tedshaowang.com
A vulnerability disclosure policy (VDP), also referred to as a responsible disclosure policy, describes how an organization will handle reports of vulnerabilities submitted by ethical hackers. A VDP must thus be easily identifiable via a simple way, a security.txt notice.
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<h1><a href="/">Ted Shaowang</a></h1>
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Contact: swjz@uchicago.edu<br />
Office: Crerar 299
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<h1 id="hi">Hi!</h1>
<p>I am currently a fourth-year PhD student in computer science at the University of Chicago, advised by <a href="http://sanjayk.io/" target="_blank">Sanjay Krishnan</a>.
My research interests include edge-based data systems and video analytics.</p>
<h2 id="projects">Projects</h2>
<p><strong>EdgeServe</strong> is a decentralized model serving system that optimizes data movements and model placements within an edge cluster. <a href="https://github.com/swjz/EdgeServe" target="_blank">[Link]</a></p>
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<p><strong>Sensor Fusion on the Edge: Initial Experiments in the EdgeServe System</strong> <a href="assets/pdf/bidede22-shaowang.pdf">[Paper]</a><br />
<strong>Ted Shaowang</strong>, Xi Liang and Sanjay Krishnan.<br />
BiDEDE 2022: <em>The International Workshop on Big Data in Emergent Distributed Environments</em></p>
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<p><strong>Declarative Data Serving: The Future of Machine Learning Inference on the Edge</strong> <a href="http://www.vldb.org/pvldb/vol14/p2555-shaowang.pdf">[Paper]</a><br />
<strong>Ted Shaowang</strong>, Nilesh Jain, Dennis D. Matthews and Sanjay Krishnan.<br />
VLDB 2021: <em>The 47th International Conference on Very Large Data Bases</em></p>
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<p><strong>AMIR</strong> (Active Multimodal Interaction Recognition) is a framework for activity recognition that trains independent models for video and network data respectively, and subsequently combines the predictions from both models using a meta-learning method. <a href="https://amir-vidnet.github.io/" target="_blank">[Link]</a></p>
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<li><strong>AMIR: Active Multimodal Interaction Recognition from Video and Network Traffic in Connected Environments</strong> <a href="https://www.paparrizos.org/papers/LiuUbiComp23.pdf">[Paper]</a><br />
Shinan Liu, Tarun Mangla, <strong>Ted Shaowang</strong>, Jinjin Zhao, John Paparrizos, Sanjay Krishnan and Nick Feamster<br />
UbiComp 2023: <em>The ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT)</em></li>
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<p><strong>VizEx</strong> is an ongoing project that explores how to effectively debug long-tail errors in video analytics pipelines.</p>
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<li><strong>Towards Causal Physical Error Discovery in Video Analytics Systems</strong> <a href="assets/pdf/hilda22-video.pdf">[Paper]</a><br />
<strong>Ted Shaowang<sup>*</sup></strong>, Jinjin Zhao<sup>*</sup>, Stavros Sintos, Sanjay Krishnan<br />
HILDA 2022: <em>Workshop on Human-In-the-Loop Data Analytics</em></li>
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