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How Dr. Jing Gao Applies Academic Insights at Meta

How Dr. Jing Gao Applies Academic Insights at Meta
Photo Courtesy: Jayleen Yuan

In the dynamic intersection of academia and industry, few exemplify the seamless blend of theoretical knowledge and practical application as profoundly as Jing Gao. A Research Scientist at Meta Platforms, Inc., Jing’s journey from academic research to industrial innovation highlights the transformative potential of integrating rigorous research methodologies with real-world applications.

Dr. Gao’s academic career began with her Ph.D. in Operations Research at the University of Minnesota, Twin Cities. As a teaching and research assistant, she immersed herself in the intricacies of machine learning, data analysis, and optimization. These formative years equipped her with a deep understanding of complex algorithms and data-driven decision-making processes. Jing’s role as a teaching assistant also honed her ability to communicate complex concepts clearly, a skill that has proven invaluable in her professional career.

Transitioning to Meta Platforms, Inc., Dr. Gao brought her robust academic foundation to the tech industry. At Meta, she excelled in optimizing Click to Message Ads, driving the iteration process of ads ranking models with datasets as large as 1.5 billion records per day. Her work involved exploring proposals, authoring features, and implementing new optimization algorithms to enhance model performance and resource efficiency. Through her work in model training and performance improvement, Dr. Gao enhances the efficiency of model development and deployment. This, in turn, aids small business owners and brings communities closer together, thereby contributing to economic growth. Dr. Gao’s ability to apply cutting-edge research to practical problems allowed her to improve ad scores and model stability significantly.

Dr. Gao’s work extends beyond the realm of commercial applications, significantly contributing to national interests. Her research on optimizing airline networks not only enhances operational efficiency and reduces costs for the aviation industry but also promotes environmental sustainability through reduced fuel consumption and emissions. Furthermore, her innovations in algorithm development support national infrastructure by improving air traffic management, ensuring safer and more efficient air travel. By aiding businesses through her work at Meta, Dr. Gao fosters economic growth and strengthens community ties, demonstrating a profound impact on both technological advancement and societal well-being. 

Her academic background not only provided a strong foundation in machine learning and optimization but also instilled a commitment to rigorous research and innovation. This dual focus enabled Jing to bridge the gap between theoretical research and its practical application, driving significant advancements in her role at Meta.

Dr.Gao’s foray into algorithm development began during her collaboration with Professor Ankur Mani on a data-oriented aircraft routing project. This project aimed to optimize aircraft path planning in dynamic environments, leveraging real-world datasets and mathematical modeling. The collaborative effort marked the beginning of Jing’s focus on algorithm development for airline networks, particularly under non-stationary conditions.

Key moments in her career include her significant contributions to the collaborative routing and sensing project in the National Airspace. Jing’s work involved simulating national airline systems using FlightAware datasets, formulating optimal paths as multi-armed bandit problems, and developing a novel bandit framework tailored to wind observations. By combining non-stationarity and spatial-temporal correlations, Jing’s algorithms achieved an average travel time reduction of 5% per flight. Her innovative approach, which integrated learning theory, Bayesian inference, and Gaussian kernels, addressed the challenge of real-time information scarcity and adaptive weather conditions.

Dr.Gao’s research has been recognized at numerous prestigious conferences, including the INFORMS Annual Meetings, where she presented her findings in 2019, 2020, and 2021. Her work was honored with an Honorable Mention in the INFORMS Aviation Application Section Student Paper Competition in 2020, underscoring the impact and relevance of her research in the field. 

Beyond her technical achievements, Jing has played a pivotal role in fostering academic camaraderie and professional development among doctoral students in operations research. As Vice President of the INFORMS Student Chapter at the University of Minnesota, Jing initiated tech talks, inviting speakers from both academia and industry to share their insights. Under her leadership, the student chapter was recognized as a winner of the 2021 and 2022 Student Chapter Annual Award, highlighting her commitment to community building and academic excellence.

 Dr. Gao has held positions as a session chair for the INFORMS Annual Meetings in 2020 and 2021 further demonstrating her leadership and organizational skills. Jing’s ability to bridge the gap between academic research and industry application has not only advanced her professional career but also contributed to the broader field of operations research.

Dr. Gao’s journey from academic research to industrial innovation is a testament to the transformative power of integrating rigorous research with practical application. Her work at Meta Platforms, Inc. and her contributions to algorithm development for airline networks exemplify the impact of bridging academia and industry. As a leader and innovator, Jing continues to drive advancements in machine learning, optimization, and data-driven decision-making, paving the way for future innovations in both academia and industry.

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Published by: Martin De Juan

(Ambassador)

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