ISyE Seminar Series: Nishith Pathak

Nishith Pathak

"Using Deep Networks and Transfer Learning for Player Experience Management in Online Games"

Presentation by Nishith Pathak
Data Scientist
Wargaming, Austin

3:30 pm - Seminar
4:30 pm - Reception, snacks and beverages

About the seminar:

Online games are a rich eco-system of many users interacting and participating in goal oriented activities. Developing and maintaining such systems is a non-trivial process. User satisfaction in online games is an important and complex concept which has many factors feeding into it, such as attaining goals in the game, the social experience of interacting with other players as well as the UI and UX aspects of the game world. Traditionally the gaming industry has relied on game designers’ experience and user surveys along with AB testing for informing various decisions related to these topics. However, with recent advances in machine learning, particularly the ability of deep networks to deal with unstructured data, there are now various possibilities for designing automated systems for more agile, scalable and effective user experience management. This talk will focus on how how deep networks and transfer learning can be used for some of the challenges faced in maintaining a positive user experience. We specifically look at models for analyzing text data and focus on two problems. The first one is related to identifying toxic behavior among users. The second problem is extracting sentiment and relevant topics from user feedback.


Dr. Nishith Pathak is a senior Data Scientist with, developer of some of the most popular online games such as World of Tanks and World of Warships. He completed his PhD in Computer Science from the University of Minnesota Twin Cities, Minneapolis, MN and his Bachelors in Technology from the Indian Institute of Technology, New Delhi. His research interests lie in the area of machine learning and its application in the gaming domain. He has collaborated actively with industry leaders and has over thirteen years of experience researching, developing and implementing systems for facilitating processes in various aspects of a game’s life cycle involving development as well as maintainence. He has also published various peer-reviewed research articles in leading IEEE and ACM conferences as well as journals. For the last four years he has been working at the Prague and Austin locations for and has been involved in developing machine learning based systems related to customer satisfaction, game balance and user skill estimation.

Watch Seminar:

Start date
Wednesday, Oct. 5, 2022, 3:30 p.m.
End date
Wednesday, Oct. 5, 2022, 4:30 p.m.