Fei (Travis) Dai

About Me

Hello and welcome! I am Fei (Travis) Dai, a Senior Lecturer in Computing at the Eastern Institute of Technology (EIT), New Zealand. I received my PhD in Computer Science from the University of Otago.

My research focuses on optical interconnect systems, distributed AI training, collective communication, and parallel and distributed systems. I am particularly interested in communication-efficient system design for deep learning, optical and photonic approaches to scalable computing, and system co-design across algorithms, architectures, and interconnects.

I also work in computing education, with current interests in theory-to-practice barriers, reflective learning, and transnational computing education in cross-cultural contexts, particularly between China and New Zealand.

In teaching, I value hands-on, learner-centred learning and aim to connect technical concepts with authentic applications. I welcome opportunities for collaboration in optical and AI systems, distributed training, collective communication, system co-design, and computing education.

Research Interests

• Optical Interconnect Systems
• Distributed AI Training
• Collective Communication
• AI Systems and System Co-design
• Parallel and Distributed Systems
• Computing Education

News

• [2026] Promoted to Senior Lecturer in Computing at the Eastern Institute of Technology.
• [2025] Our paper on theory–practice barriers in Sino–New Zealand undergraduate computing education was published at CSEDU 2025.
• [2025] Our paper, State of the Art in Parallel and Distributed Systems: Emerging Trends and Challenges, was published in Electronics.
• [2024] Our paper on the all-gather operation in optical interconnect systems was published in the IEEE Open Journal of the Communications Society (OJ-COMS).
• [2023] Our paper on distributed DNN training performance comparison was accepted to ICA3PP 2023.
• [2023] Our paper on the all-reduce algorithm in optical interconnect systems was accepted to ICPP 2023.
• [2023] Our paper on the all-gather operation in optical interconnect systems was accepted to IEEE ICC 2023.
• [2023] Our paper on distributed DNN training in optical interconnect systems was accepted to PPoPP 2023.
• [2022] Our paper on multi-layer perceptron training performance on electrical and optical network-on-chips was published in The Journal of Supercomputing.

Selected Publications

Academic Services (Selected)

Editorial

• Guest Editor, Electronics (MDPI) — Special Issue: Emerging Distributed/Parallel Computing Systems

Conference Service

• Artifact Evaluation Committee Member, ACM EuroSys — 2025, 2026
• Technical Program Committee (TPC) Member, AICSConf (Artificial Intelligence and Complex Systems Conference) — 2021
• Technical Program Committee (TPC) Member, ICNCIS (International Conference on Network Communication and Information Security) — 2023–Present
• Technical Program Committee (TPC) Member, CCIOT (International Conference on Cloud Computing and Internet of Things) — 2024–Present
• Reviewer / Program Committee Member, PDCAT (Parallel and Distributed Computing, Applications and Technologies) — 2020–2021
• Reviewer / Program Committee Member, PAAP (Parallel Architectures, Algorithms, and Programming) — 2019
• Reviewer / Program Committee Member, PMAM (Programming Models and Applications for Multicores and Manycores) — 2023
• Delegate Session/Workshop Chair, PMAM 2023 (co-located with PPoPP), Montreal, Canada
• Session Chair, CSEDU 2025 (International Conference on Computer Supported Education)
• Program Committee Member, the 3rd International Workshop on Artificial Intelligence Empowered Communication and Networking at ICCCN 2026

Journal Reviewer

• IEEE journals: IEEE Transactions on Parallel and Distributed Systems (TPDS); IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD); IEEE Transactions on Computers; IEEE Access
• MDPI journals: Electronics; Network; Telecom; Quantum Beam Science
• Other journals: The Journal of Supercomputing; Future Generation Computer Systems; Microprocessors and Microsystems; PLOS ONE

Teaching

I teach in the areas of:

• Electronics and Internet of Things
• Automation and Embedded Systems

My teaching emphasises hands-on learning, authentic assessment, and connecting theory with practice.

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