I build machine learning systems that ship, not just notebooks that run.
Software engineer and data scientist turning healthcare and agricultural data into deployed, working software, end to end, from data pipeline to interface, on every project.
Case Studies
Four projects that best represent how I work: framing a real problem, choosing an appropriate model or architecture, and shipping something a user can actually open in a browser.
Cardiovascular Risk Detection
Early identification of heart failure and cardiovascular risk is critical for preventive care, but risk-scoring tools are often locked inside clinical software that's inaccessible for screening contexts.
Built an interactive risk-assessment tool in R Shiny, structuring inputs and thresholds around published NHS clinical guidelines so output is interpretable by non-specialist users running early screening.
Diabetes Risk Detection
Diabetes risk factors are well-documented, but turning that knowledge into something a person can self-check before symptoms develop requires more than a static checklist.
Trained a classification model on standard diabetes risk indicators and shipped it as a Streamlit app, prioritizing fast, accessible early-detection screening over diagnostic precision.
Heritage of Faith and Hope
A rehabilitation center needed a public-facing site that communicates trust and clarity to people in vulnerable circumstances, a context where confusing UX or a slow page has real cost.
Designed and built the full production site in React, prioritizing accessibility, clear information hierarchy, and an emotionally warm but professional visual tone throughout.
Real-Time Emotion Detection
Affective computing applications (UX research, accessibility tools, sentiment systems) need a lightweight way to read emotional signal from facial images without specialized hardware.
Built and trained a convolutional neural network for facial emotion classification in TensorFlow, then deployed it behind a Streamlit interface for real-time, browser-based inference.
About Me
I'm a software engineer and data scientist who builds machine learning models and ships them as real, usable applications, not just notebooks. My applied work spans credit scoring, fraud detection, sentiment analysis, and cardiovascular risk prediction aligned with NHS clinical guidelines.
Alongside ML, I build full-stack web applications and dashboards with React JS, Streamlit, and Tableau. I bring a human-computer interaction and design-thinking background to that work, so the systems I build are usable and aligned with how real users actually behave, not just technically correct.
I also work as a freelance technical researcher and writer, producing case-study-based academic papers in computer science, a practice that keeps my research and technical-communication skills sharp alongside the engineering work. Two of my repositories have been preserved in GitHub's Arctic Code Vault Archive Program, and I've independently shipped more than 20 deployed applications across healthcare AI, agriculture, computer vision, and full-stack web development.
Skills & Capabilities
Grouped by what I actually do with them, not just listed as tools.
AI & Machine Learning
Data Science & Analytics
Software Engineering
HCI & Research
Proficiency Levels
All Projects
The four case studies above are my strongest work. Everything below includes additional ML, agriculture, and full-stack projects, plus front-end practice builds used to sharpen UI implementation skills.
Diagnostic support tool that classifies animal diseases from symptom inputs, for veterinary and agricultural use.
Smart agriculture recommendation engine suggesting optimal crops from soil, rainfall, and temperature data.
Conversational search application accepting natural language queries and returning contextually relevant results.
Client-facing site for an immigration consultancy serving clients navigating visa and relocation processes.
Full-stack dental practice management app with scheduling, patient records, billing, and staff management.
Course delivery app with lesson management, student enrolment, and progress tracking for online education.
Live global Covid-19 dashboard with interactive maps, time-series charts, and country-level statistics.
Real-time video conferencing app with room creation and peer-to-peer video/audio via WebRTC.
UI practice build replicating an e-commerce storefront with product browsing, cart, and authentication.
UI practice build replicating a booking platform interface with listings, search, and real-time data.
UI practice build replicating real-time messaging, room creation, and presence indicators.
UI practice build replicating a streaming interface with category browsing and trailer previews via TMDB.
UI practice build with image upload, feed display, likes, comments, and authentication.
Work Experience
Design, build, and deploy machine learning and full-stack applications independently, end to end. Also research and write academic, case-study-based computer science papers for clients, work that depends on the same rigor and clarity as the engineering side.
- Independently shipped 20+ deployed web and ML applications across healthcare, agriculture, and computer vision
- Built multiple healthcare ML tools aligned with published clinical guidelines
- Contributed two repositories to the GitHub Arctic Code Vault Archive Program
Coordinated digital learning content production, assigning tasks to subject-matter experts and tracking progress across multiple concurrent workstreams.
- Compiled and formatted draft content, ensuring consistency across contributions
- Managed task assignment and progress tracking using Google Forms
- Collaborated directly with management and project administrators to keep delivery on schedule
Hands-on experience in computer hardware maintenance, networking, and system administration across KWS headquarters.
- Assembled and maintained computer hardware, printers, and network equipment for HQ staff
- Configured network clients and managed printer networks
- Installed and configured Windows XP, 7, and 10 across desktop machines
Education
Let's Connect
Always open to discussing new opportunities, internships, graduate programs, and collaborations in software engineering, applied ML, or HCI research. If you have a relevant role or project in mind, reach out directly.
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