I am a Research Staff Member in the Scalable Knowledge Intelligence Group at IBM Research Almaden. My background is in applying deep learning techniques on large noisy unlabelled multimodal data. This includes incorporating signal processing techniques to time series data as well as computer vision to visual data. Currently, I am working in the space of combining NLP and computer vision techniques for Document extraction and understanding.
I received my PhD in Computer Science in 2019 from the University of Washington in the areas of computer vision and computational neuroscience, co-advised by Bing Brunton, Rajesh Rao and Ali Farhadi. My work started a new line of research in the lab that uses machine learning to automatically analyze unlabelled clinical videos and intracranial EEG, which was generously funded by DARPA and the NSF. I was also fortunately supported as a joint fellow of UWIN (University of Washington institute of neuroengineering) and the eScience Institute, on top of my Canadian NSERC fellowship. I received my MSc in Computer Science in 2016, also from the University of Washington and my Honours BSc in Computer Science in 2014 from the University of British Columbia with the top student award in my graduating class.