Hualiang Li

Built and grew a data science team, overseeing annual strategic and budget planning. Developed and deployed various AI/ML models, optimizing them for performance and applying state-of-the-art computer vision, LLM, and generative AI models to enhance game content creation and user experience.

Partnered with Engineering and Operations teams to define optimal data science infrastructure, build ETL processes, and deploy machine learning models. Ensured high-quality project delivery within time constraints.

Built, led, and empowered data science teams to deliver products from concept to production. Collaborated with Engineering and Operations to establish optimal data science infrastructure and deploy machine learning models, applying computer vision to solve movie content business problems.

Led a team of data engineers, business analysts, and data scientists, managing seven concurrent projects using EMR and EHR data. Developed machine learning algorithms to extract insights from complex and imbalanced data sources.

Led and trained a data scientist team for USAA and Boeing. Won a USAA proof of concept competition to address declining auto insurance sales against multiple consulting companies.

Performed research in statistical machine learning, signal processing, and complex optimization theory. Contributed to academic advancements in these fields.

Activities and societies: Recipient of 2010 IEEE Signal Processing Society Best Paper Award for the paper “Stability analysis and Newton algorithm for complex maximum likelihood ICA using Wirtinger calculus.”

Performed research in statistical machine learning, signal processing, and complex optimization theory. Awarded the IEEE Signal Processing Society Best Paper Award in 2010 for contributions to the field.

Studied Industrial Automation Control, gaining foundational knowledge in systems and processes. This degree provided a strong basis for future work in data science and machine learning.