You can also read more about her experience on LinkedIn.
Bee is currently working at Siemens in deep learning and natural language processing. She has worked on machine translation, sentiment analysis and document similarity tasks for English and German language data. Her work has led to her to use a diverse ranging of technologies including Docker, AWS and deep learning libraries like Keras and PyTorch.
In 2017, she worked for Mozilla as a research and development intern. During her internship, she worked with the Open Innovation and Participation Team to advise Mozilla leadership on a global diversity and inclusion strategy. She conducted qualitative research, interviews and data analytics to assist in building this strategy for Mozilla’s volunteer community. Additionally, she proposed and led quantitative analysis using data analytics, machine learning (clustering algorithms) and NLP (sentiment analysis and topic modeling) to augment existing qualitative community research. At the end of her internship, she participated in an international work event based on excellent performance.
Bee is interested in using data to understand human behavior in social environments. Her research uses interdisciplinary methods drawn from psychology, neuroscience, graph theory and AI to get a deeper understanding of human behaviour.
In 2016, she was a predoctoral fellow at the Max Planck Institute for Human Development in Berlin. Her work focused on understanding human decision making in online social environments. She worked with the Adaptive Behavior and Cognition (ABC) research group under Dr. Ozgur Simsek. She was also invited to attend 2016 Summer Institute on Bounded Rationality at MPIB.