AI | Mobile | Web | Speech | Vision | Software Developer
I am a highly self-motivated and enterprising fourth-year B.S. + M.S. student with five years of interdisciplinary research experience in AI, psychiatry, and linguistics, currently working on computer vision research.
I had always been fascinated by linguistics, even at a young age. In the eighth grade, I was a championship finalist (top 10) in the Scripps National Spelling Bee out of 11 million students worldwide, after 5 years of hard work and dedication. Later on, in high school, I began merging my interests in linguistics with artificial intelligence and psychiatry, developing and "bringing the heart" to innovative conversational technologies to improve the lives of individuals.
For around three years, I was the creator and developer of BuddyBot, a voice-based AI trainer companion to improve conversational skills and socio-communicative ability in Autistic individuals, using a reinforcement learning-based adaptive conversation engine. On the psychiatric side, I was a member of the Fung Lab (http://med.stanford.edu/funglab.html) at the Stanford Psychiatry and Behavioral Sciences Department since 2017 for human subjects research (e.g. data collection, clinical trials) to train and evaluate BuddyBot. BuddyBot had also been entered into the 4-year, $5M IBM Watson Artificial Intelligence XPRIZE, and had been fortunate to have been selected among the top 30 out of 683 teams for Round 2 of the contest (http://ai.xprize.org). Additionally, in May 2019, BuddyBot was featured at the United Nations AI For Global Good Summit in Geneva, Switzerland.
Following that, I worked at the Stanford Open Virtual Assistant Laboratory on NLP + deep learning research to improve state-of-the-art general free-text question answering systems on Wikipedia. I've also worked on various NLP projects as a software engineer intern at AIBrain and Gridspace.
Recently, I have gained an interest the field of computer vision, and I am currently working on vision research as a member of the Stanford Vision and Learning Lab. This summer, I will also be working as a Machine Learning Intern at Pinterest.
-Reinforcement Learning (q-learning, policy gradient learning)
-Machine Learning (K-means clustering, markov models, regression, classfication)
-Deep Learning (artificial, convolutional, and recurrent neural networks)
-Natural Language Processing (neural machine translation, semantic parsing, sentiment analysis, POS tagging, semantic similarity, information retrieval)
-Computer Vision (3D Vision, convolutional neural networks)
-Data Science (data scraping and collection, data structure and databases, exploratory data analysis and visualization, Bayesian statistics, regression methods, forecasting)
-Application Development: iOS Development, Android Development, Python Flask and Django Web Development
IBM Watson, IBM Cloud (Speech-to-text, Text-to-speech, Database Services, Unix Servers, GPU Servers, NLP, Data Science Experience)
--Frameworks + Tools--
Tensorflow, Pytorch, Xcode, IBM Watson Services, Neo4J, SQL & NoSQL Databases, Jupyter Notebook, Spyder, Eclipse, Android Studio, Autodesk Inventor
Python, C++, C, Swift, Java, HTML, SQL, Cypher