VietAI TechTalk 2: From supervised to unsupervised learning

Topic: From supervised to unsupervised learning

Time: 8.30am to 11.00am on 23/06/2018

Language: Vietnamese

Location: 227 Đường Nguyễn Văn Cừ, Phường 4, Quận 5, Hồ Chí Minh

Requirements: this talk will be highly technical talk - aims at acedamia people including prof., lecturers and students at technical universities. We have slots for engineers as well.

Speaker Bios:

Hung Bui: He is currently a senior machine learning research scientist at Google DeepMind, Mountain View, CA. His technical expertise and interests include probabilistic graphical models, deep generative models, Bayesian inference and machine learning, especially models for sequential and relational data, with applications in human activity/intent recognition, video understanding and natural language processing. These interests center around the challenging problem of how to make the machine better understand the humans – a problem that plays a central part in intelligent assistive technologies, personal assistance and dialogue management. Before joining Google DeepMind, he was at Adobe Research and Nuance Natural Language Understanding Lab, and also spent almost 10 years at the AI Center, SRI International (formerly Stanford Research Institute). At SRI, he led the multi-institution research team in developing probabilistic inference technologies for understanding the user activities during the CALO project (the largest AI project in history, also known as the project that spun off Siri). Going further back in time, He was an assistant professor at Curtin University, Australia (2000-2003),  Ph.D graduate in computer science (Curtin, 1998), graduate from HUS high school for gifted students, and a maths olympian (silver medal, IMO 1989).

Trieu Trinh: He graduated as a Computer Science student from University of Science HCM, class of 2017. Trieu is a former intern at University of Montreal in 2015, working on Educational Data Mining. In 2016, he interned at Japan Advanced Institute of Science and Technology on the application of Deep Learning in Question Answering. Trieu also worked on Mobile Computer Vision using Deep Learning at Misfit Wearables in summer of 2015. Trieu authored high impact open-sourced projects on Github, contributed to Tensorflow models and recently published at International Conference on Machine Learning 2018. Trieu is currently working at Google Brain, researching the application of Machine Learning in Natural Language Processing.