Exciting news! Our papers, "CARE: Comprehensive Artificial Intelligence Techniques for Reliable Autism Evaluation in Pediatric Care," for which I am a first author, and "Beginner-Friendly Review of Research on R-Based Energy Forecasting: Insights from Text Mining," for which I am a co-corresponding author, have been published in Computers, Materials & Continua and Electronics, respectively. We would also like to extend our deepest appreciation to the two journals that kindly granted us APC waivers, thereby allowing us to publish these works without charge.

As the scope of my research continues to evolve—embracing themes of sustainability, urban resilience, and environmentally responsible AI—the Machine Learning for Industrial Applications (MLIA) Lab has taken on a new identity.

We are now SEED Lab: Sustainable Engineering & Environment-driven Data Laboratory. This new name reflects our deepening commitment to building data-driven solutions for a more sustainable and intelligent future.

Exciting news! Our papers, "Deep Learning-Based Natural Language Processing Model and Optical Character Recognition for Detection of Online Grooming on Social Networking Services," for which I am a co-corresponding author, and "Vision-based approach to knee osteoarthritis and Parkinson’s disease detection utilizing human gait patterns," for which I am a co-first author, have been published in Computer Modeling in Engineering & Sciences and PeerJ Computer Science, respectively. These publications are important milestones in our ongoing research efforts, and I would like to thank Prof. Dr. Seungmin Rho for his invaluable collaboration on these studies!

I have been invited to serve as a Guest Editor for two Special Issues with Tech Science Press journals:

CMES – Computer Modeling in Engineering & Sciences

Special Issue: Deep Learning for Energy Systems

CMC – Computers, Materials & Continua

Special Issue: Bridging the Gap: AutoML and Explainable AI for Industrial and Healthcare Innovations

We are currently welcoming submissions—feel free to reach out if you are interested in contributing!

Over the past two and a half years, I have had the privilege of being part of Soonchunhyang University, where I built invaluable memories, collaborated with brilliant minds, and contributed to meaningful research. This journey has been an incredible period of growth, learning, and innovation.

Now, I am thrilled to embark on a new chapter as an Assistant Professor at Duksung Women’s University—my spouse’s alma mater. This transition holds special significance for me, and I remain committed to driving impactful research and education and am excited for the opportunities ahead.

✨ To my colleagues, students, and collaborators—thank you for your unwavering support and inspiration.

Exciting news from our research efforts! Two notable papers have been published, marking significant milestones in our academic journey. Our paper "Differential Impacts of Environmental, Social, and Governance News Sentiment on Corporate Financial Performance in the Global Market" was published as a Feature Paper in Electronics. This collaborative effort between the MLIA Laboratory and industry authors marks a significant advancement in natural language processing and pushes the boundaries of industrial applications in ESG analysis. In addition, our study "Advancing Ensemble Learning Techniques for Residential Building Electricity Consumption Forecasting" was published in PLOS ONE, demonstrating the potential of explicable AI in energy forecasting. Congratulations to all of our collaborators on these remarkable achievements that are driving innovation and real-world impact!

Exciting news! Our paper "Reliable Autism Spectrum Disorder Diagnosis for Pediatrics Using Machine Learning and Explainable AI" has been published in Diagnostics. This collaborative work, involving members of the MLIA Laboratory and esteemed colleagues from various departments at Soonchunhyang University, represents a significant advancement in the application of machine learning and explainable AI for reliable pediatric ASD diagnosis. This publication adds to our growing list of accomplishments and underscores our commitment to high-impact medical research. Congratulations to all authors and contributors on this important milestone!

Exciting news! Our paper "Advanced R-GAN: Generating anomaly data for improved detection in imbalanced datasets using regularized generative adversarial networks" has been published in the Alexandria Engineering Journal. Notably, this journal is ranked within the top 10% of its JCR category, highlighting its exceptional academic reputation and affirming the high quality and impact of our research. In addition, six KCI-listed journal articles with MLIA Laboratory students as first authors have been published, bringing our total to seven valuable publications and marking significant milestones in our ongoing research efforts.

Exciting news! Our papers, "Advancing Autoencoder Architectures for Enhanced Anomaly Detection in Multivariate Industrial Time Series," for which I am a co-corresponding author, and "Object Detection under the Lens of Privacy: A Critical Survey of Methods, Challenges, and Future Directions," for which I am a co-first author, have been published in Computers, Materials & Continua and ICT Express, respectively. These publications are important milestones in our ongoing research efforts, and I would like to thank Prof. Dr. Seungmin Rho for his invaluable collaboration on these studies!

On October 8, 2024, my website, Prof. Dr. Jihoon Moon, has underwent a significant update.

I look forward to sharing more of my latest news and insights with you in the future.

Thank you for your continued interest and support.