Research & Contributions
A custom framework similar to PyTorch/TensorFlow for recommender systems. Provides modules to build scalable recommendation systems with DNG scoring. CoreRec has over 22,000 installations.
Working with Farzad Abdolhosseini on Intra Language Interfaces. Successfully merged contributions to Apple's AXLearn, optimizing model architecture and testing.
Worked at NVIDIA in the TEGRA Team preprocessing data to train DriveNet for autonomous vehicle driving. Developed high-performance AI applications and hardware acceleration solutions.
Technical Expertise
Specializing in machine learning and deep learning with expertise in transformer architectures, RNNs, CNNs, and language models. Proficient in NLP, Edge AI, and model optimization.
Created SLYRIC (Sign Language Yielding Realtime Intelligent Classifier) as an independent project for real-time sign language classification, optimized for edge devices.
Currently developing BHASA LLM using MAMBA architecture. Research focuses on evolving state space models, Bayesian approaches, and efficient AI architectures with sustainable applications.