Available for opportunities

Hi, I'm

Hameed Ijadunola

Ph.D. Candidate · Software & AI/ML Engineer

Computer Engineering Ph.D. candidate at the University of Tennessee specializing in computer vision, deep learning, and multimodal AI — with 4+ years of industry experience shipping scalable web and mobile products. I research tiny object detection, hyperspectral imaging, and vision-language models, and build full-stack applications from React/Next.js frontends to Node.js/tRPC backends and React Native mobile apps.

10+

Projects

20+

Technologies

4+ yrs

Experience

2

Publications

About Me

Researcher. Engineer. Builder.

I'm a Ph.D. candidate in Computer Engineering at the University of Tennessee, Knoxville, researching computer vision, deep learning, and multimodal AI in the AICIP Group. My work spans tiny object detection, hyperspectral imaging, and vision-language models — targeting top-tier venues like ECCV, CVPR, and ICML.

Alongside my research, I have 4+ years of industry experience as a software engineer — building and shipping cross-platform mobile apps (10k–30k active users), full-stack web platforms, and scalable APIs across companies in Nigeria and remotely. I also serve as a Graduate Teaching Assistant for Deep Learning (COSC-525) and Circuits II (ECE-201).

My goal is to build efficient, high-performance AI systems that solve real-world problems — bridging the gap between research and production engineering.

Education

University of Tennessee, Knoxville

Ph.D. in Computer Engineering

Aug 2024 – Present

Computer Vision
Deep Learning
Robot Learning

Federal University of Technology Akure

B.Eng. Computer Engineering · First Class Honors

Graduated 2021

Research Focus

  • Tiny object detection for tire defect analysis (FCOS, RetinaNet, SSD) — 10–15% mAP improvement

  • Vision-language models (CLIP, LLaVA) for representation learning and downstream image understanding

  • Temporal ML models (LSTM, Transformers) for bovine mastitis detection — 91% accuracy

  • Hyperspectral image classification with PCA, autoencoders, and MVC-NMF

Engineering Strengths

  • TypeScript-first, end-to-end type safety (tRPC + Next.js App Router)

  • Cross-platform mobile with React Native & Expo — shipped to App Store & Play Store

  • AI integration — RAG pipelines, Vercel AI SDK, Pinecone vector search

  • CI/CD automation and cloud deployments (AWS, GCP, Vercel, DigitalOcean)

Experience

Graduate Research & Teaching Assistant

Current

University of Tennessee, Knoxville · Aug 2024 – Present

AICIP Group research + TA for Deep Learning (COSC-525) and Circuits II (ECE-201)

Hyperspectral Image Analyst Intern

EnSenSys · Jun 2025 – Aug 2025

Hyperspectral classification pipelines; 8pp accuracy gain, 25% faster feature extraction

Software Engineer

Spinel Consulting · Mar 2023 – Aug 2024

React Native apps serving 10k–30k users; CI/CD reduced release time by 75%

Software Engineer

Softwater Solutions · Apr 2022 – Mar 2023

Accelerated mobile dev cycles 50%; reduced load times 50% via performance optimization

Software Engineer

Sabi · Nov 2021 – Apr 2022

React/Next.js web interfaces; mobile-first strategy improved user retention by 20%

Publications

Under Review · ECCV 2026

A. Cozma, H. A. Ijadunola, J. Dosch, C. Murphy, H. Qi. “Architecture Follows Data: CNN Backbone Design for Tiny Object Detection.”

Published · IEEE NIGERCON 2022

F. M. Dahunsi, H. Ijadunola, A. O. Melodi, A. A. Ponnle. “Analysis of GSM, Wi-Fi and LPWAN Communication Technologies for Smart Energy Metering Circuits.”

My Work

Projects

What I Know

Skills & Technologies

Get In Touch

Contact Me

I'm currently open to fullstack and mobile internship opportunities. If you have a project in mind or want to chat about tech, feel free to reach out.