Distributed AI training
I analyse how data, tensor and pipeline parallel training move information between computing nodes, including communication in large language models.
PROFILE
Research at the intersection of AI systems and interconnects
Dr Fei (Travis) Dai is a Senior Lecturer in Computing at the Eastern Institute of Technology. He received his PhD in Computer Science from the University of Otago.
His research interests include distributed AI training, collective communication, optical and electronic interconnects, and the co-design of algorithms and computing systems. He also studies performance and energy use in large-scale AI workloads.
His broader interests include embedded and edge AI, Internet of Things systems, automation, and generative AI in computing education. He also works on authentic and AI-aware assessment and helping students connect theory with practical work. He welcomes research collaboration and postgraduate supervision enquiries.
AI SYSTEMS · OPTICAL INTERCONNECTS
Fei (Travis) Dai
Efficient systems and interconnects for large-scale AI
I study how AI models communicate across computing systems. My work develops collective communication methods and evaluates optical and electronic interconnects for faster, more energy-efficient training.
Senior Lecturer in Computing · EIT, New Zealand
CURRENT PROJECT · 2026
Communication Analysis of LLM Training for Optical Interconnect Co-design
EIT internal research fundRESEARCH
Communication is a major cost in AI training.
My research focuses on the algorithms and networks that move data during distributed training.
Collective communication
I design and evaluate all-reduce, all-gather and related operations used to coordinate large-scale training.
Interconnect co-design
I study how communication algorithms and optical or electronic networks can be designed together to reduce training time and energy use.
SELECTED WORK
Representative publications
A short selection from my work on distributed training and optical interconnects.
IEEE Open Journal of the Communications Society · 2024
Efficient Algorithm for All-Gather Operation in Optical Interconnect Systems
An all-gather method designed around the communication properties of optical interconnects.
International Conference on Parallel Processing · 2023
WRHT: Efficient All-Reduce for Distributed DNN Training in Optical Interconnect Systems
An optical-aware all-reduce method for distributed neural-network training.
The Journal of Supercomputing · 2023
Comparing the Performance of Multi-Layer Perceptron Training on Electrical and Optical Network-on-Chips
A performance and energy study of neural-network training on electrical and optical on-chip networks.
Electronics · 2025
State of the Art in Parallel and Distributed Systems: Emerging Trends and Challenges
A broader review of important developments and open challenges in parallel and distributed computing.
AI-Enabled Intelligent Embedded Architectures for Edge and Real-Time Systems
This Special Issue brings together practical research on embedded AI, edge intelligence and real-time systems. We welcome original research and review articles that connect AI methods with efficient system design.
- Embedded and edge AI
- AI accelerators
- Hardware–software co-design
- Real-time AI systems
- Energy-efficient architectures
TEACHING
Learning through clear explanations and practical work
My teaching connects computing concepts with the systems students design, build and evaluate.
Current areas
Electronics and Internet of Things
Automation and Embedded Systems
I use hands-on tasks and step-by-step guidance to help students move from core ideas to working systems.
My assessment design is authentic and AI-aware: students use appropriate tools while showing that they understand their decisions and learning.
ACADEMIC SERVICE
Selected editorial, conference and reviewing roles
Editorial
- Lead Guest Editor, Electronics Special Issue on AI-enabled intelligent embedded architectures
- Guest Editor, Electronics Special Issue on emerging distributed and parallel computing systems
Conferences
- Artifact Evaluation Committee, ACM EuroSys 2025 and 2026
- Program Committee, ICCCN 2026 workshop on AI-empowered communication and networking
- Session Chair, CSEDU 2025
- Workshop and Session Chair, PMAM 2023
Reviewing
Reviewer for IEEE TPDS, IEEE Transactions on Computers, IEEE TCAD, Future Generation Computer Systems, The Journal of Supercomputing and PLOS ONE.
GLOBAL REACH
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