LLM Finetuning and Compression (2024-present)
This project involves integrating powerful model compression techniques into fine-tuning workflows, empowering AI developers and researchers to optimize and deploy large models with efficiency and scale. Founding member of the team.
My Responsibilities: Develop a custom pipeline for fine-tuning and compressing open-source LLM models together, evaluating their performance on domain-specific tasks; research and evaluation of SOTA LLM Compression techniques.
Model Compression (2024)
This project involved the quantization of computer vision models for face detection, recognition, and swapping to enable real-time performance on edge devices like the Jetson AGX Orin.
My Responsibilities: Set up and deploy face detection, recognition, and swapping models on Jetson AGX Orin; perform int8 model quantization using PyTorch Quantization and NVIDIA TensorRT for optimized and real-time performance.
LLM Tools (2023-2024)
The project involved the development of a suite of multifaceted tools integrating Large Language Models (LLMs) for enhanced software project management, coding, documentation, meeting and video analysis, automation, QA, HR, and administrative tasks.
My Responsibilities: Development of a chatbot with a workspace containing user stories, transcriptions, and database analysis using Retrieval-Augmented Generation (RAG); integration of bulk Curriculum Vitae (CV) analysis.
Virtual Tours (2022-2024)
The project was about the generation of planar simplified 3D mesh for virtual tours of multi-room indoor scenes captured with iPad Pro Lidar, followed by texture projection using MVS texturing.
My Responsibilities: Geometrical analysis, formulation, and implementation of algorithms for planar simplification and texturing; implementation of ICP registration and TSDF volumetric integration for combining multiple 3D meshes; application of hole filling, mesh simplification, and texturing enhancement for 3D meshes.
Landmark Detection (2021)
The goal of the project was to develop a custom object detection model that detects faulty knot-bolt arrangements on large construction sites.
My Responsibilities: Labeling data for training deep Convolutional Neural Networks and YOLO models; fine-tuning pre-trained YOLO models based on new data and requirements.
Facial Check-In System (2021)
This project involved the development of a system that would handle daily employee check-in/check-out through face detection.
My Responsibilities: Fine-tuning FaceNet models with an improved loss function; developing a pipeline for matching facial embeddings with the existing database using Naive Bayes Algorithm.