Profile Picture of Adrián Moreno (@zetxek), working side by side with a colleague: sitting on a desk, while looking at a screen

I am a Research Fellow at the University of Leeds, working at the intersection of computer architecture and system optimization. I focus on (i) hardware-assisted memory safety, such as Capability Hardware Enhanced RISC Instructions (CHERI), and (ii) systematic optimization of large language models for training and inference. My research interests include cloud computing, high-performance cluster management, and middleware for scalable, reliable, and efficient AI systems.

I have served as a TPDS peer reviewer, Eurosys Shadow PC member, and Publicity Co-Chair for IEEE CISOSE JCC and etc.


I am a Technical Consultant for the AI Training Infrastructure at Kuaishou Technology.

I am Co-Founder of ACE3 AI LTD, a spin-out building a next-generation cloud platform for large AI models. Our platform provides a more efficient, cost-effective way to manage and accelerate AI workloads, combining an intuitive, user-centric interface with highly optimized execution and scheduling. It turns my Ph.D. research into practical infrastructure for modern AI applications.

About Me

News

💷 Nov/2025. Awarded further £40K non-diluted Seed funding from AI SuperConnector Programme.
☁️ Sep/2024. Awarded $25K Google Cloud funding support (as PI) for AISC project.
💷 Jul/2024. Awarded £20K non-diluted Seed funding (as PI) from AI SuperConnector Programme Cohort One.
💷 Aug/2024. Co-awarded £16K International Strategy Fund (as CoI) for Joint Research Centre.
💷 Apr/2024. Awarded £389K funding, (e.g., £150K EPSRC IAA, etc.) to transfer PhD research into a spin-out company ACE3 AI LTD.

Publications

AURANAV: Safety-Centric Navigation through Real-Time Familiarity and Social Awareness
2025 IEEE International Conference on Joint Cloud Computing (JCC)
Sweet or Sour CHERI: Performance Characterization of the Arm Morello Platform
2025 IEEE International Symposium on Workload Characterization (IISWC)
KAIR: A Statistical and Causal Approach to Pinpointing Stragglers in Distributed Model Training
2025 IEEE/ACM International Conference on Automated Software Engineering (ASE) (CCF A) (Industry Showcase)

Experience

My research philosophy focuses on the collaboration of the industry and solving practical problems. Through internships or industry-backed research during the study, I deepened my understanding of real-world applications and developed skills to connect theory with effective actionable solutions. From then on, I concentrated on front-line research with practical impact.

Education

2019 - 2023
University of Leeds, UK
Doctor of Philosophy (PhD) in Computer Science.
Research Areas: Advanced, system-level optimization techniques for large-scale AI and foundation models, e.g., parallelism strategies; as well as high-performance GPU cluster management, including scheduling, resource allocation, distributed system design, and scalable infrastructure operations.
Dissertation: Cost-Effective Acceleration Strategies for Large-Scale Model Training. (been successfully translated into a spin-out company ACE3 AI LTD.)

2015 - 2018
Beihang University, China
Master of Engineering in Computer Science and Technology.
Research Areas: Cloud computing architectures, virtualization technologies, advanced cluster management methodologies, and high-availability failover mechanisms.
Dissertation: Research and Implementation of a Distributed Scheduler for Heterogeneous Workloads. (adopted in Alibaba Cloud Platform, one of the global largest cloud platforms)

Contact

Email

X.Sun4 (at) leeds.ac.uk

Social Links

Address

3.25 Sir William Henry Bragg Building
University of Leeds
Woodhouse
Leeds
LS2 9JT
United Kingdom