Vinay Singh

About Me

I am currently pursuing a Master of Science in Computer Science at Texas A&M University (GPA: 4.0/4.0), with a solid foundation in software development, machine learning, and AI. With over two years of experience at Oracle, I’ve optimized enterprise clinical-trial applications through distributed caching and UI framework enhancements, and interned at AWS as a Software Development Engineer. My technical toolkit includes Java, JavaScript, C++, SQL, Python, Docker, OCI, Kubernetes, and more.

Experience

Amazon

Software Development Engineer Intern, AWS (May 2024 - August 2024)

Oracle

Software Developer, Life Sciences Global Business Unit (August 2022 - August 2024)

Contributed to design and development of ClinicalOne, a unified clinical-trial platform, as a full-stack developer across 5+ microservices.
Devised a distributed cache system using Akka, reducing inter-service calls by 75% and boosting API performance by 300%.
Played a key role in a new Forms UI framework, improving rendering efficiency by 40% and reducing data-parse time by 20%.
Led a team to increase code coverage for three microservices to over 80%, enhancing system reliability.

Skills

Programming Languages

Java, JavaScript, C++, SQL, Python

Fundamentals

Data Structures & Algorithms, Operating Systems, OOP, DBMS, Predictive Analysis, ML, AI

Tools & Technologies

OJET, Git, Jenkins, OCI, Docker, Kubernetes

Education

Texas A&M University

Master of Science in Computer Science (August 2024 - May 2026), GPA: 4.0/4.0

Thapar Institute of Engineering and Technology

Bachelor of Engineering in Computer Engineering (July 2018 - June 2022), CGPA: 9.67/10

Research

Trajectory Prediction in Autonomous Driving

“Trajectory Prediction in Autonomous Driving with Vision-based Deep Neural Networks”, IEEE SITIS 2023.

View Publication

Discernment of Cyclists in Aerial Images

Presented at ICBDAIA 2023.

Projects

ScoutNFT

Engineered a CLIP-based NFT recommendation system on 100K+ image-text pairs, fine-tuned for content-based search.
Employed Fast MMR for diversified top-k retrieval, cutting redundancy by 40% and enabling sub-50ms cosine-similarity lookups.

Benchmarking NeRF on Sparse View Reconstruction

Benchmarked PixelNeRF, SparseNeRF, ZeroRF, and TrackNeRF on DTU and synthetic NeRF datasets with 1/3-view sparsity.
Proposed a novel hybrid architecture combining strengths of multiple models to improve PSNR by 2 dB on average.

Smart Surveillance System

Developed real-time door lock/unlock and anomaly-detection pipeline using HAAR Cascade, DCNN, and 3D-CNNs, achieving 98% facial-recognition accuracy and 40% higher threat-detection rates.
Optimized inference latency under 200ms for edge deployment.

PHLYO

Implemented AI-powered passenger facilitation system with collaborative filtering using Flutter and Firebase.
Analyzed baggage-prediction data, improving airline resource utilization by 30% during Smart India Hackathon 2020.

Hi, I'm Vinay Singh