Software Engineer (Robotics / ML)

• Developed, tested, and integrated robotics middleware in healthcare, automating equipment delivery across 3 workflows in 2 hospitals to enhance efficiency and reduce manual labor reliance.
• Built TypeScript-based frontend features to enhance UI/UX per client specifications.
• Streamlined key workflows by automating Docker builds, code deployment, and log collection with Bash scripts, minimizing manual effort.

Research Engineer in SIA-NUS Digital Aviation Corporate Lab, Seat Team

• Research Goal: Develop an AI model to predict passenger sitting discomfort caused by prolonged sitting in long-haul Business Class flights using multi-modal sensors and aim to alleviate it using an AI-powered smart seating solution.
• Implemented ML algorithms to analyse time-series seat pressure data, studying human shifting patterns over short intervals indicative of discomfort
• Key Contributions: Developed General Comfort Rating Data Collection System to allow passengers to provide discomfort ratings to specific body regions.

Research Student (NLP/ML)

• Research goal: Enable AI agents to understand high-level natural language instructions and achieve high completion success rate in a suite of simulated scenarios.
• Research and incorporate state-of-the-art NLP techniques enabling AI agents to comprehend high level natural language instructions by optimizing LLMs with over 700+ million parameters.
• Improved agent decision-making by refining LLM-generated outputs with advanced AI techniques like POMDPs for optimized selection of action sequences.
• Achieved top 13th placing on global ALFRED leaderboard outperforming state-of-the-art baseline models.

Robotics Engineer Internship

• Developed and implemented computer vision and pattern recognition algorithms to enhance automation products, demonstrating their capabilities for marketing and client efficiency solutions.
• Engaged in meetings with existing and prospective clients to discuss future collaborations.

Chao Zhou Lim, advised by Dr. Kim Jung-Jae and Dr. Goh Shen Tat
Top 13 Placing ALFRED Challenge (2024)
[Code] [Dataset]

Skills: NLP • LLM • RL • CNN • Transformers • Tensorflow • Generative AI • AI Planning and Decision Making • Robotics • Python • Linux • Shell Script

An in-house Android Data Collection System developed by me for the Cabin Seat Comfort Project, under SIA-NUS Digital Aviation Corporate Laboratory.

• Allows researchers to collect study participants' discomfort ratings of specific body regions and monitor collected data in real-time.
• Developed using Java, XML, Google Apps API, Google Apps Script and Firebase Cloud Messaging.

Skills: App development • Java • XML • Google Apps Script • Google Apps API • Android • Postman • Firebase Cloud Messaging (FCM)

Utilize in-context learning (ICL) and prefix tuning to train large language models to identify grammatical error patterns and tendencies in english sentences/essays written by the same author.
Project featured on NUS 24th School of Computing Term Project Showcase (STePS).
[Code][Dataset]

Skills: NLP • LLM • Transformers • Tensorflow • Python • Hugging Face • In-context Learning • Prefix Tuning • Generative AI

Utilize machine learning algorithms and neural networks to detect and segment brain tumors from MRI images.
Best Project grade for the module.
[Code]

Skills: Python • OpenCV • Tensorflow • Neural Networks • Feature Engineering • Data Augmentation • Segmentation Algorithms

Fine-tuned an LSTM model using self-curated dataset and trained weights to translate customized hand gestures to readable text, in real-time.
A project for a module taken in NUS.
[Code]

Skills: LSTM • Computer Vision • OpenCV • Mediapipe • Python • Tensorflow

Designed a PCB defects tracking system to track 3 types of defects within printed circuit boards, using multi-modal sensors, computer vision and motion control for resolution ehancements.
A project for a module taken in NUS.
[Code]

Skills: CAD • 3D Modelling • SolidWorks • Computer Vision • Python • Circuits • Motion Control • Microcontroller

• Directed small projects during my internship at AMA, for the company's marketing efforts.
• Train a collaborative robot to navigate and pick up objects based on pattern recognition and visual cues.
• Use a Raspberry Pi to remotely control an industrial robot to perform an accuracy test using time-of-flight (ToF) sensors and internet of things.
• Projects featured on client's LinkedIn, company's website and my LinkedIn.

Skills: Robotics • Computer Vision • Python • ROS • Microcontroller • Sensors • IoT

Fine-tuned a Zumo robot to track and follow lines using feedback control system and a PID controller.
A project for a module taken in NUS.
[Code]

Skills: Robotics • Computer Vision • C++ • Microcontroller • PID