About
Jing Gao is an Associate Professor at the Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana. She serves as the Director of Graduate Admissions and focuses on data mining, machine learning, and their applications in healthcare, biology, and societal systems.
Research Interests
- Data veracity analysis and multi-source data integration
- Knowledge graphs and large language models
- Fairness, interpretability, and efficiency in AI
- Federated learning and transfer learning
- Applications in healthcare, education, and criminal justice
Recent Article Trends
Her work emphasizes large language models (LLMs) with innovations in knowledge editing, federated learning, and fairness-aware systems. Key themes include:
- Improving LLM efficiency via sparse adaptation and quantization
- Advancing privacy-preserving federated learning architectures
- Developing fairness-aware algorithms through counterfactual reasoning
- Integrating knowledge graphs for factuality validation
- Optimizing multi-agent reasoning and self-reflective confidence
Technical Areas
Her research spans computer engineering domains including:
- Signal & Image Processing
- Communications & Networking
- AI/ML Model Efficiency
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