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We’re proud to announce our 2020 Twitch Research Fellowship award winners!
We received applications from many talented and promising graduate students from around the world, carrying out research in a variety of areas relevant to Twitch, including deep learning, applied statistics, and human-computer interaction. We selected Fellows based on the relevance 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 to support their academic research and an offer to connect with a team at Twitch for a full-time paid internship at Twitch HQ.
Amanda Cullen - University of California, Irvine
Amanda Cullen is a PhD candidate at the University of California, Irvine in the Department of Informatics, advised by Dr. Aaron Trammell (Assistant Professor, Informatics) and Dr. Bonnie Ruberg (Assistant Professor, Film and Media Studies).
Amanda’s research uses ethnographic methods to explore the everyday experiences of women on live-streaming platforms, including the many complex decisions they make in regard to personal expression in their online work.
Amanda is also an ARCS Foundation Scholar, and has previous graduate degrees in Cultural Anthropology (University of West Florida) and Public Service (University of Arkansas Clinton School of Public Service).
Alex Lamb - University of Montreal, MILA
Alex Lamb is a PhD candidate in Computer Science at the University of Montreal and the Montreal Institute for Learning Algorithms (MILA), advised by Yoshua Bengio.
Alex researches new algorithms for deep learning aimed at improving their generalization and modularity. Outcomes from this work could aid performance on tasks with high diversity and rapid change.
Alex has an undergraduate degree from Johns Hopkins and a master’s degree from the University of Montreal (supervised by Aaron Courville). Alex previously worked on Amazon’s demand forecasting team with Kari Torkkola.
Alex’s home page.
Sneha Mehta - Virginia Tech
Sneha Mehta is a PhD candidate in the Computer Science department, as well as a member of the Discovery Analytics Center at Virginia Tech, advised by Dr. Naren Ramakrishnan, who is a Thomas L. Phillips Professor of Engineering in the Department of Computer Science and Director of Discovery Analytics Center.
Sneha’s research involves information extraction and sentiment analysis from text streams using natural language processing and machine learning.
Sneha has a bachelor’s degree in Computer Science and a master’s degree in Mathematics from BITS Pilani University in India.
Carlos Toxtli Hernandez - West Virginia University and the National Autonomous University of Mexico (UNAM)
Carlos Toxtli Hernandez is a PhD candidate in Computer Science, conducting research in the areas of crowdsourcing and artificial intelligence. Carlos is part of the HCI lab at West Virginia University and the National Autonomous University of Mexico (UNAM), advised by Dr. Saiph Savage.
Carlos creates tools that shape the future of how crowds collaborate and the things they can do collectively. Carlos is currently designing crowdsourcing systems that coordinate audiences on Twitch to moderate live streams via micro-contributions, using artificial intelligence to learn over time the best methods for leveraging audiences to moderate multimodal content (e.g. text, video, audio) more accurately and consistently at scale.
In the past, Carlos has worked at Google, the United Nations, and Microsoft Research. Carlos is a serial entrepreneur and has created various startups that are transforming the Global South.
Zhengyuan Yang - University of Rochester
Zhengyuan Yang is a PhD candidate in Computer Science at the University of Rochester, advised by Professor Jiebo Luo.
Zhengyuan’s research interests include vision+language (e.g. visual grounding, tracking by language) and human-centered image understanding (e.g. human action recognition, human part parsing). Zhengyuan’s research could have many applications at Twitch, such as language-based video search, chat content understanding, and human-centered video editing.
Zhenguian obtained his bachelor’s degree from the University of Science and Technology of China in 2016.
Zhengyuan’s home page
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:
Jordan Huffaker - University of Michigan
Jordan is a PhD candidate in the Computer Science Department at the University of Michigan, advised by Mark Ackerman. Jordan builds hybrid intelligence systems to combat media manipulation, in the forms of misinformation, hate speech, harassment, and other harmful content.
Jiajing Guo - Cornell
Jiajing is a PhD candidate in the Information Science Department at Cornell University, advised by Susan R. Fussell. Jiajing’s research interests lie in the intersection of design, AI-assisted communication, and online community dynamics.
Will Partin - UNC Chapel Hill
Will is a PhD candidate in the Communication Department at UNC Chapel Hill, advised by Dr. Torin Monahan. Will’s research focuses on the platformization of cultural production with particular emphasis on live streaming, video games, and esports.
Charlie Ringer - University of York
Charlie is a PhD candidate in the Centre for Doctoral Training in Intelligent Games and Games Intelligence (IGGI) at the University of York, jointly advised by Dr. James A. Walker (University of York) and Dr. Mihalis Nicolaou (The Cyprus Institute and Goldsmiths University of London). Charlie’s research is focused on applying deep learning techniques to the identification of interesting moments (e.g. highlights) in livestreams.
Raquel Robinson - University of Saskatchewan
Raquel is a PhD candidate in Computer Science at the University of Saskatchewan, advised by Regan Mandryk (University of Saskatchewan) and Katherine Isbister (University of California, Santa Cruz). Raquel is broadly interested in enhancing engagement and social/emotional connections among streamers and their spectators.
Nataniel Ruiz - Boston University
Nataniel is a PhD Candidate in the Image & Video Computing Group at Boston University, advised by Dr. Stan Sclaroff. Nataniel’s research in computer vision focuses on face, gesture, and behavior analysis, as well as simulation and synthetic data.
Congratulations to this year’s talented group of Fellows and Finalists! We are excited to engage deeper with them, learn more about their research, and support their continued studies.