Short Bio

Wenlu Wang is an associate professor in the Department of Computing Sciences at Texas A&M University Corpus Christi. She received her Ph.D. degree from the Department of Computer Science and Software Engineering at Auburn University in 2020.

About me

I am interested in transferring artificial intelligence (AI) to real-world applications, particularly in the realm of AI for Science. Specifically, I work on the following subjects:

1. How to convert a scientific problem into a format that AI can understand?
   • Can LLMs understand chemical language? cMolGPT
   • How can AI be leveraged to address physics-based real-world problems, for example in hydraulics? AquaSentinel
   • How to use AI for more accurate gemonic selection?
     
2. How to empower open-source LLMs?
   • How can we enable private, efficient LLM deployment on low-resource hardware? TranSQL+
     
3. How to “deploy” AI to address real-world challenges?
   • Stereo-based aquatic tracking AquaSense
   • AI-Powered Urban Wastewater Management Systems in Corpus Christi
     

Research Interests

AI4Science.

News

• [07/2026] Our spatial entropy-based graph unlearning paper has been accepted by SDM 2026! Congratulations to Qiming, and many thanks to our collaborators!
• [05/2026] Our AI for power grid project has been selected for funding by TAMU Research Excellence Fund. Many thanks to our collaborators!
• [01/2026] Our prototype for AI-enabled urban wastewater systems in Corpus Christi has been accepted to AAAI 2026. Thanks to our collaborators!
• [08/2025] Our DB4AI - databases for AI project is accepted by SIGMOD 2026. Thanks to our collaborators!
• [07/2025] Our AI for drug discovery project will be funded by our university’s research enhancement grant.
• [09/2024] Qiming’s GNN work is accepted by ACM SIGSPATIAL SRC. Congratulations Qiming!
• [07/2024] Our Benchmarking Toolkit for the Cost-Effectiveness of LLM Pipelines is online
• [05/2024] Our brain MRI project is accepted by MICCAI. Thanks to our collaborators!
• [05/2024] Our phenotyping project is accepted by Evolutionary Applications (IF 4.1). Thanks to our collaborators!
• [09/2023] Our project working on equitable healthcare is selected by NIH. Thanks to NIH!
• [08/2023] Our project working on interdisciplinary research is funded by NSF. Thanks to NSF!
• [05/2023] Check out our collaboration with Biogen - CMolGPT A Conditional Generative Pre-Trained Transformer for Target-Specific De Novo Molecular Generation. (Code).