Singapore, Singapore
Enthusiastic and driven Chemistry graduate with a keen interest in Computer Science. With a solid foundation in these two subjects, I am eager to learn and to apply my chemical and computational skills to tackle complex interdisciplinary challenges and making meaningful contributions.
Undertaking a Computational Chemistry Final Year Research Project about Machine Learning-Based Model for Predicting the Material Properties of Amorphous Materials. The project is a collaboration between the National University of Singapore (NUS) under Professor Wong's computational laboratory and the Institute of High Performance Computing (IHPC), A*STAR.
AY22/23 Semester 2: • CS2040C: Data Structures and Algorithms (Teaching Feedback: 4.6 out of 5) AY23/24 Semester 1: • CS2040S: Data Structures and Algorithms (Teaching Feedback: 4.6 out of 5) AY24/25 Semester 1: • CS2040S: Data Structures and Algorithms (Teaching Feedback: 4.9 out of 5) Taught the theory on basic data structures and algorithms to undergraduate Computer Engineering and Computer Science students, live-coded and demonstrated many problem-solving techniques often used when tackling many algorithmic problems throughout the semester. Inspired students through close mentorship and imparted knowledge beyond academics to help students develop essential life skills and cultivating a passion for lifelong learning.
Undertook a Cheminformatics Undergraduate Research Opportunity Project in Science (UROPS) about High-Throughput screening for candidate Natural Product-like mosquito repellents. The project is a collaboration between the National University of Singapore (NUS) under Professor Wong's computational laboratory and the Institute of High Performance Computing (IHPC), A*STAR. Picked up valuable skillsets throughout the research project: o Got familiar with cheminformatics and its underlying principles. o Picked up basic machine learning techniques and skills. o Dealt with a huge AI-generated chemical dataset for prediction. (67 million entries) Carried out in-silico screening and obtained 5 target compounds that are non-toxic, easy to synthesize with promising predicted repellency.
• Recipient of the A*STAR Research Internship Award (ARIA). • Undertook a research project about Synergizing Chemical and Biotechnological Techniques for Hybrid Retrosynthesis under Dr Dillon Tay. • Evaluated multiple fingerprinting methods of molecules and many machine learning models (Feedforward Neural Network, Decision Trees, Random Forests) to assist in the Rollout of a Monte Carlo Tree Search for Computer Aided Synthesis Planning (CASP). • Tried to incorporate the trained enzymatic reaction template models with existing synthetic reaction template to produce a robust CASP model.