Biography
Chong Wang is a Applied Scientist II at Amazon Advertising. He received his PhD degree in Information Systems department of New Jersey Institute of Technology in 2017. He was working with Prof. Yi Chen.
His research interests are broadly in Machine Learning, Natural Language Processing, Text Mining, and Computational Advertising.
The topic of the dissertation project is Viewability Prediction for Display Advertising.
Education
Full-Time Work Experience
- Applied Scientist II @ Amazon
New York City
Oct. 25, 2021 - Present
- Data Scientist @ S&P Global
New York City
Sep. 4, 2018 - Oct. 22, 2021
- Research Scientist @ Thomson Reuters
New York City
Oct. 23, 2017 - Sep. 3, 2018
Internship Experience
- Data Science Intern @ Jet.com
Hoboken, NJ
Aug. 7, 2017 - Oct. 20, 2017
- Intern @ Forbes Media
Jersey City, NJ
Jul. 4, 2016 - Aug. 31, 2016
- Research Intern @ Verisign Inc.
Reston, VA
May. 18, 2015 - Aug. 7, 2015
Publications
- Ma, Z., Wang, C., Bang, G., Liu, X, (2020) Utilization of Deep Learning to Mine Insights from Earning Calls for Stock Price Movement Predictions, the 2020 ACM International Conference on AI in Finance
- Ma, Z., Bang, G., Wang, C., Liu, X, (2020) Towards Earnings Call and Stock Price Movement, 2020 KDD Workshop on Machine Learning in Finance (KDD 2020 Workshop)
- Wang, C., Kim, L., Bang, G., Singh, H., Kociuba, R., Pomerville, S., Liu, X., (2020) Discovery News: A Generic Framework for Financial News Recommendation, The 32nd Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-20)
- Wang, C., Chen, Y. (2020). Topical Classification of Domain Names Based on Subword Embeddings. Electronic Commerce Research and Applications (ECRA).
- Zhao, S., Kalra, A., Wang, C.,
Borcea, C., Chen, Y. (2019). Ad Blocking Whitelist Prediction for Online Publishers. 2019 IEEE International Conference on Big Data (IEEE BigData 2019).
- Kalra, A.*, Wang, C.*,
Borcea, C., Chen, Y. (2019). Reserve Price Failure Rate Prediction with Header Bidding in Display Advertising. The 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD 2019). (*contributed equally; oral session acceptance rate = 6.4%)[video]
- Wang, C., Zhao, S., Kalra, A., Borcea, C., Chen, Y. (2018). Webpage Depth Viewability Prediction using Deep Sequential Neural Networks. IEEE Transactions on Knowledge and Data Engineering (TKDE), vol. 31, no. 3, pp. 601-614, doi: 10.1109/TKDE.2018.2839599
- Acherman, B., Wang, C., Chen, Y. (2018). A Session-Specific Opportunity Cost Model for Rank-Oriented Recommendation. Journal of the Association for Information Science and Technology (JASIS&T), 69: 1259-1270. doi: 10.1002/asi.24044
- Wang, C., Kalra, A, Zhou, L., Borcea, C., Chen, Y. (2018). Predictive Models and Analysis For Webpage Depth-level Dwell Time. Journal of the Association for Information Science and Technology (JASIS&T), 69: 1007-1022. doi: 10.1002/asi.24025
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Liu, Z., Wang, C., & Chen, Y. (2018). Keyword Search on Temporal Graphs. IEEE 34rd International Conference on Data Engineering in Data Engineering (ICDE).
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Zhao, S., Wang, C., Kalra, A., Vaks, L., Borcea, C., & Chen, Y. (2017). Ad Blocking and Counter-Ad Blocking: Analysis of Online Ad Blocker Usage, . In the Proceeding of the 23rd Americas Conference on Information Systems (AMCIS 2017).
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Wang, C., Kalra, A., Zhou, L., Borcea, C., & Chen, Y. (2017). Probabilistic Models For Ad Viewability Prediction On The Web. IEEE Transactions on Knowledge and Data Engineering (TKDE), vol. 29, no. 9, pp. 2012-2025, doi: 10.1109/TKDE.2017.2705688
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Liu, Z., Wang, C., & Chen, Y. (2017). Keyword Search on Temporal Graphs. IEEE Transactions on Knowledge and Data Engineering (TKDE), vol. 29, no. 8, pp. 1667-1680, doi: 10.1109/TKDE.2017.2690637
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Wang, C., Kalra, A., Borcea, C., & Chen, Y. (2016, October). Webpage Depth-level Dwell Time Prediction.
In Proceedings of the 25th ACM International on Conference on
Information and Knowledge Management (pp. 1937-1940). ACM. doi:
10.1145/2983323.2983878
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Wang, C., Kalra, A, Borcea, C., Chen, Y. (2015, Nov).
Revenue-Optimized Webpage Recommendation.
2015 IEEE International Conference on Data Mining Workshop (ICDMW),
Atlantic City, NJ, USA, pp. 1558-1559.
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Wang, C., Kalra, A, Borcea, C., Chen, Y. (2015, Oct).
Viewability Prediction for Online Display Ads.
In Proceedings of the 24rd ACM International Conference on Information and Knowledge Management (CIKM'15).
Melbourne, Australia, 413-422. doi: 10.1145/2806416.2806536
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Watrous-deVersterre, L. Wang, C. Song, M. (2012)
Concept Chaining utilizing Meronyms in Text Characterization,
In Procs. of 16th ACM/IEEE Joint Conference on Digital Libraries
(JCDL'12), Washington, DC, USA, 241-248. doi: 10.1145/2232817.2232862
Patents
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Ma, Z., Wang C., Liu X., Deep Learning from Earning Calls for Stock Price Movement Prediction, US Patent App. 17/030,953
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Wang C., Cesar, R., Papadimitriou, A., Liu X., Automated event processing system, US Patent App. 16/939,821
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Kim L., Ma Z., Bang G., Wang C., Singh H., Kociuba R., Pomerville S., Liu X., Automated news ranking and recommendation system, US Patent App. 11,334,949
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Wang C., Kim L., Bang G., Singh H., Kociuba R., Pomerville S., Liu X., Deep learning-based two-phase clustering algorithm, US Patent App. 16/779,363
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Singh, H., Kim, L., Bang G., Wang C., Kociuba R., Pomerville S., Liu X., Subscription-enabled news recommendation system, US Patent App. 16/779,305
Professional Services
- PC Member for CIKM 2017,
CIKM 2018,
KDD 2022,
SIGIR 2020,
SIGIR 2021,
ICAIF 2020 2021,
WSDM 2021,
AAAI 2021,
AAAI 2021 KDF workshop,
The Web Conf 2021 NRI-1 Workshop,
INTELLI 2021,
WSDM 2022,
AAAI 2022,
SIGIR 2022,
CIKM 2022,
VLDB 2023,
WSDB 2023,
AAAI 2023.
- Journal Reviewer for
IEEE Transactions on Knowledge and Data Engineering,
Information Science,
Information Processing and Management,
Artificial Intelligence Review,
IEEE Transactions on Intelligent Transportation Systems,
IEEE Transactions on Network Science and Engineering,
INFORMS Journal on Computing,
Heliyon,
Electronic Commerce Research and Applications,
Journal of Web Engineering
- Conference Reviewer for KDD 2021, AMCIS 2015, SIGIR 2014, EDBT 2014, SIGMOD 2014, VLDB 2014, ICDE 2014
Skills
- Programming Languages: Python, Java, Tensorflow, Pytorch, SQL, MongoDB
- Software: MySQL, SAS 9, MongoDB
Contact
- E-mail: munichong at gmail.com
- WeChat: munichong
- Linkedin:
Chong Wang
Miscellaneous