JIAN GAO

Chino, California ***** 909-***-**** add6l5@r.postjobfree.com

SUMMARY

PhD in CS with 9 years’ experience in machine learning, sequential prediction, and image processing. RESEARCH INTERESTS

• Unsupervised Machine Learning, Stochastic Optimization, Game Theory

• Image Processing, Time-series Prediction, Deep Neural Networks EDUCATION

Ph.D. Computer Science, New York University Spring 2020 Dissertation: Game-Theoretic Approaches for Generative Modeling. (Advisor: Hamidou Tembine, GPA: 4.0) M.S. & B.S. Pattern Recognition & Intelligent Systems, Tongji University Spring 2015 T: An Affine Invariant Approach for Dense Wide-baseline Image Matching. (Advisor: Fanhuai Shi, GPA: 3.8) WORK EXPERIENCE

Data Analytics Intern, 05/2019 to 08/2019

Hitachi America, Ltd – Santa Clara, CA

• Time series data analysis - solar & wind power forecasting using XGBoost and Ensemble model (paper [6])

• Developed a system for renewable energy and demand forecasting using online & offline data Computer Vision Intern, 05/2018 to 08/2018

Phillips Lighting – Boston, MA

• Google street view image object detection and classification using Mask R-CNN

• Automated generation of artistic indoor images using GANs (IP Filing Incentive Award, U.S. patent filed)

• Speech processing, emotional voice conversion based on neural network autoencoders RESEARCH EXPERIENCE

PhD program, Learning & Game Theory Laboratory, NYUAD, 2015-2020

• Signal processing, filtering, sequential prediction, aircraft tracking (U.S. Air Force Research Project)

• Deep generative learning, GANs, distributionally robust optimization (book chapter [2])

• Vehicle tracking, video analysis, object detection, Intelligent Transportation Systems (paper [1][12])

• Nonparallel emotional speech conversion, generative model for style transfer Master program, Image & Vision Computing Laboratory, Tongji University, 2012-2015

• Developed a system for image-based plant leaf detection and classification

• Dense wide-baseline matching, stereo matching, camera calibration for 3D scene reconstruction PROGRAMMING SKILLS

• Python, C/C++, Matlab, Linux, Git, AWS, Jupyter • Tensorflow, Keras, Pandas, Scikit-learn, PyTorch PUBLICATIONS

1. J. Gao and H. Tembine, "Distributed Mean-Field-Type Filters for Traffic Networks," in IEEE Transactions on Intelligent Transportation Systems, pp. 507-521, Feb. 2019. doi:10.1109/TITS.2018.2816811

2. Jian Gao, Deep Chakraborty, Hamidou Tembine, and Olaitan Olaleye, “Nonparallel Emotional Speech Conversion,” INTERSPEECH 2019, Graz, Austria, September 2019. 3. Jian Gao, Yida Xu, Julian Barreiro-Gomez, Massa Ndong, Michalis Smyrnakis and Hamidou Tembine

(September 5th

, 2018) Distributionally Robust Optimization. In Jan Valdman, Optimization Algorithms, IntechOpen. DOI: 10.5772/intechopen.76686. ISBN: 978-1-78923-677-4 4. Jian Gao and Hamidou Tembine, Distributionally Robust Games: Wasserstein Metric, International Joint Conference on Neural Networks (IJCNN), Rio de Janeiro, Brazil, July 2018 5. Jian Gao and Olaitan Olaleye. "Automated generation of artistic and photo-realistic synthetic lighting scene images and realizations using generative networks", (ID: 2018ID80933, US Patent submitted) 6. Jian Gao, Panitarn Chongfuangprinya, Yanzhu Ye, Bo Yang, "A Three-Layer Hybrid Model for Wind Power Prediction", IEEE PES GENERAL MEETING, Montreal, Canada, August 2020 7. Jian Gao and Hamidou Tembine, Distributionally Robust Games for Deep Generative Learning, July 2018. DOI: 10.13140/RG.2.2.15305.44644

8. Jian Gao and Hamidou Tembine, Bregman Learning for Generative Adversarial Networks, Chinese Control and Decision Conference (CCDC), Shenyang, China, June 2018 (Best paper finalist Award) 9. Dario Bauso, Jian Gao and Hamidou Tembine, Distributionally Robust Games: f-Divergence and Learning, 11th EAI International Conference on Performance Evaluation Methodologies and Tools

(VALUETOOLS), Venice, Italy, Dec 2017

10. Jian Gao and Hamidou Tembine, Empathy and Berge equilibria in the Forwarding Dilemma in Relay- Enabled Networks, International Conference on Wireless Networks and Mobile Communications

(WINCOM), Rabat, Morocco, Nov 2017 (Best paper Award) 11. Jian Gao and Hamidou Tembine, Correlative Mean-Field Filter for Sequential and Spatial Data Processing, in the Proceedings of IEEE International Conference on Computer as a Tool (EUROCON), Ohrid, Macedonia, July 2017

12. Jian Gao and Hamidou Tembine, Distributed Mean-Field-Type Filter for Vehicle Tracking, in American Control Conference (ACC), Seattle, USA, May 2017 13. Jian Gao and Hamidou Tembine, Distributed mean-field-type filters for Big Data assimilation, in the second IEEE International Conference on Data Science and Systems (HPCC-SmartCity-DSS), Sydney, Australia, Dec 2016, pp. 1446-1453.

14. Fanhuai Shi, Jian Gao, Xixia Huang, An affine invariant approach for dense wide baseline image matching. International Journal of Distributed Sensor Networks (IJDSN) 12(12) (2016) 15. Jian Gao, Fanhuai Shi, A Rotation and Scale Invariant Approach for Dense Wide Baseline Matching. Intelligent Computing Theory - 10th International Conference, ICIC (1) 2014: 345-356