Il post non è disponibile nella tua lingua. Ecco alcune alternative:
We’re proud to announce our 2021 Twitch Research Fellowship award winners!
This was the second year of the Fellowship Program, and we were excited to receive so many applications from talented and promising graduate students. The research statements that they submitted described exciting work in a wide variety of areas relevant to Twitch, including computer vision, applied statistics, and human-computer interaction. We selected Fellows based on a number of factors, including the novelty and quality of their research, their publication record and recommendation letters, and their ability to craft a vision for how their research could help push forward innovation at Twitch.
Each winner will receive a $10,000 award and a mentorship connection with a scientist at Twitch to help support their independent academic research. In addition, Fellows will participate in a virtual Fellowship summit next year to present their research for our Science and Product teams, including our CEO, Emmett Shear.
Keri Mallari – University of Washington
Keri Mallari is a PhD student in the Human Centered Design and Engineering Department (HCDE) at the University of Washington, advised by Dr. Gary Hsieh. Keri’s research interests are in the field of human-computer interaction and social computing. Her work is focused on the study, design, and development of systems to support online communities, such as livestreamers and their communities.
Keri received her bachelor’s degree from CUNY Lehman College in Mathematics and Computer Science, supported by the Macaulay Honors scholarship program.
Ning Yu – University of Maryland
Ning Yu is a Ph.D. candidate in the joint Computer Science program between the University of Maryland and Max Planck Institute for Informatics, co-advised by Prof. Larry Davis and Prof. Mario Fritz.
Ning’s research aspirations lie in computer vision, computer graphics, and deep learning, with the goal of modeling applications for visual synthesis, forensics, security, and privacy. In particular, his research in generative modeling could power tools for photorealistic media generation, recreation, and processing, as well as strategies for detecting and preventing unethical uses of GANs, such as deepfakes.
Ning obtained his M.S. from the University of Pennsylvania and B.E. from Huazhong University of Science and Technology. He has several industry research experiences at Adobe and NVIDIA.
Richard Faltings – University of Texas, Austin
Richard Faltings is a PhD student in Economics at the University of Texas at Austin, advised by Eugenio Miravete and Jorge Balat.
Richard studies how digital transportation platforms can coordinate riders and vehicles in decentralized markets through appropriate incentives. Outcomes of this research suggest potential incentive mechanisms that Twitch could use to coordinate scheduling across content creators, in order to increase their viewership.
Richard has a bachelor’s degree and a master’s degree from the University of St. Gallen in Switzerland.
Elena Lucherini – Princeton University
Elena is a Ph.D. candidate at Princeton University’s Center for Information Technology Policy, advised by Arvind Narayanan. Her research offers a critical analysis of technology and machine learning. Elena’s current work is focused on developing scalable methods to characterize the societal impact of recommender systems. Her new simulation tool, T-RECS, provides a lens on the potential effects arising from the actions and interactions of users and content creators in an environment mediated by a recommender system.
Elena is excited about studying recommender systems in order to understand long-term impacts on content creators and viewers and to identify strategies for avoiding unintentional effects such as polarization, stereotype reinforcement, and potential unfair treatment of minorities.
Tal August – University of Washington
Tal August is a PhD candidate in Computer Science at the University of Washington advised by Katharina Reinecke and Noah Smith.
Tal’s research explores how to adapt language for different audiences. His goal is to develop automated tools that support communication and conversation in domains such as science communication and within online communities, such as Twitch. These tools could help scientists explain their research to a wider audience of readers or support moderators in community governance and newcomer onboarding.
Because we received such a high volume of outstanding applications, we wanted to recognize an additional set of applicants as Finalists. Finalists will receive a $5,000 award to help support their academic research. The Finalists are:
Sejoon Oh – Georgia Tech
Sejoon is a Ph.D. student in Computer Science at Georgia Institute of Technology, advised by Prof. Srijan Kumar. Sejoon is building the next generation of trustworthy, reliable, and robust recommender systems against adversarial attacks. Sejoon is also interested in tensor analysis, parallel and high-performance computing, and deep learning & data mining.
Simon Friis – MIT
Simon is a PhD candidate in the Economic Sociology Program at the MIT Sloan School of Management, advised by Profs. Ezra Zuckerman Sivan and Ray Reagans. Simon’s research uses public Twitch data to understand the social forces that shape entrepreneurial strategy and valuation in cultural markets.
Brandon Harris – University of Oregon
Brandon is a PhD candidate in the School of Journalism and Communication at the University of Oregon, advised by Dr. Chris Chavez. Brandon’s research examines the relationship between content creators, digital platforms, and the platformization of cultural production throughout the video game, live streaming, and esports industries.
Julia Mendelsohn – University of Michigan
Julia is a PhD student at the University of Michigan School of Information, advised by Ceren Budak and David Jurgens. Julia develops computational models to understand how people discuss controversial sociopolitical issues on social media platforms, and highlights the broader implications of users’ linguistic choices.
Yuntian Deng – Harvard University
Yuntian is a PhD candidate in the Computer Science Department at Harvard University, advised by Prof. Alexander Rush and Prof. Stuart Shieber. Yuntian works on accurate, efficient, and interpretable text generation by combining neural encoder-decoder models and probabilistic graphical modeling.
E. Brooke Phipps – University of Maryland
Brooke is a PhD student in the Rhetoric and Political Culture program within the Communication Department at the University of Maryland. She is advised by Dr. Damien Smith Pfister. Brooke’s research focuses on digital political advocacy, with a special emphasis regarding the experiences of BIPOC, LGBTQ+, and women streamers on live streaming platforms. Brooke’s Twitter and home page.