Honored to receive the Best Paper Award at IEEE Cloud Summit 2025 for the KubeLLM research project.
Palden Lama
Associate Professor, Department of Computer Science, The University of Texas at San Antonio
I build intelligent, resilient computing systems at the intersection of AI, cloud and edge computing, and cyber security. My research advances AI for Systems and Systems for AI: using learning to automate complex infrastructure while designing middleware that makes AI practical in constrained environments.
Latest updates
News
Our paper "LLM-Based Multi-Agent Framework For Troubleshooting Distributed Systems" was accepted at IEEE Cloud Summit 2025.
Received NIH funding for "Expanding Genomic Data Science Access via Cloud Computing and Dynamic Learning Modules."
Background
Academic training and systems experience
Dr. Lama received the BTech degree in electronics and communication engineering from the Indian Institute of Technology, Roorkee, in 2003, and the PhD degree in Computer Science from the University of Colorado, Colorado Springs, in 2013.
Before joining academia, he gained four years of professional experience in the software industry. During his PhD study, he also worked as a research aide at Argonne National Laboratory.
Research
AI, cloud, edge, and secure autonomous systems
The rapid growth of Internet services requires systems that are scalable, secure, reliable, efficient, and increasingly self-adaptive. My group develops systems and middleware solutions that improve performance, energy efficiency, and security across distributed computing environments.
Cloud and Edge Computing
Resource management, performance guarantees, serverless computing, stream processing, and middleware for large-scale distributed services.
Artificial Intelligence
AI-driven automation for complex systems, multi-agent troubleshooting, federated learning, and efficient DNN deployment at the edge.
Cyber Security
Cyber risk detection, ransomware detection, DDoS defense, secure federated learning, and resilient computing curricula.
AI and Cloud Systems Lab
Research group focused on intelligent cloud and edge systems
The AI and Cloud Systems Lab explores complementary directions: AI for Systems, using artificial intelligence to automate and optimize infrastructure operations; and Systems for AI, designing middleware and system software for scalable, low-latency, energy-efficient AI deployment.
Explore lab people and projectsCybersecurity in Computing Curricula
Software project-based learning focused on identity and access management.
Secure Federated Learning at the Tactical Edge
Robust techniques to detect malicious behavior in federated learning.
Expanding Genomic Data Science Access via Cloud Computing and Dynamic Learning Modules
Cloud-enabled genomic data science access and dynamic learning modules.
Containerized Microservices in the Cloud
Performance models and resource management for cloud microservices.
Publications
Recent and selected work
LLM-Based Multi-Agent Framework For Troubleshooting Distributed Systems
M. De Jesus, P. Sylvester, W. Clifford, A. Perez and P. Lama. Best Paper Award.
Where to Split? A Pareto-Front Analysis of DNN Partitioning for Edge Inference
A. Masud, N. Foley, P.D. Rajarajan and P. Lama.
Data-Priority Aware Fair Task Scheduling for Stream Processing at the Edge
F. Akram, P. Kang, P. Lama and S. Khan. Best Paper Award.
Teaching
Courses
- CS 4843/5573 Cloud Computing
- CS 4593/5463 Cloud and Big Data
- CS 5523 Operating Systems
- CS 3423 Systems Programming
- CS 4593 AT: Pathogenic OutBreak Investigation
Service
Professional activities
- Technical Program Committee Chair: IEEE Cloud Summit 2024
- Track Co-Chair: "Grid, Cloud, Internet and Peer-to-peer Computing and Communication (GCIP)" track, IEEE International Conference on Computer Communications and Networks (ICCCN) 2015
- Review Board Member: IEEE Transactions on Parallel and Distributed Systems (TPDS), 2019 - 2021
- Student Travel Award Chair: IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), 2015
- Invited Panel Member: John R. Evans Leaders Fund (JELF), Canada Foundation for Innovation, 2014
- Newsletter Editor: IEEE Technical Committee of Distributed Processing, 2020 - 2024
Awards
Honors
- Best Paper Award, IEEE Cloud Summit 2025
- Best Paper Awards, IEEE Cloud Summit 2024
- Winner, xTechHBCU 2022 competition sponsored by the US Army
- Best Paper Nomination, IEEE MASCOTS 2017
- Best Paper Award, IEEE CLOUD 2017
- NSF Travel Grant Support for IEEE/ACM CCGrid 2015 Conference