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<div dir="ltr"><span style="text-decoration: none; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px; background-color: rgb(255, 255, 255); display: inline !important;">This is an announcement of Yihua Cheng's
MS Presentation</span><br style="text-decoration: none; box-sizing: content-box; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px;">
<span style="text-decoration: none; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px; background-color: rgb(255, 255, 255); display: inline !important;">===============================================</span><br style="text-decoration: none; box-sizing: content-box; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px;">
<span style="text-decoration: none; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px; background-color: rgb(255, 255, 255); display: inline !important;">Candidate: Yihua Cheng</span><br style="text-decoration: none; box-sizing: content-box; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px;">
<br style="text-decoration: none; box-sizing: content-box; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px;">
<span style="text-decoration: none; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px; background-color: rgb(255, 255, 255); display: inline !important;">Date: Thursday, May 11, 2023</span><br style="text-decoration: none; box-sizing: content-box; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px;">
<br style="text-decoration: none; box-sizing: content-box; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px;">
<span style="text-decoration: none; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px; background-color: rgb(255, 255, 255); display: inline !important;">Time: 10 am CST</span><br style="text-decoration: none; box-sizing: content-box; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px;">
<br style="text-decoration: none; box-sizing: content-box; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px;">
<span style="text-decoration: none; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px; background-color: rgb(255, 255, 255); display: inline !important;">Remote Location: </span><a href="https://urldefense.com/v3/__https://uchicago.zoom.us/j/3150893650?pwd=RFgxNEE2MUQ0QzlsVXF3Ym94bDQ2Zz09__;!!BpyFHLRN4TMTrA!-0ZZKe84CprwUS3x1FJd3qYU59qrrBPu1RfqoaVL9zMoIEcWcLpfmrtXpC73PAp5u1XupKsG4PXfIPtx5WTc9CYdIOuXm8fQw1tq$" target="_blank" rel="noopener noreferrer" data-auth="NotApplicable" style="box-sizing: content-box; margin: 0px; font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px;">https://uchicago.zoom.us/j/3150893650?pwd=RFgxNEE2MUQ0QzlsVXF3Ym94bDQ2Zz09</a><br style="text-decoration: none; box-sizing: content-box; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px;">
<br style="text-decoration: none; box-sizing: content-box; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px;">
<span style="text-decoration: none; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px; background-color: rgb(255, 255, 255); display: inline !important;">Location: JCL 390</span><br style="text-decoration: none; box-sizing: content-box; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px;">
<br style="text-decoration: none; box-sizing: content-box; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px;">
<span style="text-decoration: none; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px; background-color: rgb(255, 255, 255); display: inline !important;">M.S. Paper Title: Online Profiling and Adaptation of Quality
Sensitivity in Internet Video</span><br style="text-decoration: none; box-sizing: content-box; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px;">
<br style="text-decoration: none; box-sizing: content-box; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px;">
<span style="text-decoration: none; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px; background-color: rgb(255, 255, 255); display: inline !important;">Abstract: Video streaming systems separate two processes:
(1) online video streaming (which optimizes quality metrics, such as higher bitrates, and fewer stalls), and (2) offline modeling of quality sensitivity (i.e., how the quality metrics affect average user experience). As bandwidth scarcity and resource contention
worsen, it is pressingly needed to better allocate resources by finer-grained modeling of how quality sensitivity varies during each video. However, per-video quality-sensitivity modeling has been impractical, especially for live videos, as traditional offline
user studies can be too slow for a new video before viewers watch it.</span><br style="text-decoration: none; box-sizing: content-box; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px;">
<span style="text-decoration: none; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px; background-color: rgb(255, 255, 255); display: inline !important;">We explore an alternative architecture, where quality sensitivity
is modeled online by analyzing user actions in real</span><br style="text-decoration: none; box-sizing: content-box; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px;">
<span style="text-decoration: none; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px; background-color: rgb(255, 255, 255); display: inline !important;">video sessions as they stream the same video. The challenge
is how to model quality sensitivity reliably and apply it in near-realtime to improve concurrent and future video sessions. We address the challenge in the context of SensitiFlow, a controller that orchestrates adaptive-bitrate (ABR) logic of video sessions
to optimize the common user-satisfaction metric of user engagement (view time per session). SensitiFlow creates an online control loop that (i) gradually profiles quality sensitivity per video segment as more user experience-related feedback (e.g., exit or
skip) is received from video sessions, and (ii) optimizes the ABR decisions of the video sessions to jointly improve their user engagement and generate more feedback. SensitiFlow’s control loop is fast enough to profile quality sensitivity online and optimize
bitrate decisions under common viewer arrival patterns of live events (e.g., live sports and TV shows). Using the real traces collected from 7.6M video sessions, we show that compared to a state-of-the-art (baseline) ABR logic agnostic to the variation of
quality sensitivity within a video, SensitiFlow (without using more bandwidth) can realize 80% of the improvement in engagement that would have been obtained by a hypothetical “oracle” system having the knowledge of quality sensitivity in advance. Our user
study also confirms that SensitiFlow can improve the mean opinion score (MOS) by 40% over the baseline ABR logic, suggesting that SensitiFlow’s online profiling of quality sensitivity is effective.</span><br style="text-decoration: none; box-sizing: content-box; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px;">
<br style="text-decoration: none; box-sizing: content-box; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px;">
<span style="text-decoration: none; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px; background-color: rgb(255, 255, 255); display: inline !important;">Advisors: Junchen Jiang</span><br style="text-decoration: none; box-sizing: content-box; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px;">
<br style="text-decoration: none; box-sizing: content-box; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px;">
<span style="text-decoration: none; color: rgb(33, 33, 33); font-family: Roboto, Helvetica, Arial, sans-serif; font-size: 14.666667px; background-color: rgb(255, 255, 255); display: inline !important;">Committee Members: Junchen Jiang, Nick Feamster, Vyas Sekar</span><br>
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