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Shuai ZhaoMotto: To Advance Technology For Better Experience. Research Interests: Search/Recommendation/Advertising, Natural Language Processing, Causal Inference and Experiment Design Broader Interests: Optimization Methods, Bandit/Reinforcement Learning, Philosophy of Science, Organizational Behavior Email: sz255(at)njit.edu |
Short Bio |
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I am a machine learning engineer at Linkedin. Previously, I was an applied scientist at Amazon. I received Ph.D. in Data Science at NJIT, during when my research collaborated with Forbes Media, AT&T Labs-Research and Hearst Communications. I received my Bacholar of Information Systems at Xidian University. |
Work Experience |
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Machine Learning Engineer, Linkedin, Seattle, WA. 07/2022-Current 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 Volunteer in Evangelical Chinese Church, Redmond, WA |