Dr. @Yitong Yang  is a Research Assistant Professor at Hong Kong University of Science and Technology (HKUST), China. He is an Editorial Board Member for Scientific Reports since 2024 and Guest Editor for the Smart Grids Collection. Dr. Shang’s research focuses on the nexus of Transportation, Energy, and Artificial Intelligence, particularly EV charging demand prediction, Vehicle-to-Grid (V2G) scheduling, and federated learning-based secure energy management. Dr. Shang is passionate about bridging fundamental AI methodologies and real-world sustainable energy challenges through interdisciplinary collaboration.

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In this interview, we asked Dr. Yitong Shang to talk to us about his work as an Editor at Scientific Reports. Read on to find out more.

What do you like most about being an Editorial Board Member for Scientific Reports?

What I appreciate most is, on the one hand, Scientific Reports' unwavering commitment to evaluating scientific validity over perceived novelty or expected impact. On the other hand, the open-access model ensures our collective efforts reach global practitioners and policymakers, thereby maximizing scientific impact. It is deeply rewarding to contribute to a platform that prioritizes integrity and accessibility simultaneously.

We know that finding reviewers is one of the hardest parts of an editorial role. Do you have any tricks on finding reviewers? 

First, my primary strategy is to mine the manuscript's own reference list, as researchers already engaging with the topic are often ideal reviewers. Second, for rapidly evolving areas like AI-energy integration, early-career researchers are often enthusiastic, rigorous, and up to date. Third, maintaining a personal reviewer database built through previous collaborations and conference interactions is invaluable. Last but not least, diversifying geographically and institutionally also improves review quality and reduces unconscious bias in the evaluation process.

If you were to give a piece of advice to other Editors, what would that be?

First, our role is to safeguard methodological soundness, not to dictate research directions. Second, always provide constructive, specific editorial feedback that genuinely helps authors improve, regardless of the final decision. Finally, stay intellectually curious beyond your specialty; the best editorial judgments come from editors who appreciate the broader scientific landscape and can recognize rigor and contribution across disciplinary boundaries.

How important is reproducibility in research? As an Editor, how do you help authors report reproducible results?

Reproducibility is foundational to trustworthy science, without it, even compelling findings lose credibility and practical value. As an Editor, I consistently encourage authors to provide comprehensive methodological detail, openly share datasets and code, and clearly document experimental conditions. For AI and machine learning papers, I specifically request that authors report model architectures, hyperparameters, and random seeds. I also recommend adherence to discipline-specific reporting standards.

What are the key things journals should do to ensure scientific rigor?

Mandatory data sharing, code availability, and transparent statistical reporting requirements are essential structural safeguards. Systematic checks for plagiarism, image manipulation, and statistical irregularities should be standard. Pre-registration should be encouraged where applicable.

What are the biggest challenges that you see for the future of research and research dissemination?

Key challenges include information overload, with thousands of papers published daily, discoverability and quality filtering are increasingly critical. The proliferation of predatory journals erodes public trust in science. AI-generated content introduces new verification complexities. Research-to-practice translation remains frustratingly slow, particularly in applied domains like sustainable energy. Global inequity in research funding and publishing costs limits contributions from developing regions despite open-access progress.

What interested you about becoming a Guest Editor? What is your Collection focused on?

I became Guest Editor for the "Smart Grid" collection because smart grid technology sits at the precise intersection of my research - AI, energy systems, and sustainable transportation electrification. The collection focuses on innovative smart grid solutions including demand response, distributed energy resources, AI-driven grid optimization, and EV-grid integration. I was motivated by the opportunity to curate research, bridging academic innovation, and practical implementation, while fostering a global research community. Scientific Reports' inclusive, validity-focused ethos made it the ideal platform to bring rigorous, impactful smart grid research to the broadest possible audience. The collection is accessible at: https://www.nature.com/collections/ebddggabji

Dr. Yitong Shang’s lab webpage: https://ce.hkust.edu.hk/people/yitong-shang-shangyitong