Projects

Model Architecture & Development

Advanced Image Classification

PyTorch Hugging Face TensorFlow

Implementation of state-of-the-art image classification model using Vision Transformers (ViT) with high accuracy on benchmark datasets.

Neural Architecture Search

PyTorch Ray CUDA

Automated machine learning framework for discovering optimal neural network architectures using reinforcement learning algorithms.

Real-Time Object Detection

OpenCV YOLOv8 TensorFlow

Novel transformer architecture for real-time object detection with optimized inference pipeline for autonomous driving applications.

LLM Fine-tuning Optimization

PyTorch Transformers PEFT

Efficient fine-tuning techniques for large language models using parameter-efficient methods like LoRA and QLoRA with minimal computational resources.

CUDA Optimization

CUDA C++ Triton

Custom CUDA kernels and optimization techniques for deep learning operations with significant performance improvements for training speed.

Transformer Inference Engine

TensorRT CUDA C++

High-performance inference engine optimized for transformer models in production with kernel fusion and dynamic batching.

Distributed Training Framework

PyTorch DeepSpeed Horovod

Scalable training framework with data and model parallelism support for efficiently training large models.

Optimized Stable Diffusion Pipeline

PyTorch diffusers xFormers CUDA

High-performance Stable Diffusion implementation with custom attention mechanisms and memory optimizations for efficient training and inference.

MLOps Platform

Kubernetes MLflow Kubeflow

Production-grade MLOps infrastructure with automated training and deployment pipelines for the complete machine learning lifecycle.

Mobile-First ML Pipeline

TFLite CoreML ONNX Metal

Efficient deployment of ML models on mobile devices with hardware-specific optimizations and battery-aware inference strategies.

Video Understanding Pipeline

TorchScript TensorRT OpenCV

High-performance video processing system with real-time object tracking and action recognition optimized for edge devices.

Deep RL for Robotic Manipulation

PyTorch Isaac Gym RLlib CUDA

State-of-the-art reinforcement learning implementation for robotic manipulation tasks with GPU-accelerated physics simulation.

Multimodal Robot Learning

PyTorch ROS2 SAM LLMs Isaac Gym

Advanced robotic system integrating vision-language models with RL for complex manipulation tasks with natural language control.