I am a Machine Learning Scientist at Amazon (Seattle) building the Amazon Product Knowledge Graph. I work on developing machine learning and deep learning models for open information extraction and representation learning. My doctoral thesis at Max Planck Institute for Informatics (Germany) obtained the prestigious SIGKDD 2018 Doctoral Dissertation Award Runner-up (one of the top-3 best doctoral dissertations world-wide in data mining). My research interests involve representation learning and graphical models to capture the joint interaction between structure, content, and dynamics of information --- with a particular focus on interpretability.
In my PhD dissertation, I worked on probabilistic graphical models to extract "credible", "trustworthy" and "expert" information from large-scale, non-expert, user-generated online content. I developed machine learning models that exploit the joint interaction between users, language, and their evolution in online communities for tasks like: credibility analysis, personalized content recommendation, (latent) experience-aware item recommendation, finding (latent) topic-specific experts in online communities, spam and anomaly detection etc.[PhD Thesis on Credibility Analysis] [SIGKDD 2018 Dissertation Talk Slides] [CV]