Graduate from Carnegie Mellon University’s School of Computer Science with deep technical expertise in AI and machine learning. I have strong foundation in advanced deep learning, computer vision, and natural language processing. My academic projects and graduate-level coursework have provided deep theoretical understanding as well as the practical skills necessary for complex problem-solving in these fields- At my internship at SpaceX, I applied these competencies to engineer an intelligent fleet planning system for the rockets, leveraging hybrid Deep Learning and Deep Reinforcement methods to optimize real-world operations.- Strong Communication and Presentation from interning at an AI Cloud startup- As a teaching assistant at CMU, I instructed the most popular undergraduate AI course, simplifying advanced concepts for hundreds of students and honing my abilities to communicate intricate subjects effectively.Skills:o Generative AI: adept with implementations of Llama-2 LLM (grouped query attention and RoPE embeddings), GANs, and Low Rank Adaptation for fine-tuning, multimodal foundation models, and distributed training.o Deep Learning: developed and models for Phoneme recognition, Facial Recognition, and attention-based Transcript Generation.o NLP: built question generation and answering systems with Hugging Face Transformers, part of speech labeling with Hidden Markov Models, and Machine Translation with LSTMs. o Computer Vision: skilled in 3D reconstruction using Epipolar geometry, homography estimation, CNN-based scene recognition, and advanced tracking with the Lucas-Kanade and KLT algorithm.