Deep Learning Engineer.
I help companies design, build, and deploy end-to-end deep learning solutions.
I specialize in Computer Vision, Time Series, Robotics, and Electronics.
My workflow emphasizes data-centric modeling and deployment strategies.
I’m an introvert - INFJ according to the MBTI personality test. I enjoy reading self-development books on psychology, nutrition, biohacking and productivity. Among my favorites are Deep Work, Deep Nutrition, Quiet, Ultralearning, The Cancer Code, The Bulletproof Plan to Age Backward, and The 7 Habits of Highly Effective People. See all the books I’ve read here.
Other than reading I enjoy tinkering with electronics and coding in my free time. I’ve made Raspberry Pi-based electronic locks, Telegram bots to monitor crowd attendance, an Android app to broadcast live stream videos, and fixed old electronic board problems on televisions, ceiling fans, etc. I’m known as the “DIY tech guy” among my friends.
I’m an academic with a proven track record. I’ve published in reputable journals including Nature, Elsevier, and IEEE Transactions. See my publication list here. I’ve also helped companies design end-to-end deep learning solutions and deploy them into production.
⚠️ I’m seeking remote employment opportunities as a Data Scientist or Machine Learning Engineer. If you know of any openings, I’d be forever grateful if you can connect me.
Or, if you wish to support me in creating more contents on machine learning deployment tips and tricks, consider buying me a coffee. Your support means a lot to me 🤗
I have a unique blend of academic and industry experience.
What I bring to the table –
🟩 9+ years of modeling DL-based time series and computer vision algorithms.
🟩 3+ years of helping companies deploy DL models into production.
🟩 10+ years of academic journal and conference publication track record. Full publication list here.
🟩 Proven ability to think from first principles in designing high quality, scalable DL-based solutions.
🟩 Unique combination of technical know-how and communication to a non-technical audience through written and spoken mediums.
🟩 Multilingual – English, Mandarin, Malay, basic Korean.
🟩 Trained in Neuro-Linguistic Programming (NLP) and Emotional Freedom Technique (EFT) Tapping.
I provide end-to-end deep learning pipeline design, modeling and deployment services.
Book a 1-hour personal video call session with me to discuss general issues on your projects including problem definition, feasibility analysis, project scoping, etc.
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Exploratory Data Analysis
Data collection, exploring insights from existing dataset, discovering dataset issues such as class imbalance and biases.
Data Labeling and Cleaning
Cleaning and de-biasing data, crafting dataset, feature engineering, and data transformation.
Model selection and establishing benchmark performance. Iterate on training and evaluating model on dataset. Selecting most promising models for further development.
Run hyperparameter optimization algorithm to gain the best performance from model.
Optimize model for inferencing by quantization and conversion into portable form such as OpenVINO, ONNX, Tflite. Deploy to live environment for inferencing and monitoring. Refine model by observing model performance.
Front-end & Back-end Development
Front-end development focusing on mobile and web app using Flutter as a framework of choice. Back-end and database development with Firebase, MySQL, InfluxDB etc.
Integration & Monitoring
Integration with Microsoft Azure, Amazon AWS, Google Machine Learning, etc. Cross-compatibility development with existing company ecosystem. Monitoring data/concept drift in deployment pipeline.
Edge Deployment and Serving
Deploy trained and optimized model on CPU or GPU hardware on the edge for inference with model serving framework such as Triton or Tensorflow Serving.
Tech stack –
🟩 Python, C, Assembly, Dart, PySpark, Robot Operating System.
🟩 Docker, Jupyter, VSCode, Git.
🟩 DL framework – Tensorflow, PyTorch, Keras, Fastai.
🟩 DL experiment – Weights & Biases, Tensorboard, CometML, Optuna, Neural Network Intelligence.
🟩 DL deployment – OpenVINO, TensorRT, ONNX, TFLite, TorchScript, Hugging Face Hub, DeepSparse.
🟩 Database – Firebase, MySQL, InfluxDB, Hive.
🟩 UI – Flutter, Grafana, PyQt, Gradio.
🟩 Edge Device – Android/iOS Device, Raspberry Pi, NVIDIA Jetson, Arduino/ESP32/PIC/AVR MCU, Coral Edge TPU, Intel Neural Compute Stick.
🟩 Current GitHub Stats –
Ph.D. in Engineering
My Ph.D. work explores the effectiveness of using deep learning models to estimate state-of-charge (SOC) in the batteries of hybrid electric vehicles. The study conducts various in-depth comparative analyses of state-of-the-art deep learning methods applied to SOC estimation. The goal of the study is to develop a novel estimation algorithm that can accurately estimate the remaining charge from the drivers’ driving patterns. This work proposes the use of a self-supervised Transformer model and yields low error metrics providing a promising alternative to conventional SOC estimation models. See our published Nature paper.
Master’s Degree in Electrical Engineering
My Master’s Degree work explores the idea of recognizing the behavior of humanoid robots using a Long Short-Term Memory (LSTM), a variation of recurrent neural networks. The LSTM network is shown capable of classifying robotic maneuvers from joint angle data. See our published paper and demo video.
Bachelor of Electrical and Electronics Engineering (Honours)
I graduated first class with a cumulative GPA of
3.71/4.00. My bachelor’s thesis explores the idea of using pulse width modulation (PWM) techniques in combination with PID control algorithms to control the torque of a brushed DC motor. I fabricated a custom printed circuit board (PCB) to proof the working principle of the motor driver. See our published paper.
National Energy University, Malaysia.
Lecturer. Taught undergraduate and diploma level courses. Primary subjects taught include Microprocessor Systems, Digital Logic Design and Random Process. I was also featured once on Malaysia’s national TV showcasing my efforts on robotics education to the younger generation.
Center for Advanced Mechatronics and Robotics.
Research Engineer. Responsible to design boiler header inspection robot, algorithms for P3AT line following robot, algorithms for behavior classification with LSTM on NAO humanoid robot, develop learning modules for workshops on Arduino microcontroller.
Why hire me for your next project?
Throughout the years in academia with tight industry collaborations, I have developed a unique blend of skills and expertise in both software and hardware.