MSc Computer Science (Artificial Intelligence)
University of Nottingham
Sept 2025 – June 2027
Open to Opportunities
Mohammed Azeez
MSc CS (AI) student at the University of Nottingham — building and evaluating ML/DL systems across healthcare, cybersecurity, and environmental domains. Research experience at the University of Tokyo and Tunghai University, Taiwan.
About Me
Who I Am
I'm Azeez — I build things with AI and I'm endlessly curious about how models learn, fail, and improve. I've chased this curiosity from Bangalore to Taichung to Tokyo (remotely), and now I'm at the University of Nottingham doing my MSc in AI.
When I'm not training models or reading papers, you'll find me doing street photography on my iPhone or working on side projects that probably won't make money but will definitely teach me something.
My research spans LLM deployment on edge hardware, deep learning for medical imaging, and NLP pipelines for cyber-threat intelligence. I'm drawn to the gap between rigorous evaluation and real-world deployment.
Languages
English (Fluent)
Urdu (Native)
Hindi (Fluent)
Kannada (Fluent)
0
International
Research Stints
Research Stints
0
Team Members
Managed
Managed
0
ML Models
Deployed
Deployed
0
Exam Candidates
Outranked
Outranked
The Story
The Journey
Five cities. Three countries. One continuous thread.
🇮🇳
Bangalore, India
2002 – 2020
Where it all started. School, first line of code, and way too much biryani.
🇮🇳
Bangalore, India
2020 – 2024
BTech in Computer Engineering at Presidency University. Built my first ML model here.
🇹🇼
Taichung, Taiwan
May – Jul 2024
IIPP Research Program at Tunghai University. Led a 13-person team. First time living abroad.
🇯🇵
Tokyo, Japan
2024 – 2025
Remote AI research with University of Tokyo. LLMs, edge deployment, and learning to work across time zones.
🇬🇧
Nottingham, UK
2025 – 2027
MSc in AI at University of Nottingham. Current chapter.
1 / 5
Education
Academic Journey
BTech Computer Engineering
Presidency University, Bangalore
Aug 2020 – Nov 2024
PCMC Science (Pre-University)
Huda National Pre-University, Bangalore
2018 – 2020
Secondary Schooling
Huda National School, Bangalore
Until 2018
Experience
Where I've Worked
Research roles spanning Japan, Taiwan, and the United Kingdom.
Research
AI Research Assistant
University of Tokyo — Remote
Aug 2024 – Aug 2025- Built model-serving prototypes using Ollama and FastAPI for edge-computing simulation.
- Benchmarked Llama 3.1 across varying RAM allocations to establish minimum resource requirements.
- Analysed API response latency and token throughput to inform model-selection recommendations.
- Delivered weekly technical reports on cloud-to-local LLM hosting feasibility.
IIPP Programme
AI Research Intern
Tunghai University, Taiwan
May 2024 – Jul 2024- Built an automated NLP pipeline using Python + GPT-4o API for CTI-report entity extraction.
- Coordinated a 13-member international research team across data collection and validation.
- Refined system prompts to improve extraction accuracy, cutting manual entry by 50%.
- Aligned the AI extraction pipeline with established cybersecurity frameworks.
Projects
Things I've Built
Research-grade systems, scrappy automations, and everything in between.
AgentForge
Multi-Agent LLM Orchestration
Built an agentic framework where multiple LLMs talk to each other, catch each other's mistakes, and iterate until the answer is actually good. Uses LangGraph for orchestration and Redis so agents remember what happened three steps ago.
MedVision
Chest X-Ray Diagnosis
Fine-tuned ResNet-50 to classify 14 thoracic diseases from NIH chest X-rays. Added Grad-CAM heatmaps so doctors can see WHY the model flagged something — not just that it did.
CTI Entity Extraction
NLP for Cyber Threat Intelligence
Automated the boring part of cybersecurity research — extracting threat indicators from CTI reports. Fine-tuned GPT-4o and Llama 3.1 to pull out IOCs, TTPs, and threat actor names with minimal hallucination.
DataScale
Fraud Detection at Scale
Processed millions of financial transactions in PySpark to catch fraud. The real challenge was class imbalance — built a custom SMOTE implementation that runs inside Spark, which boosted minority class recall by 35%.
BioSage
Clinical Decision Support API
A production-grade REST API that serves patient risk models. FastAPI handles async requests, Redis caches predictions, and the whole thing runs in Docker. Built it to be the kind of ML API I'd actually want to integrate with.
EcoSense
Environmental Anomaly Detection
Used LSTMs and Isolation Forests to spot anomalies in air quality sensor data. Hit 92% F1 on public benchmarks. The interesting part was figuring out which features actually matter for multivariate time-series.
Multiple Disease Prediction System
Published Research · National Conference
My first proper ML project — and it got published. Built a system that predicts diabetes, heart disease, and Parkinson's from patient data. Presented at a national conference and published in IRJMETS (Vol. 6, Issue 5, 2024).
LLM Edge Deployment
Research · University of Tokyo
How small can you go before a local LLM becomes useless? Benchmarked Llama 3.1 variants across 4GB–16GB RAM to find the sweet spot between cost, speed, and coherence for edge deployment.
Shift Monitor Bot
Automation · Playwright + WhatsApp
Got tired of missing shift notifications. Built a bot that monitors my email via IMAP, auto-claims available shifts on the booking platform using Playwright, and pings me on WhatsApp. Runs on my phone via Termux.
Job Alert System
Anti-Scraper Engineering · GitHub Actions
Amazon's job site blocks scrapers hard — CloudFront, hash-based SPAs, bot detection. So I intercepted their GraphQL API via AWS AppSync, track job IDs with state files, and get email alerts. Runs free on GitHub Actions every 5 minutes.
WhatsApp Chat Analyzer
Data Viz · Weekend Project
Upload a WhatsApp export and get insights — who talks the most, peak activity hours, emoji usage patterns, word clouds. A fun weekend project that taught me more about data viz than any course.
Skills
Tools of the Trade
Languages
PythonSQLJavaC++
ML / Deep Learning
PyTorchTensorFlowScikit-learnNeural Networks
LLMs & NLP
LangGraphRAGPrompt EngineeringHuggingFaceOllama
Data & Analysis
PandasNumPyMatplotlibSeaborn
Dev & Infrastructure
GitDockerFastAPIStreamlitRedis
Research
Experiment TrackingLiterature SynthesisTechnical Reporting
Recognition & Learning
Achievements & Certifications
Achievements
Top 5% in K-CET — ranked 22,000 out of 370,000+ candidates.
Selected by faculty at Tunghai University and University of Tokyo for international AI research collaborations.
Fully funded for the IIPP research programme in Taiwan.
Peer-reviewed publication in IRJMETS, Vol. 6, Issue 5, 2024.
Certifications
Data Analytics — IIT BHU Varanasi
Deep Learning Specialisation (5 courses) — Andrew Ng, Coursera
Introduction to LLMs — DeepLearning.AI
LangChain for LLM Applications — DeepLearning.AI / LangChain Academy
IIPP Research Programme — Tunghai University, Taiwan
AI Research — University of Tokyo
Get In Touch
Let's Work
Together
Open to research collaborations, ML consulting, freelance projects, and good conversations about AI. Currently pursuing MSc AI at Nottingham.
Download Resumemohammedazeez205@gmail.com
linkedin.com/in/mohammed-azeez
GitHub
github.com/mohammmed-azeez
Available for new projects
Remote research roles, consulting, part-time, and full-time opportunities welcome.