Abdullah Choudhry
Building cutting-edge software solutions and advancing AI research through innovative applications of deep learning and machine learning techniques.
Get to know who I am
Discover my journey, skills, and what drives me in the world of technology.
Who am I?
Abdullah Choudhry is an Honors Computer Science graduate with a passion for Artificial Intelligence, Software Engineering, and human-centered innovation. He graduated from the University of the Pacific in 2025 as Valedictorian with a B.S. in Computer Science and a minor in Data Science, earning multiple academic honors for excellence in research, leadership, and scholarship.
His work spans a wide range of AI applications, including deep learning for computational biology, leveraging large language models for instructional use, and tackling real-world challenges through projects like Neural Oceans — which uses satellite imagery and deep neural networks to detect ocean plastic pollution — and Adaptive Education AI, an autonomous robot professor designed to teach students through natural interaction. He has also explored the perception deficits of image recognition models under adversarial conditions.
Abdullah has gained hands-on experience at NVIDIA working at the intersection of GPUs and deep learning, and continues to push the boundaries of intelligent systems through his ongoing research.
Beyond the code, he is fascinated by the future of AI-powered systems — especially humanoid robots and hardware-accelerated intelligence — and is always exploring new ways to bridge computation with empathy. In his free time, he enjoys watching boxing and UFC, anime, gaming, hackathons, and discovering great food.
My Professional Journey
4+
Years Coding
20+
Projects
3+
Publications
Research Interests
Deep Learning & Neural Networks
Machine Learning Algorithms
Robotics & Autonomous Systems
Natural Language Processing
Computer Vision
Technical Skills
Programming Languages
AI/ML Frameworks
Web Frameworks
Operating Systems
Tools & Technologies
Professional Experience
My academic background and professional career path in software engineering and machine learning research.
Education
University of the Pacific, Stockton, CA
Bachelor of Science in Computer Science, Minor in Data Science
- ✓GPA: 4.00
- ✓Valedictorian - Class of 2025
- ✓Summa Cum Laude
- ✓Departmental Outstanding Graduate
- ✓Departmental Academic Excellence
- ✓Dean's Honor Roll: Spring 2022 - Fall 2025
Experience
Research Assistant for Machine Learning and Cybersecurity
University of the Pacific | School of Engineering and Computer Science
Conducted research in machine learning and cybersecurity. Developed innovative algorithms and models for solving complex security problems and advancing the field.
High-Performance Computing and Deep Learning Performance Engineer Intern
NVIDIA Corporation | Performance Lab, Santa Clara, CA
Led GPU performance benchmarking across various HPC and Deep Learning frameworks, including PyTorch, TensorFlow, and CUDA. Worked on optimizing performance for AI applications and high-performance computing workloads.
Teaching Assistant for Discrete Mathematics
University of the Pacific | School of Engineering and Computer Science
Assisted professor with course materials, led review sessions, and helped students master complex mathematical concepts essential for computer science.
Recent Events & Achievements
Exploring the highlights of my academic and professional journey through events, conferences, and achievements.
Commencement | Diploma & Hooding Ceremony 2025
University of the Pacific, Stockton, CA
Celebrated the culmination of my academic journey at the University of the Pacific Commencement and Hooding Ceremony. It was a momentous occasion marking the official conferral of my degree and the transition from student to graduate.
SOECS Graduation Awards 2025
University of the Pacific, School of Engineering and Computer Science
I was honored as Valedictorian, Departmental Outstanding Graduate, and Departmental Academic Excellence at the SOECS Graduation Awards 2025.
Machine Learning with GPUs Research Poster
Computer Science Department
Presented a comprehensive research poster on Machine Learning optimizations with GPUs, demonstrating performance improvements and implementation techniques for various ML algorithms.
Won Pacific Summer Undergraduate Research Fellowship (SURF)
University of the Pacific
Excited to announce that I've been awarded the Pacific Summer Undergraduate Research Fellowship (SURF) for 2025! This prestigious fellowship will support my research project over the summer, allowing me to dive deeper into innovative computing solutions and work closely with faculty mentors.
Pacific Research and Creativity Showcase 2025
University of the Pacific, Stockton, CA
I presented my research on 'Deep Learning for Genomic Feature Prediction Using Semantic k-mer Embeddings and a CNN-LSTM Architecture.' My work focused on predicting functional DNA elements (like exons and coding regions) directly from genomic sequences using deep learning. I developed a model that combines semantic k-mer embeddings (using Word2Vec) with a hybrid CNN-LSTM architecture to capture both local sequence motifs and long-range dependencies. The approach outperformed traditional methods, especially in recall and precision for exon/CDS detection, and demonstrated the power of AI in uncovering complex biological patterns. The research also explored cross-species generalization and the potential for integrating transformer models for even richer genomic context.
Inducted into the Phi Kappa Phi Honor Society
University of the Pacific
I'm honored to have been inducted into Phi Kappa Phi, the nation's oldest and most selective multidisciplinary collegiate honor society. Membership is by invitation only to the top 10% of seniors and graduate students and 7.5% of juniors.
SF Hacks 2025
San Francisco, CA
Our project, EchoLens, translates real-world audio—both spoken and environmental—into accessible visual information for Deaf and Hard-of-Hearing users. EchoLens performs real-time speech-to-text transcription with emotional tone detection, classifies environmental sounds (like alarms or footsteps), and displays directional cues to inform users where sounds originate. We integrated Whisper API for transcription, Gemini AI for emotional tone, YAMNet for sound classification, and PyRoomAcoustics for spatial mapping. The frontend, built with React.js and Material UI, features a dynamic transcription panel, live waveform rendering, and an interactive sound map. The backend uses Flask, TensorFlow, and MongoDB for real-time audio processing and AI memory. This hackathon taught us the power of multimodal, accessible design and how inclusive technology can empower communities.
2nd Place at HackHayward 2025
Hayward, CA
I am thrilled to announce that my teammate and I secured 2nd Place at HackHayward 2025 in the Sustainability with Artificial Intelligence track! Our project, Carbon-Aware AI Job Scheduler, is an intelligent task scheduling system designed to optimize computing workloads and minimize carbon emissions. By integrating real-time carbon intensity data and leveraging multiple AI services, it provides smart scheduling recommendations and detailed environmental impact analyses for resource-intensive computing tasks.
Inducted into Pacific Node of the Pledge of the Computing Professional
University of the Pacific
Proud to have been inducted into the Pacific Node of the Pledge of the Computing Professional, an organization dedicated to promoting and recognizing the ethical and moral behavior of computing professionals.
Immerse The Bay Stanford XR Hackathon
Stanford University, CA
I had the incredible opportunity to attend the prestigious Immerse the Bay Stanford XR Hackathon hosted by Stanford University! It was my first time diving into Mixed Reality development, where I had the opportunity to learn Unity, work with the Meta Quest 3, and explore the intricacies of C# and Blender. In barely 36 hours, we embraced the challenge of building an MR game, working tirelessly to debug code, fine-tune interactions, set up hardware, and model in Blender—all while mastering a new and exciting tech stack. The experience pushed our skills to new heights, and bringing our vision to life was incredibly rewarding.
CalHacks 11.0 - My First Hackathon
UC Berkeley, CA
Our Project: Halo. We built Halo, an AI-powered virtual companion designed to offer personalized emotional support and track users' emotional history, with the goal of assisting people facing mental health challenges and integrating into smart home environments. Halo uses Hume AI for real-time emotion detection, enabling empathetic conversations with a large language model. Google Gemini generates insights and summaries to help users understand their emotional patterns. We also used TensorFlow for computer vision to automate motion-triggered interactions, added data visualizations for emotional history, and integrated the Spotify API for music recommendations. The UI was developed with React, Next.js, and TypeScript, using MongoDB for data management and deployed via Vercel.
NVIDIA Internship
NVIDIA Headquarters
I'm thrilled to share some highlights from my incredible internship experience as I approach the end of the summer portion of my CO-OP! Meeting our CEO, Jensen Huang, and learning about his vision and experiences has been an unforgettable and inspiring experience. His passion for innovation and unwavering commitment to excellence have profoundly influenced me. Jensen is truly one of a kind, and I have come to deeply admire him as an ideal role model.
Inducted into the Mortar Board Honor Society
University of the Pacific
Honored to be inducted into the Mortar Board Honor Society, a national honor society recognizing college seniors for their achievements in scholarship, leadership, and service.
Pacific Research and Creativity Conference 2024
University of the Pacific, Stockton, CA
I was honored to present my RNA Sequencing research at this prestigious conference, mentored by Dr. Julia Olivieri. This project stood at the intersection of Computer Science, Computational Biology, and Statistics, focusing on identifying statistically significant equivalence in gene expression.
Send Me a Message
Have a question, want to collaborate, or just want to say hello? Fill out the form below and I'll get back to you soon!