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Shuai ZhaoResearch Interests: Search/Recommendation/Advertising, Auction Mechanism Design, Natural Language Processing, Causal Inference and Experiment Design Broader Interests: Optimization Methods, Contextual Bandit/Reinforcement Learning/Online Learning, Philosophy of Science/Theology of Christ, Organizational Behavior Email: cheershuaizhao(at)gmail.com |
Short Bio |
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I am a Senior Machine Learning Engineer at TikTok Shop Advertising. Previously, I worked at LinkedIn and Amazon, focusing on machine learning research and applications in search and recommender systems. I received my Ph.D. in Data Science from NJIT, where my research included collaborations with Forbes Media, AT&T Labs Research, and Hearst Communications. |
Work Experience |
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Senior Machine Learning Engineer in ML and auction design, TikTok, Seattle, WA. 08/2024-Now Senior Machine Learning Engineer, Linkedin, Seattle, WA. 07/2022-08/2024 Applied Scientist II, Amazon Alexa AI, Seattle, WA. 11/2020-07/2022 Machne Learning Research Collaborator (Mentor: Wen-Ling Hsu, Guy Jacobson), AT&T Labs - Research, Bedminster, NJ. 05/2018~10/2020 Data Science Research Collaborator (Supervisor: Achir Kalra), Forbes Media, Newport, NJ. 08/2016~10/2020 Oracle ERP Financial Engineer (Fulltime), Hand ERP Solutions Ltd. (SSE:300170), Shanghai, China. 06/2014~06/2015 |
Technical Skills |
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Python, Java, R, C++, Shell/Scripting, MongoDB, MySQL, TensorFlow, pyTorch, DeepLearning4J, Spark, Hive, Pig, Docker, Tableau, Jupyter Notebook |
Selected Publications |
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Shuai Zhao, Michael Chen, Cristian Borcea, Yi Chen, Personalized Dynamic Counter Ad-Blocking Using Deep Learning, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023 Shuai Zhao, Wen-Ling Hsu, George Ma, Tan Xu, Guy Jacobon and Raif Rustamov, Characterizing and Learning Representation on Customer Contact Journeys in Cellular Services, The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020. Shuai Zhao, Achir Kalra, Cristian Borcea, and Yi Chen, Measuring the Impact of Counter-Ad-blocking Strategies on User Engagement, The Web Conference (WWW), Oral Presentation, 2020. Shuai Zhao, Xiaopeng Jiang, Guy Jacobson, Rittwik Jana, Wen-Ling Hsu, Raif Rustamov, Manoop Talasila, Syed Anwar Aftab, Yi Chen and Cristian Borcea, Cellular Network Traffic Prediction Incorporating Handover: A Graph Convolutional Approach, The 17th Annual IEEE International Conference on Sensing, Communication and Networking (SECON), 2020. Shuai Zhao, Roshani Bharati, Cristian Borcea, and Yi Chen, Privacy-Aware Federated Learning for Page Recommendation, IEEE International Conference on Big Data (BigData), 2020. Qiong Wu, Wen-Ling Hsu, Tan Xu, Zhenming Liu, George Ma, Guy Jacobson and Shuai Zhao, Speaking with Actions - Learning Customer Journey Behavior, IEEE International Conference on Semantic Computing (ICSC), 2019. Chong Wang*, Shuai Zhao*, Achir Kalra, Cristian Borcea, and Yi Chen. Webpage Depth Viewability Prediction using Deep Sequential Neural Networks, IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol.31, No. 3, 2019. Shuai Zhao, Manoop Talasila, Guy Jacobson, Cristian Borcea, Syed Anwar Aftab, and John F. Murray, Packaging and Sharing Machine Learning Models via the Acumos Open Platform, IEEE International Conference on Machine Learning and Applications (ICMLA), 2018. Chong Wang, Shuai Zhao, Achir Kalra, Cristian Borcea, and Yi Chen. Predictive Models and Analysis for Webpage Depth‐Level Dwell Time, Journal of the Association for Information Science and Technology (JASIST), Vol.69, No. 8, 2018. |
Services |
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Reviewer: SIGIR, VLDB, WSDM, CIKM, ICDE, TKDE, TOIS, INFORMS Journal of Computing, Artificial Intelligence Review, AMCIS Group Leader in Evangelical Chinese Church, Redmond, WA |