I am a scientist affiliated with the Empirical Inference Department at Max Planck Institute for Intelligent Systems, Tübingen, Germany. From January 2016 to December 2017, I was a lecturer at the Department of Mathematics, Faculty of Science, Mahidol University in Thailand. My research interest lies in the area of machine learning, its theory, and applications. I am particularly interested in statistical learning theory, kernel methods, Bayesian nonparametric, large-scale learning, and counterfactual prediction. My current research aims to bridge the gap between randomized experiments and empirical inference from data with applications in observational studies, clinical trial, economics, and online advertisement.
As a PhD student, I have worked primarily with Prof. Bernhard Schölkopf. In December 2015, I was awarded the doctoral degree with summa cum laude, that is, "with greatest honor", from the University of Tübingen. I previously obtained a master's degree with distinction in machine learning from University College London (UCL), United Kingdom. At UCL, I worked primarily with Prof. Yee Whye Teh. (M.Sc. thesis advisor) at the Gatsby Computational Neuroscience Unit and Prof. John Shawe-Taylor (M.Sc. Tutor) at the Center for Computational Statistics and Machine Learning. During my PhD, I was a visiting scholar at the Institute of Statistical Mathematics, Japan; Center for Cosmology and Particle Physics, New York University; Palomar Observatory in San Diego; American Museum of Natural History, and Institut für Stochastik und Anwendungen, University of Stuttgart, among others.
In 2011, it was a great honour for me to co-organize a Festschrift symposium together with my PhD advisor, Prof. Bernhard Schölkopf, and Yevgeny Seldin to honor Prof. Vladimir Vapnik, on the occasion of his 75th birthday. I also helped organize the 29th Neural Information Processing Systems (NIPS 2016), which took place in Barcelona, Spain (together with Ulrike von Luxburg, Isabelle Guyon, Behzad Tabibian, Rohit Babbar, and several other people). In December 2016, I was also invited to participate in the Dagstuhl Seminar in New Directions for Learning with Kernels and Gaussian Processes.