Shaiv Patel
AI Engineer · ML Researcher · Software Engineer
Building intelligent systems at the intersection of AI and scalable software.
Engineer, Researcher, Builder
Driven by curiosity and a passion for building systems that learn.
I am an AI/ML Engineer and Computer Engineering graduate student at Johns Hopkins University, where I work at the intersection of artificial intelligence, machine learning, and scalable software systems.
My research and engineering focus spans computer vision, natural language processing, and deep learning — with a commitment to building production-grade systems that translate research innovations into real-world impact. I bring a strong foundation in systems design, algorithm development, and software engineering best practices.
I thrive in environments where I can push the boundaries of what's possible with intelligent systems, collaborating with teams that value rigor, creativity, and purposeful engineering.
Education
Johns Hopkins University
M.S. Computer Engineering
Focus Areas
Where I’ve Worked
A track record of research, engineering, and impact across AI and software.
Computer Vision Research Intern
Johns Hopkins University
- ›Developing novel deep learning architectures for medical image analysis and 3D reconstruction
- ›Implementing state-of-the-art computer vision pipelines for real-time object detection and segmentation
- ›Contributing to research publications in top-tier AI conferences
AI/ML Engineer Intern
SimpleTicket
- ›Designed and deployed NLP models for automated customer support ticket classification and routing
- ›Built scalable ML inference pipelines serving thousands of predictions per minute
- ›Reduced average ticket resolution time by optimizing AI-driven response generation
Software Engineer Intern
Safarii Infosoft
- ›Developed full-stack web applications using modern frameworks and cloud services
- ›Implemented RESTful APIs and microservices architecture for enterprise clients
- ›Collaborated with cross-functional teams following agile development practices
Selected Work
Research and engineering projects that push the boundaries of AI and software systems.
A biometric authentication system leveraging keystroke dynamics and AI-generated prompt analysis. Uses deep learning models to create unique behavioral fingerprints from typing patterns, achieving high-accuracy user verification without traditional passwords.
An AI-driven clinical decision support system for early bipolar disorder detection using multimodal data analysis. Combines NLP-based sentiment analysis of patient records with physiological signal processing to improve diagnostic accuracy.
Technical Toolkit
Technologies and frameworks I work with to build intelligent, scalable systems.
Languages
AI / ML
Systems & Tools
Research Notes
Thoughts, explorations, and notes from my work in AI and machine learning.
Exploring Transformer Architectures for Medical Imaging
A deep dive into how Vision Transformers (ViTs) are reshaping medical image analysis. I explored attention mechanisms tailored for 3D volumetric data, comparing performance against traditional CNN-based approaches on segmentation benchmarks.
Real-Time Object Detection on Edge Devices
Notes on optimizing YOLO-based detection pipelines for deployment on resource-constrained edge hardware. Covers model pruning, INT8 quantization via ONNX Runtime, and achieving sub-20ms inference latency on Jetson Nano.
Fine-Tuning LLMs for Domain-Specific NLP Tasks
Research notes on parameter-efficient fine-tuning (LoRA, QLoRA) of large language models for specialized NLP tasks including clinical text summarization and technical document classification.
Currently Exploring
Topics and technologies I’m actively diving into — always learning, always building.
Multimodal Foundation Models
Investigating architectures that unify vision, language, and audio understanding in a single model — with a focus on emerging approaches like Gemini and GPT-4V.
ML Systems & Infrastructure
Building efficient training and inference pipelines — exploring distributed training frameworks, model serving with vLLM, and GPU kernel optimization.
Agentic AI Systems
Designing autonomous AI agents that can reason, plan, and execute complex multi-step tasks using tool-use and retrieval-augmented generation.
Edge AI & On-Device Inference
Deploying deep learning models on mobile and IoT devices — model compression, quantization-aware training, and real-time inference optimization.
Reinforcement Learning from Human Feedback
Exploring RLHF and DPO alignment techniques for fine-tuning language models to better follow instructions and align with human preferences.
Generative AI for Creative Tools
Experimenting with diffusion models, neural style transfer, and controllable generation for creative applications in design and content creation.
Let’s Connect
Interested in collaborating on AI research, engineering projects, or opportunities? Reach out.
I'm always open to discussing new opportunities, research collaborations, or interesting engineering challenges. Feel free to reach out through any of the channels below.
shaiv@example.com
linkedin.com/in/shaivpatel
GitHub
github.com/shaivpatel