David Lo

AI + SE Seminar Series (Oct 16, 2025. 9:30 am – 10:30 am EST).

Efficient and Green Code LLMs: Happier Software Engineers, Happier Planet

Many are excited about the potential of code Large Language Models (code LLMs). However, code LLMs are large, slow, and energy-hungry compared to traditional automated software engineering solutions, which raises usability and sustainability concerns. This is especially true when we want to deploy them in IDEs on local devices, which is often the preferred setting. This talk will highlight several strategies to improve the efficiency and energy consumption of code LLMs. It will also present a vision of what the future can be with efficient and green LLM and a call for action for more research in this direction to make both software engineers and our planet happier.

BIO

David Lo is the OUB Chair Professor of Computer Science and Director of the Information and Systems Cluster at the School of Computing and Information Systems, Singapore Management University. He leads the Software Analytics Research (SOAR) group. His research interest is in the intersection of software engineering, AI, and cybersecurity, encompassing socio-technical aspects and analysis of different kinds of software artifacts, with the goal of improving software quality and security and developer productivity. His work has been published in major and premier conferences and journals in the area of software engineering, AI, and cybersecurity attracting substantial interest from the community. He has won more than 20 international research and service awards including 9 ACM SIGSOFT IEEE TCSE Distinguished Paper Awards. He has received a number of international honors including ACM Fellow, IEEE Fellow, Fellow of Automated Software Engineering, and IEEE TCSE Distinguished Service Award.

For more details, please visit: http://www.mysmu.edu/faculty/davidlo/

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