Welcome to My New Research Website
I've launched a new research website to share my work in multi-agent LLM orchestration, cloud computing, and computer vision.
Professional Summary
Sen He is an Assistant Professor in the Department of Electrical and Computer Engineering
at the University of Arizona. His research spans LLM4SE, performance engineering, computer vision, and human-computer interaction.
Education
PhD in Computer Science
University of Texas at San Antonio
Research Interests
LLM for Software Engineering
Performance Engineering
Computer Vision
Human-computer Interaction
Awards
2025
Best Paper Award, International Congress on Intelligent & Service-Oriented Systems Engineering
Tucson, USA2025
Award for Excellence at the Student Interface, Department of Systems and Industrial Engineering
Tucson, USA2020
Outstanding Research Awards, Department of Computer Science, UTSA
San Antonio, USA2019
ACM SIGSOFT Distinguished Paper Award, ACM SIGSOFT
Tallinn, Estonia🔬 Research Overview
My research lies at the intersection of AI for Software Engineering, Computer Vision, and Human-Computer Interaction. I am particularly interested in how large language models can be orchestrated as multi-agent systems to solve complex software engineering tasks — from automated code generation and debugging to performance optimization.
My current research thrusts include:
- Multi-Agent LLM Orchestration: Designing and evaluating collaborative multi-agent architectures that leverage frontier LLMs for software engineering tasks such as code generation, debugging, and refinement (see PerfOrch).
- Software Performance Engineering: Developing methodologies for performance testing in cloud environments, including serverless platforms and edge/fog computing systems.
- AI-Driven Software Testing: Harnessing LLMs and AI techniques for automated testing of complex software systems, including VR applications and cloud-native architectures.
- Computer Vision: Applied work in medical image segmentation, brain connectivity analysis, and 3D vision.
Selected Journal Papers
DynamicLip: Shape-Independent Continuous Authentication via Lip Articulator Dynamics.
IEEE Transactions on Mobile Computing, 25(3): 4063-4076,
2026.
Harnessing large language models for virtual reality exploration testing: a case study.
Automated Software Engineering, 33(1): 7,
2026.
Microservice logs analysis employing AI: A systematic literature review.
Journal of Systems and Software, 236: 112786,
2026.
Performance analysis of AI-generated code: A case study of Copilot, Copilot Chat, CodeLlaMa, and DeepSeek-Coder models.
Empirical Software Engineering, 31(3): 62,
2026.
Unveiling code clone patterns in open source VR software: an empirical study.
Automated Software Engineering, 32(2): 72,
2025.
Selected Conference Papers
Assessing the performance of AI-generated code: A case study on GitHub Copilot.
IEEE 35th International Symposium on Software Reliability Engineering (ISSRE), 216-227, 2024,
2024.
Improving Resource and Energy Efficiency for Cloud 3D through Excessive Rendering Reduction.
European Conference on Computer Systems (EuroSys), 2024,
2024.
A Cloud 3D Dataset and Application-Specific Learned Image Compression in Cloud 3D.
European Conference on Computer Vision (ECCV), 2022,
2022.
Performance Testing for Cloud Computing with Dependent Data Bootstrapping.
The 36th IEEE/ACM International Conference on Automated Software Engineering (ASE), 2021,
2021.
A benchmarking framework for interactive 3D applications in the cloud.
53rd Annual IEEE/ACM International Symposium on Microarchitecture (MICRO), 881-894, 2020,
2020.
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