I've started my publication, Intuitive Deep Learning, where we explain deep learning concepts in an intuitive way. Please clap / share / follow to support my publication!
People say that Artificial Intelligence and Machine Learning is going to take over the world. Before that happens, I want to take over AI and ML. I’m a researcher under Andrew Ng’s Stanford Machine Learning Group, and my past and current involvements in AI include Natural Language Processing on Grammar Correction, Computer Vision for Medical Imaging (X-Rays), sentiment analysis on speech data for customer-service calls, and algorithmic improvements on graph algorithms applied to predicting genres for items sold on Amazon.
Language is always evolving and is fluid; a general rules-based approach for correcting grammar simply cannot capture the richness embedded in language.
I got involved in Crio through Andrew Ng’s Stanford Machine Learning Group, and I work as a full-stack Machine Learning developer.
I've started my publication on Intuitive Deep Learning with one simple mission: to explain deep learning concepts in a simple and intuitive way!
There is much work on sentiment analysis in text, but not as much work on sentiment analysis in audio. Part of the reason behind that is the lack of a public dataset; however, many companies have recorded customer-service calls and these customers then give feedback on how the call went. This provides a rich dataset for how satisfied customers were during the entire call.
I am a paid Research Assistant under Andrew Ng’s Stanford Machine Learning Group and I work with a large bank as a Machine Learning consultant for this project. My involvements largely surround the Machine Learning architectures to predict Net Promoter Score (NPS) from the calls.
I work with BJ Fogg on the cutting-edge of Behavior Design, a set of models and methods by BJ Fogg that describes how behavior works and how one can design for a specific behavior. I consult (informally) for companies looking into using Behavior Design or Design Thinking to design for user’s specific behavior.
This was a project which combined advances in Natural Language Processing with representation learning on graphs (GraphSAGE) to predict which category an Amazon item is classified under.
This was a project done with the Stanford Medical School where we developed an algorithm to identify whether an abdominal X-ray shows any abnormalities. We additionally provided explanations for our predictions using influence functions and propose a novel domain-adaptation method for influence functions.
My team’s work was featured on the Wall Street Journal here.
I am currently a researcher under Andrew Ng's Stanford Machine Learning Group. Some of the classes I took in Stanford include "CS229: Machine Learning" by Andrew Ng in which I got an A+, and "CS231N: Convolutional Neural Networks for Visual Recognition" by Fei-Fei Li.
I also worked as an academic tutor for MS&E211:Introduction to Optimization.
I have been awarded the Adam Smith Prize for Top Overall Mark in my final year as well as the Adam Smith Dissertation Prize for the top dissertation on the topic "Modelling Bounded Rationality in the Jackson Favor-Exchange Model". I am continuing on this research and have been a member of Prof. Matthew Jackson's informal discussion group in Stanford.
I have also been active in a multitude of extra-curricular activities, such as being the co-organizer of TEDxCambridgeUniversity.
I also worked as a Teaching Assistant to create supplementary teaching materials for the course "Quantitative Methods in Economics"
I work as a full-stack Machine Learning researcher in Crio Grammar and Style Checker as well as a paid Research Assistant in the lab on the emotion-recognition for speech data project. I currently work remotely as a lead author to publish some of our results on unsupervised text style transfer.
iDoctor is a group formed from the “MS&E273: Technology Venture Formation” class at Stanford working with Dr Jeffrey Goldberg. I’ve been involved in product and business development, marketing, prototype testing and clinical trials.
I was involved in multi-disciplinary projects across various domains, such as doing a quantitative and algorithmic network-analysis and data-visualization of Singapore's industry landscape.
I was involved in the post-merger integration of a merger and market research in consumer markets in South-East Asia.
During my free time, I enjoy playing a good game of badminton.
In Singapore, I volunteer as a Club Leader at TOUCH Young Arrows, an organization committed to care for needy and disadvantaged children aged six to 12.