Available now · full-time DS / AI roles

Fernado George · Data Scientist & AI Engineer

Models that leave the notebook.

I'm a data scientist and AI engineer in Malaysian Borneo. I build retrieval assistants, computer-vision pipelines and the interfaces that put them in people's hands, then measure whether they hold up outside the lab.

See selected work Resume

multimodal_fusion.infer()

true label sad

P(predicted)

Row-normalised confusion matrix from the thesis. Pick a label to compare.

Thesis F1 (multimodal): 71.6%
CGPA · Dean's List: 3.75
Client systems in production: 2
Featured hackathon builds · 1 Gold, 1 runner-up: 4

Python
Java
C++
R
SQL
SQLAlchemy
JavaScript
HTML/CSS
Deep Learning
NLP
LLMs (OpenAI, Gemini, Ollama)
RAG (FAISS, BM25)
Computer Vision
LightGBM & Forecasting
PyTorch
TensorFlow
FastAPI
React (Vite)
Node.js
Tailwind CSS
Gradio & Streamlit
LangGraph & CrewAI
MLflow
Docker & Kubernetes
PostgreSQL, MySQL & MongoDB
AWS (ECS, ECR, S3)
Git & CI/CD
Python
Java
C++
R
SQL
SQLAlchemy
JavaScript
HTML/CSS
Deep Learning
NLP
LLMs (OpenAI, Gemini, Ollama)
RAG (FAISS, BM25)
Computer Vision
LightGBM & Forecasting
PyTorch
TensorFlow
FastAPI
React (Vite)
Node.js
Tailwind CSS
Gradio & Streamlit
LangGraph & CrewAI
MLflow
Docker & Kubernetes
PostgreSQL, MySQL & MongoDB
AWS (ECS, ECR, S3)
Git & CI/CD

01/Selected work

Things I've built and shipped

8 builds across retrieval, computer vision, forecasting and social-impact products, including two client systems running in production.

AI & HealthcareFeatured
Gold Medal · Festival Idea Sabah 2025
Team Leader of Development
Built an AI medical scribe with Google Speech-to-Text and Gemini Pro 2.5, using all-MiniLM-L6-v2 embeddings in a RAG pipeline that grounds generated notes in retrieved context.
- Google Speech-to-Text
- Gemini Pro 2.5
- RAG
- GCP
Client project: screenshots and repository are private.
Retrieval & LLM Systems
Client work, in production
AI/ML Development Intern · Breakfast Byte
Gradio-based AI assistant for a German client, running local Ollama models alongside OpenAI workflows. Hybrid BM25 + FAISS retrieval over a multi-format document pipeline (PDF, DOCX, spreadsheets) with streaming responses, so staff query internal documents in natural language instead of searching folders.
- Python
- Gradio
- +4
Client project: footage and repository are private.
Computer Vision
Client work, in production
AI/ML Development Intern · Breakfast Byte
End-to-end vision pipeline converting a Sarawak car-wash operator's daily CCTV footage into structured service records: vehicle-session detection, multi-bay assignment, license-plate OCR, and wash-action classification, surfaced through a local operator dashboard.
- Python
- OpenCV
- +3
NLP & Social Impact
2nd Prize · JomHack Varsity Challenge 2025
Lead Developer
AI-powered matchmaking engine connecting under-resourced schools with NGOs. A Telegram-first intake flow turns a plain-language description of need into a structured request, then ranks verified donors against it. There's no web portal for schools to learn.
- AI Chatbot
- +3
Full-Stack Web App
Event complete · 60+ participants · 100% uptime
Full-Stack Developer
Handled real-time registration for 60+ international participants with 100% uptime across the event weekend.
- React (Vite)
- Node.js
- +2
AI & Marine Tech
Top 8 Finalist · MarineHack 2025
AI/ML Engineer
Predictive maintenance system that flags a hull's biofouling growth before drag builds, so cleaning gets scheduled ahead of the fuel-cost spike instead of after it. The growth model is paired with A* route optimization. On simulated voyage data the combined model projected up to 30% fuel savings (a simulation result, not a sea trial).
- FastAPI (Python)
- +3
Social Impact & AI
Borneo Hackathon 2025
Team Leader & Backend Developer
'Zero-tech' AI coaching app for rural micro-entrepreneurs: a localized 'Cikgu' chatbot speaking Bahasa Pasar, photo-to-copywriting generation, and daily missions like 'log today's sales in one voice note'. It's built for owners whose only device is a shared phone.
- React Native
- +3
Data Engineering & MLOps
End-to-end telemetry platform · Docker & Kubernetes
Solo Developer
Renewable-energy telemetry platform ingesting live Open-Meteo data into a PostgreSQL star-schema warehouse with a DuckDB OLAP layer and n8n orchestration. LightGBM inflow forecasting and Isolation Forest anomaly detection (MLflow-tracked) are served via FastAPI, with a LangGraph self-correcting SQL agent, a CrewAI strategic panel, and a Streamlit SCADA command center. Everything is containerized with Docker Compose and deployable to Kubernetes.
- Python
- PostgreSQL
- +9

Open any project for the full write-up · ← → to browse

02/Final Year Thesis

Does emotion recognition survive the real world?

Addressed the gap between lab performance and real-world application in Emotion Recognition. This study benchmarked Contextual vs. Statistical fusion strategies against noise and missing data, concluding that Ensemble methods offer the highest reliability while Contextual Bi-GRU offers the best efficiency.

Comparative Study of Hybrid Fusion for Robust Multimodal Emotion Recognition

Weighted F1, ensemble: 71.6%
Models benchmarked: 15
Modalities fused: 3
Emotion classes: 6

01
Robustness benchmark. Every model re-scored under Gaussian noise and dropped modalities, not just clean input.
02
Contextual Bi-GRU. Architecture capturing temporal emotion changes better than statistical baselines.
03
Ensemble strategy. Achieved 71.6% F1-score, maintaining stability even under noise.

Python
PyTorch
WavLM
DINOv2
ModernBERT

Live presentation Read the thesis

Fig. 01

What happens when the inputs get noisy

y: weighted F1 %

Weighted F1 as Gaussian noise is added to every input. Each band spans the best and worst model in a family. Values above σ = 0 are read off the thesis plots, so treat them as approximate.

03/Experience

Where the work happened

A completed six-month AI/ML internship with two client systems in production, plus two terms on my faculty's student association committee.

Mar 2026 – Aug 2026

Completed

AI/ML Development Intern

Breakfast Byte Sdn. Bhd. · Kuching, Sarawak

Six-month AI/ML internship, now completed. Two client systems in production: KI Konnekt, a hybrid BM25/FAISS retrieval assistant for a German client, and a CCTV-to-records computer-vision pipeline for a Sarawak car-wash operator, both written up in Projects. Also built HydroGrid Sarawak, an open-source renewable-energy telemetry platform: PostgreSQL star-schema warehouse with DuckDB OLAP, MLflow-tracked forecasting and anomaly detection served via FastAPI, and LangGraph/CrewAI agents deployed via Docker and Kubernetes.

Built during the internship

KI Konnekt / client RAG assistantRetrieval & LLM Systems
CCTV-to-records pipeline / car washComputer Vision
HydroGrid Sarawak / Energy & Hydrogen IntelligenceData Engineering & MLOps

Student leadership

Nov 2023 – Aug 2024
Ketua Exco Akademik dan KerjayaHead of Academic & Career Committee
Persatuan Mahasiswa Fakulti Komputeran dan Informatik (PMFKI) · Universiti Malaysia Sabah
Held the academic and career portfolio for the computing faculty's student association, running its academic programmes and industry engagement for a 10-month term.
Nov 2022 – Aug 2023
Timbalan SetiausahaDeputy Secretary
Universiti Malaysia Sabah
Deputy secretary for the association: meeting records, committee correspondence and event documentation across a 10-month term.

Education

Bachelor of Computer Science (Data Science) With Honours
Universiti Malaysia Sabah · 2022 – Present
CGPA 3.75 · Dean's List
Science Module II
Sarawak Matriculation College · 2021 – 2022
CGPA 4.00 · Best Computer Science Student Award

Toolkit

Languages8

Python
Java
C++
R
SQL
SQLAlchemy
JavaScript
HTML/CSS

AI & ML6

Deep Learning
NLP
LLMs (OpenAI, Gemini, Ollama)
RAG (FAISS, BM25)
Computer Vision
LightGBM & Forecasting

Frameworks & Tools13

PyTorch
TensorFlow
FastAPI
React (Vite)
Node.js
Tailwind CSS
Gradio & Streamlit
LangGraph & CrewAI
MLflow
Docker & Kubernetes
PostgreSQL, MySQL & MongoDB
AWS (ECS, ECR, S3)
Git & CI/CD

04/About

The short version

Fernado George Anak Mani

I started out writing small game mods, which turned into a habit of taking systems apart to see how they decide things. That is still what I do, now with retrieval systems and computer vision.

My thesis benchmarked multimodal emotion models under noise and missing inputs, reaching 71.6% F1. My internship work turned a client's document archive into a queryable assistant and their CCTV feed into structured service records. I build the model and the interface that puts it in someone's hands.

Off-hours, I fish.

Based in: Malaysian Borneo
Focus: Retrieval systems · Computer vision
Studying: Bachelor of Computer Science (Data Science) With Honours, Universiti Malaysia Sabah
Grades: CGPA 3.75 · Dean's List

Hackathons

Four hackathons (MarineHack, JomHack, Festival Idea Sabah and Borneo Hackathon) with one Gold, one second place and one top-8 finish (MarineHack), plus a second top-8 at the ELLM Startup Initiative. Roles ranged from leading the team and owning the backend to solo full-stack delivery.