I’m a software engineer and researcher with hands-on experience in backend development, data science, and network security. I enjoy building scalable systems, automating data-driven processes, and exploring how machine learning and natural language processing can enhance real-world applications.
I’ve contributed to both academic research and industry projects — from automating IoT device profiling using ML to developing data management tools used by data scientists at Accenture.
University College London (UCL) — BEng Electronic & Electrical Engineering
Graduation: June 2025
- Concentration in Network Security, Data Science, and Software Engineering
- Conducted a thesis on GenAI Browser Assistant Security, developing a system to detect and visualize data leaks in LLM-based Chrome extensions based on mitmproxy
🔹 Network Security Researcher — University College London & ImperialX (2025–Present)
- Achieved 90%+ IoT device identification accuracy using ML models trained on 27 weeks of traffic data.
- Automated profiling of 40+ IoT devices using mitmproxy, k-means, and LLMs (Gemma 3) to enhance network visibility and auditing.
🔹 Software Engineering Intern — Accenture (2024)
- Built a data management app using Streamlit, FastAPI, PostgreSQL, boosting team productivity for 15+ data scientists.
- Developed an ML-powered document validation API with FastAPI, Docker, Azure ML, saving 4+ hours of manual work daily.
Languages & Frameworks: Python, JavaScript (React, Node), SQL, C, MATLAB
Backend & Cloud: FastAPI, Flask, Django, Docker, AWS, GCP, Azure
Data Science & ML: Scikit-learn, TensorFlow, PyTorch, Keras, NLP (NLTK), Data Visualization
Tools & Other: mitmproxy, tshark, Selenium, Playwright, BeautifulSoup, Git, Linux