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Dr. Yang Zhao | Risk Management | Best Researcher Award

Staff Software Engineer, Xmotors.ai, United States

Yang Zhao is a distinguished researcher and software engineer specializing in operations research, machine learning, and simulation-based evaluation of autonomous systems. With a deep passion for data-driven insights, he has made significant contributions to the fields of causal inference, risk modeling, and volatility analysis. Currently based in Mountain View, California, he brings a wealth of expertise in statistics, econometrics, and artificial intelligence to his work in autonomous vehicle assessment and optimization. 🚀

Publication Profile

ORCID

🎓 Education

Yang Zhao holds a Ph.D. in Operations Research from North Carolina State University (2018), where he maintained a perfect 4.0 GPA and pursued a minor in Statistics. His research focused on simulation, risk management, and volatility modeling. Prior to this, he earned a B.S. in Financial Management from Huazhong University of Science and Technology in China (2013). His academic journey has equipped him with a strong foundation in mathematical modeling, optimization, and data science. 📚

💼 Experience

With a career spanning across top technology and research-driven companies, Yang Zhao has held key roles in the autonomous vehicle and data science sectors. He is currently a Staff Software Engineer at Xmotors.ai (2025–Present), where he develops simulation-based evaluation workflows for autonomous driving systems. Previously, as a Senior Data Scientist at Cruise LLC (2022–2025), he contributed to scene detection, safety proxy modeling, and reliability performance prediction. His prior experience includes roles at DiDi Labs (2021–2022), where he built causal inference models for pricing strategies, and SAS Institute (2018–2021), where he developed deep learning-based causal inference products and Monte Carlo simulation tools. His expertise in data science, machine learning, and simulation has been instrumental in advancing AI-driven decision-making. 🏆

🏅 Awards and Honors

Yang Zhao has been recognized for his groundbreaking contributions in statistics, econometrics, and AI-driven solutions. His innovative work in deep learning for causal inference and policy optimization has led to multiple patents. His contributions to risk estimation and volatility modeling have been published in top-tier journals, further solidifying his reputation in the field. His cutting-edge software products at SAS Institute have been widely utilized in financial modeling and simulation. 🏅

🔬 Research Focus

Yang Zhao’s research interests lie at the intersection of machine learning, statistical modeling, and AI-driven decision-making. He has extensively worked on causal inference, deep learning, survival analysis, time-series forecasting, and risk assessment. His expertise in simulation-based modeling for autonomous systems, safety evaluation, and reliability estimation has contributed to advancements in self-driving technology. Additionally, his work on Bayesian analysis, stochastic processes, and Monte Carlo methods has played a crucial role in optimizing financial and operational risk models. 📊

🎯 Conclusion

Yang Zhao is a visionary researcher and software engineer whose expertise in simulation, AI, and statistical modeling has had a profound impact on autonomous systems, risk assessment, and financial modeling. His deep understanding of machine learning and optimization, combined with hands-on experience in AI-driven evaluation, makes him a leading figure in his field. With multiple patents, high-impact publications, and contributions to top AI companies, he continues to drive innovation in data science and AI applications. 🚀

📚 Publications

A Simple and Robust Approach for Expected Shortfall Estimation (2021) – Journal of Computational Finance, 25(1). [[Read More](website W)] 📖

On GARCH and Autoregressive Stochastic Volatility Approaches for Market Calibration and Option Pricing (2023) – Risks, 13(2):31. [[Read More](website W)] 📖

Dr. Yang Zhao | Risk Management | Best Researcher Award

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