By: Noah Mitchell

In the rapidly evolving landscape of artificial intelligence, few researchers have managed to transcend the boundaries of multiple industries as effectively as Jiarui Rao. As a trailblazer in applying Large Language Models (LLMs), Rao explores innovative work in finance, e-commerce, and education, showcasing how AI can address real-world challenges.

Rao’s interdisciplinary expertise and approach to AI have made her a respected figure in both academic and commercial sectors. Her work with LLMs across different industries highlights AI’s increasing impact on traditional practices.

Transforming Financial Forecasting

Rao’s approach to financial market prediction offers a fresh perspective. She developed a hybrid intelligent decision-making model that integrates economic policy uncertainty (EPU) indicators with historical data, using LLMs to analyze sentiment signals in policy texts. This framework, which employs a PSO-SVR (Particle Swarm Optimization – Support Vector Regression) structure, has improved prediction accuracy compared to traditional models like ARIMA. Rao’s perspective on policy texts as potential amplifiers of market sentiment offers a new direction for exploring alpha returns in the financial sector.

Her work in financial forecasting challenges traditional methodologies and paves the way for more resilient, adaptable models that can account for the complexities of global financial markets. Rao’s model has shown promise in volatile market conditions, offering an edge in risk management and strategy.

Transforming E-commerce Insights

Rao’s work in e-commerce is equally transformative. In a study with Tencent, she led the development of a three-dimensional analysis model beyond traditional NLP limitations. By creating an emotion-rating mapping network based on BERT-LSTM, Rao’s team uncovered the complex, non-linear relationship between customer textual sentiment and star ratings. This model analyzes user feedback and tracks merchants’ response efficiency to negative reviews through temporal evolution graphs, quantifying a “crisis response index.” The practical application of this research has already shown remarkable results, with a 17.6% increase in conversion rates for the pilot company “Sunshine.”

Moreover, the real-time feedback mechanism developed in this study allows companies to dynamically adjust their marketing and customer service strategies, improving customer satisfaction and overall brand reputation.

Pioneering Educational Equity

In education, Rao has been working on improving accessibility and personalization. Her recent project, “RAMO: Retrieval-Augmented Generation for Enhancing MOOCs Recommendations,” explores a system that uses LLMs to address the “cold start” problem in course recommendation systems. RAMO applies RAG (Retrieval-Augmented Generation) to offer personalized course suggestions via conversational interfaces by incorporating a dynamic knowledge graph with extensive course metadata. This approach has improved recommendation accuracy, particularly in areas with less representation, such as non-STEM disciplines.

The success of RAMO has extended beyond MOOCs, with potential applications in personalized learning paths and adaptive teaching tools, especially for non-traditional learners. Rao’s innovations are setting the stage for AI-driven customized education on a global scale.

A Vision for the Future

Rao’s vision extends beyond these achievements. She is developing a domain-adaptive fine-tuning framework called DART, aimed at unlocking the next generation of industry-specific AI applications. Rao has suggested the potential for LLM-based sentiment factors to play a significant role in quantitative trading strategies in the coming years. She also envisions the development of low-resource RAG-Lite systems that could help improve access to dynamic knowledge resources in remote areas, contributing to efforts to bridge the educational divide.

Rao also anticipates the evolution of LLMs to address bias and fairness issues, helping their equitable application across all sectors, from healthcare to social services. This forward-thinking approach positions her as a leader in AI ethics, guiding the responsible development of next-generation technologies.

Conclusion

From Silicon Valley to the digital classrooms of the world, Jiarui Rao’s work exemplifies the power of AI to drive meaningful change. Her ability to tailor LLMs to address industry-specific challenges enhances productivity and fosters greater equity and accessibility. As Rao continues to push the boundaries of what AI can achieve, her legacy will undoubtedly inspire a new generation of innovators to explore the intersection of technology and human potential.

Disclaimer: The content is for informational purposes only and should not be construed as professional advice.

Published by Zane L.