[2025/01/29] Research Award: 2025 IADRC REC Scholar
Dr. Taeho Jo has been selected as the 2025 Indiana Alzheimer's Disease Research Center (IADRC) Research Education Component (REC) Scholar.
[2025/01/27] Research Intern Joins
Meghana Vodnala joined the lab as a research intern. With a Bachelor's degree in Dental Surgery and current pursuit of a Master's in Health Informatics, she will focus on studying data analytics and artificial intelligence.
[2025/01/09] Editorial Appointment: Associate Editor of Genomics & Informatics
Dr. Jo has been appointed as Associate Editor of Genomics & Informatics, a scientific journal published by Springer Nature Group, effective January 9, 2025. In this role, he will contribute to the editorial oversight of research publications in genomics and informatics.
"Linkage Disequilibrium-Informed Deep Learning Framework for Alzheimer's Disease" This study introduces Deep-Block, a novel multi-stage deep learning framework that incorporates biological knowledge for analyzing large-scale genomic data in Alzheimer's disease. Applied to the Alzheimer's Disease Sequencing Project (ADSP) dataset of 7,416 participants, the framework successfully identif...
[2024/11/30] Best Poster Award at Asia-Pacific Psychiatry and Aging Conference
Received the Best Poster Award for the research "Identifying Alzheimer's-Related Genetic Regions Using Deep Learning on Whole-Genome Data" at the Asia-Pacific Psychiatry and Aging Conference.
[2024/11/26] EBS-TV Special Lecture: The Significance of Deep Learning's Nobel Prize
Dr. Jo delivered his second lecture on EBS TV, Korea's leading public educational broadcaster. The presentation focused on the significance of 2024's Nobel Prize and current applications of AI in research, making complex scientific developments accessible to the general public.
[2024/11/25] Invited Lecture: Innovative Alzheimer's Prediction Using Deep Learning
Dr. Jo presented a hybrid lecture at Hallym University School of Medicine and Hallym Medical Center in Chuncheon, Korea. His presentation, "The Impact of Deep Learning's 2024 Nobel Prize: Innovations in Alzheimer's Prediction Through Multi-omics Analysis," examined the significance of AI's Nobel Prize recognition and showcased new developments using deep learning in Alzheimer's rese...
[2024/11/19] Invited Talk: IUSM Imaging Sciences Seminar Series
Dr. Jo delivered an invited seminar at the Imaging Sciences Research Seminar Series. His presentation, "Why Deep Learning Deserved the 2024 Nobel Prize - Transforming Alzheimer's Research and Beyond," was hosted by the Indiana University School of Medicine Department of Radiology and Imaging Sciences on November 19, 2024.
[2024/10/30] Invited Talk: Transformers for Multi-modal Biomarker Analysis in Alzheimer's Research
Dr. Jo presented his research on multi-modal biomarker & genomic analysis using SWAT transformers at IUSM Conference - Neurosurgery Morning Grand Rounds, Indianapolis, Indiana
[2024/10/15] New Postdoctoral Member Joins
Dr. Eun Hye Lee Joins Our Lab as a Postdoctoral Researcher. Dr. Lee, who earned her BS in Pharmacy, MD, and PhD from the same university and completed her Neurology Fellowship at a medical center, has joined our lab. She will focus on research involving AI applications in genomics and biological pathway analysis.
[2024/07/08] Invited Lecture: From Deep Learning Fundamentals to Advanced Transformer Architectures
Dr. Jo was invited as a featured AI instructor at FastCampus, Korea's largest and premier tech education platform with over 70,000 active learners in paid courses. He delivered an in-depth curriculum covering the fundamentals of deep learning through advanced architectures including NN, MLP, CNN, RNN, GAN, Autoencoders and Transformer (Attention mechanisms, BERT, and GPT).
Dr. Jo presented a research poster titled "Applying Deep Learning to Uncover Genetic Insights in Alzheimer's Disease: Analysis of 7,416 Whole Genome Sequences" at The 13th International Conference of Clinical Laboratory Automation in 2024. The presentation received the Silver Best Award for its innovative analysis of whole genome sequences using deep learning approaches. CopyRetry
Dr. Jo delivered a 6-hour intensive lecture at the International Healthcare Symposium, hosted by Ajou University Medical Center and the Graduate School of AI Convergence Innovation, Korea
[2023/12/14] Invited Talk: Seoul National University Veterinary Sciences Seminar Series
Dr. Jo delivered an invited lecture at Seoul National University's College of Veterinary Medicine. His presentation covered the trends and research implications of deep learning/machine learning applications in Alzheimer's disease research, with a special focus on hyperparameter optimization techniques.
[2023/10/23] Invited Lecture at 2023 AIAI Healthcare Symposium
Dr. Jo delivered a comprehensive lecture "From Perceptron to Chat-GPT" at the 2023 AIAI Healthcare Symposium, jointly hosted by Ajou University Medical Center and Graduate School of AI Convergence Innovation. The presentation traced the evolution of deep learning from early neural networks to modern language models, focusing on their applications in healthcare.
Dr. Jo and colleagues published a research paper titled "Circular-SWAT for Deep Learning Based Diagnostic Classification of Alzheimer's Disease: Application to Metabolome Data" in eBioMedicine (doi: 10.1016/j.ebiom.2023.104820) in October 2023. The study introduced a novel Circular-Sliding Window Association Test (c-SWAT) methodology to improve classification accuracy in predicting Alzheimer...
[2023/07/16] AAIC 2023 Poster Presentation - SWAT-Tab
Dr. Jo presented his research at the Alzheimer's Association International Conference (AAIC) 2023. His poster presentation, "Deep Learning-based SWAT-Tab Approach for Identifying Genetic Variants using Whole Genome Sequencing," was co-authored with Kwangsik Nho and Andrew J. Saykin.
[2023/07/16] AAIC 2023 Poster Presentation - Neuroimaging and Genetic Data Integration
Dr. Jo presented his research at the Alzheimer's Association International Conference (AAIC) 2023. His poster presentation, "Deep Learning-based Integration of Neuroimaging and Genetic Data for Classification of Alzheimer's Disease," explored novel approaches to combining multi-modal data for improved AD diagnosis.
[2023/03/25] New Book: Beginner's Guide to Cognitive Neuroscience: An Introductory Text
Dr. Jo served as a translator and technical reviewer for the "Beginner's Guide to Cognitive Neuroscience" (ISBN 979-1165219154), published by Gilbut Publishing in 2022. This 320-page introductory text provides aspiring neuroscientists with a comprehensive overview of cognitive neuroscience principles and foundational concepts.
[2022/10/13] Invited Talk: A Dual-Deep Learning AI Strategy for Genetic Variants
Dr. Jo delivered a presentation titled "A Dual-Deep Learning AI Strategy for Genetic Variants" at the Indiana Alzheimer's Disease Research Center Fall Research Symposium in 2022. The talk showcased innovative research applying dual-deep learning approaches to analyze genetic variants.
[2022/07/23] Research Grant: Alzheimer's Association Research Grant (AARG) Award
Dr. Jo was awarded an Alzheimer's Association Research Grant (AARG) in 2022 for his research project "Dual-Deep Learning AI Strategy for Tau-associated Genetic Variants in Alzheimer's Disease" from the Alzheimer's Association. This grant supports innovative research applying dual-deep learning approaches to understand genetic variants associated with tau pathology in Alzheimer's di...
[2022/06/10] EBS TV Special Series: The Role of AI in Alzheimer's Disease
Dr. Jo delivered a four-part lecture series on EBS TV, Korea's largest public educational television network, making complex scientific developments accessible to the general public. The comprehensive series explored: "The Increasing Prevalence and Causes of Early Dementia" "AI Technology for Predicting Alzheimer's Disease" "Genetic Variations in Alzheimer's Disease and AI" "AI and Its ...
[2022/03/31] New Book: Deep Learning for Everyone: A Comprehensive Guide (3rd Edition)
Dr. Jo authored "Deep Learning for Everyone" (3rd Edition, ISBN 979-1165219246), published by Gilbut Publishing in 2022. This 472-page comprehensive guide provides an extensive overview of deep learning concepts and their applications, making the subject accessible to a broad audience.
Dr. Jo and colleagues published a research paper titled "Deep Learning-based Identification of Genetic Variants: Application to Alzheimer's Disease Classification" in Briefings in Bioinformatics in 2022 (doi: 10.1093/bib/bbac022). The study introduced a novel deep learning-based approach to identify genetic variants associated with Alzheimer's disease, demonstrating effective classificatio...
Dr. Jo delivered a lecture on "Deep Learning in Alzheimer's Disease: Diagnostic Classification and Prognostic Prediction Using Neuroimaging Data" at the 1st International Symposium Interdisciplinary Graduate Program in Medical Bigdata Convergence, held at Baeksong Hall, School of Medicine, Kangwon National University on December 2, 2021.
[2021/09/08] New Book: Kaggle Data Analysis
Dr. Jo served as a translator and technical reviewer for "Kaggle Data Analysis" (ISBN 979-1165216726), published by Gilbut Publishing in 2021. This 332-page comprehensive guide provides practical instruction on real-world data analysis using Kaggle datasets.
[2021/07/26] AAIC 2021 Poster Presentation: Deep learning–based GWAS
Dr. Jo presented his research at the Alzheimer's Association International Conference (AAIC) 2021. His poster presentation, "Deep Learning–Based Genome‐Wide Association Analysis in Alzheimer's Disease," demonstrated a novel CNN approach analyzing over 12 million SNPs from 916 ADNI participants.
[2021/04/05] Research Publication: Advances and Challenges in AlphaFold2
Dr. Jo published a comprehensive review article titled "Advances and Challenges in AlphaFold2" in Physics and High Technology in 2021. The article provided an in-depth analysis of the developments and current limitations in AlphaFold2's protein structure prediction capabilities.
Dr. Jo, along with colleagues, published a research paper titled "Deep Learning Detection of Informative Features in tau PET for Alzheimer's Disease Classification" in BMC Bioinformatics (doi: 10.1186/s12859-020-03848-0) in 2020. The study developed a deep learning-based framework combining 3D CNN and LRP algorithms to identify informative features in tau PET images for Alzheimer's disease...
[2020/12/15] Invited Lecture: Natural Language Processing: From Tokenizers to Attention Mechanisms
Dr. Jo delivered an invited lecture at Seoul National University of Science and Technology. His presentation, "Natural Language Processing: From Tokenizers to Attention Mechanisms," provided a comprehensive overview of modern NLP architectures and techniques.
[2020/11/16] Invited Talk: Deep Learning and its Application for Life Science
Dr. Jo delivered a special lecture on "Deep Learning and its Application for Life Science" at the Department of Physics, Kangwon National University on November 16, 2020. The lecture provided comprehensive insights into the applications of deep learning in life sciences.
Dr. Jo delivered a special lecture titled "Making Deep Learning Your Own - From Concepts to Applications" at the Department of Educational Technology, Konkuk University on October 21, 2020.
[2020/07/27] AAIC 2020 Poster Presentation: Flortaucipir PET Feature Detection
Dr. Jo presented his research at the Alzheimer's Association International Conference (AAIC) 2020. His presentation, "Deep Learning Detection of Informative Features in [18F] Flortaucipir PET for Alzheimer's Disease Classification," demonstrated a novel deep learning approach for analyzing tau PET imaging data to classify AD and MCI.
[2020/01/27] New Book: Deep Learning for Everyone: A Comprehensive Guide (2nd Edition)
Dr. Jo authored "Deep Learning for Everyone" (2nd Edition, ISBN 979-1160504606), published by Gilbut Publishing in 2020. This 368-page comprehensive guide provides an extensive overview of deep learning concepts and their applications, making the subject accessible to a broad audience.
Dr. Jo, along with colleagues, published a systematic review paper titled "Deep Learning in Alzheimer's Disease: Diagnostic Classification and Prognostic Prediction Using Neuroimaging Data" in Frontiers in Aging Neuroscience (doi: 10.3389/fnagi.2019.00220) on August 20, 2019. This comprehensive review examined the application of deep learning approaches in neuroimaging data for improving Alzhe...
[2019/07/12] AAIC 2023 Poster Presentation - Multimodal-3DCNN
Dr. Jo presented his research at the Alzheimer's Association International Conference (AAIC) 2023. His poster presentation, "Multimodal-3DCNN: Diagnostic Classification of Alzheimer's Disease Using Deep Learning on Neuroimaging, Genetic, and Demographic Data," demonstrated a novel approach to integrating multiple data types for enhanced AD diagnosis.
[2018/07/22] AAIC 2018 Poster Presentation: Enhanced MRI-based Classification
Dr. Jo presented his research at the Alzheimer's Association International Conference (AAIC) 2018. His poster presentation was titled "Multimodal-CNN: Improved Accuracy of MRI-based Classification of Alzheimer's Disease by Incorporating Clinical Data in Deep Learning."
[2018/04/30] New Book: Deep Learning Workbook: A Practical Guide to Implementing Deep Learning Code
Dr. Jo served as a technical reviewer for the "Deep Learning Workbook" (ISBN 979-1160504606), published by Gilbut Publishing in 2018. This 218-page comprehensive guide provides practical implementations of deep learning code. The book offers hands-on exercises and practical examples for readers to understand and implement deep learning concepts.
[2017/12/27] New Book: Deep Learning for Everyone by Dr. Taeho Jo has been published (First Edition)
Dr. Jo authored "Deep Learning for Everyone" (ISBN 979-1160503715), published in 2018. This 308-page comprehensive guide became a bestseller in Korea's IT category (2018-2019) and was selected as Book of the Year (2017-2019) by major Korean bookstores including KyoboBook, Yes24, and Aladin.
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