdaGrad
📊
Data Science & Visualization
Matplotlib Plotly Seaborn Scipy Time Series Statistical Testing
📐
Mathematics & Foundations
Linear Algebra Probability & Statistics Numerical Methods PDEs — Finite Difference Schemes Floating-Point Arithmetic Convex Optimization Statistical Testing Condition Numbers
Portfolio

Featured Projects

From Edge AI hardware to gradient optimization theory — 13 projects arranged Advanced → Intermediate → Beginner.

01
🤖 Edge AI Semantic Mapping — RPi5 + Hailo-8
Real-time 2D semantic mapping on Raspberry Pi 5 with Hailo-8 NPU for assistive navigation. On-device inference at full speed with zero cloud dependency.
Edge AIHailo-8RPi5ROS2ONNX
02
🐧 Penguin AI — Multilingual RAG + RLHF Chatbot
Production LLM chatbot with 6-layer multilingual RAG pipeline (50+ languages), PPO-style RLHF, agentic ReAct reasoning, and Whisper voice input — powered by Groq + LangChain.
Multilingual RAGRLHFLangChainFAISSGroqWhisper
03
🎙️ Speech Emotion Recognition
Classifies 7 emotions from speech using MFCC + Mel-spectrograms with a CNN-LSTM architecture. Live mic and file upload support.
Speech AICNN-LSTMMFCCLibROSAPyTorch
04
🎭 Image Classification & Segmentation
PCA from scratch → ResNet-50 multi-label classifier (20 VOC classes) → semantic segmentation with ResNet-50 + ASPP decoder (mIoU 0.79) → Wilcoxon signed-rank + Bootstrap CI statistical testing.
PyTorchResNet-50ASPPU-NetPCAWilcoxon
05
🔢 Effect of Precision on PDE Solvers
FP64 vs FP32 vs FP16 across 4 finite-difference schemes (Godunov, Lax-Friedrichs, Lax-Wendroff, MUSCL) on advection-diffusion + Burgers' equations. FP16 loses stability on high-Re grids; MUSCL + SSP-RK2 preserves TVD at FP32.
PyTorchPDEsFinite DifferenceNumerical MethodsFP16/32/64
06
📉 Gradient Optimization — From Scratch
NumPy implementations of 7 optimizers (GD, SGD, Momentum, Nesterov, AdaGrad, RMSProp, Adam). Empirically verified O(1/k²) Nesterov convergence, condition number theory, and Adam generalization gap on convex + non-convex landscapes.
NumPyOptimizationConvex AnalysisAdamNesterov
07
🎸 Multi-Modal Instrument Recommender
Recommends instruments from audio, image, and text inputs using multimodal embeddings (CLIP + audio features) and cosine similarity search.
MultimodalCLIPEmbeddingsAudio AICosine Search
08
🏃 Human Activity Recognition
Classifies 6 activities from smartphone accelerometer + gyroscope using 5 ML models (SVM 95.5%). Real-time continuous detection on mobile — LinearSVC runs fully in-browser, no server needed.
SVMRandom ForestXGBoostLightGBMScikit-learnStreamlit
09
💳 Credit Card Fraud Detection
Anomaly detection on highly imbalanced transaction data using XGBoost + SMOTE. Achieves 99%+ precision with real-time scoring.
XGBoostSMOTEAnomaly DetectionScikit-learn
10
😷 Face Mask Detector — 3-Class
Compared EfficientNetB0 TFLite FP16, MobileNetV2, and YOLOv8 for real-time 3-class mask detection (Mask On / Incorrect / No Mask). EfficientNetB0 achieved 98.33% accuracy. Pipelined with OpenCV SSD face detector and deployed on Streamlit Cloud.
EfficientNetB0YOLOv8MobileNetV2OpenCVTFLiteStreamlit
11
📈 Stock Market Prediction (LSTM)
LSTM-based forecasting with RSI, MACD, Bollinger Bands as engineered features. Live data via yfinance with interactive Plotly charts.
LSTMTime SeriesyfinancePlotlyPyTorch
12
🛒 Big Mart Sales Prediction
Stacked ensemble (XGBoost + LightGBM + Ridge) with log-target + target encoding. Lifted R² to 0.63 across 8,500 stores.
XGBoostLightGBMStackingFeature Engineering
13
🎬 Movie Recommender System
Content-based recommendation using TF-IDF + cosine similarity on 5,000 movies. Fast, interpretable, and accurate suggestions.
TF-IDFCosine SimilarityNLPPandas
Get In Touch

Let's Connect

Open to research collaborations, internships, and full-time AI/ML roles.

Whether you have a project in mind, a research idea, or just want to say hello — my inbox is always open.

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