Lingjia Tang

Lingjia Tang is an Assistant Professor in Computer Science with expertise in artificial intelligence, machine learning, big data, and no-code automation. Her research focuses on developing machine learning algorithms for medical data analysis and advancing no-code automation tools to democratize technology access.

Research Interests

• Artificial Intelligence & Machine Learning
• Big Data Analytics & Graph-Based Retrieval
• No-Code Automation & User-Centric Systems
• Data Quality & Ethical AI Considerations

Scientific Contributions

With over 20 publications in prestigious journals, Dr. Tang's recent work explores:

• Graph-based retrieval frameworks (GraphRunner, TOBUGraph)
• LLM calibration and evaluation (SLMEval)
• Memory subsystem optimization in datacenters
• Meaning-typed programming paradigms
• Multi-agent conversational AI systems

Awards

• 2023 Award for contribution to machine learning technologies

Teaching

Dr. Tang teaches courses in artificial intelligence, algorithms, and computational theory with a dynamic interactive approach.

Current Projects

• Machine learning algorithms for medical diagnosis
• No-code automation tools for non-technical users