About Eric Odle

Eric Odle, Ph.D.

Postdoctoral Researcher

Department of Information Engineering and Computer Science
Feng Chia University
No. 100, Wenhwa Road, Taichung City, 407102, Taiwan, R.O.C.

Education

Ph.D. in Evolutionary Biology

Hokkaido University
Japan
Sept. 2022 – Sept. 2025

  • Thesis: Influence of Host Association and Biogeography on Pacific Marine Gregarine Speciation

M.S. in Neurophysiology

National Taiwan Normal University
Taiwan
Feb. 2019 – Jun. 2021

  • Thesis: Evaluation of the Therapeutic Effects of Dimethyl Sulfoxide on FMR1 Mutant Zebrafish Using Open-Source Deep Learning Software

M.A. in Applied Linguistics

Yuan Ze University
Taiwan
Feb. 2017 – Jun. 2019

  • Thesis: English-to-Japanese Translation of the Beck Depression Inventory-II: an Appraisal Analysis

B.A. in Japanese Language

University of Alaska, Anchorage
USA
Aug. 2010 – Jul. 2012

  • GPA: 3.9/4.0

B.S. in Biology

Saint Louis University
USA
Aug. 2006 – May 2010

  • GPA: 3.9/4.0

Professional Experience

Full-Stack Web Developer

matsuri-hr.com
Tokyo, Japan
Aug. 2024 – Present

  • Role: Full-stack web developer for Tokyo-based job-hunting site
  • Responsibilities: Incorporate CI/CD workflows, build end-to-end functionality, code review, assist junior team members, lead meetings, respond to client feedback
  • Tools: Ruby on Rails, Nuxt/Vue.js, Docker, Ubuntu Server

Static Site Developer, DevOps, and AI Integration Intern

Space Cubics, Inc.
Dec. 2024 – Present

  • Role: Static site developer, DevOps, and AI integration intern
  • Responsibilities:
    1. Lead transition of company website from all-in-one design/hosting solution to in-house written and self-hosted static site
    2. Lead project to establish containerized self-hosted GitHub workflow runners on in-house server
    3. Lead project integrating AI (Faster R-CNN) into PCB quality assurance workflow (image-based PCB component confirmation)
  • Tools: Zephyr, Zola, Jekyll, PyTorch, GitHub Actions, Nucleo-F429ZI, RPI Pico II

Machine Learning Researcher

Rebecca AI Lab (Taiwan Experience Education Program - TEEP)
Dec. 2021 – Aug. 2022

Publications

Journal Articles

2025

  • Alam, T., Shia, W. C., Hsu, F. R., Hassan, T., Lin, P.-C., Odle, E., & Watada, J. (2025). Hybrid Top Features Extraction Model for Detecting X Rumor Events Using an Ensemble Method. Journal of Web Engineering, 24(01), 79–106. DOI: 10.13052/jwe1540-9589.2414

2024

  • Odle, E., Riewluang, S., Ageishi, K., Kajihara, H., & Wakeman, K. C. (2024). Pacific marine gregarines (Apicomplexa) shed light on biogeographic speciation patterns and novel diversity among early apicomplexans. European Journal of Protistology, 94, 126080. DOI: 10.1016/j.ejop.2024.126080

  • Odle, E., Kahng, S., Riewluang, S., Kurihara, K., & Wakeman, K. C. (2024). GINSA: an accumulator for paired locality and next-generation small ribosomal subunit sequence data. Bioinformatics, 40(4). DOI: 10.1093/bioinformatics/btae152

  • Kahng, S. E., Odle, E., & Wakeman, K. C. (2024). Coral geometry and why it matters. PeerJ, 12, e17037. DOI: 10.7717/peerj.17037

2023

  • Odle, E., Hsueh, Y.-J., & Lin, P.-C. (2023). Semantic Positioning Model Incorporating BERT/RoBERTa and Fuzzy Theory Achieves More Nuanced Japanese Adverb Clustering. Electronics, 12(19), 4185. DOI: 10.3390/electronics12194185

2022

  • Bashirzade, A. A. O., Cheresiz, S. V., Belova, A. S., Drobkov, A. V., Korotaeva, A. D., Azizi-Arani, S., Azimirad, A., Odle, E., Gild, E.-Y. V., Ardashov, O. V., & others (2022). MPTP-treated zebrafish recapitulate 'late-stage' Parkinson's-like cognitive decline. Toxics, 10(2), 69.

2020

  • Lau, K., Lin, C.-Y., & Odle, E. (2020). 'I am just saying maybe…': Engagement in dissertation defenses. Language and Education, 35(1), 1–21.

Conference Proceedings

2024

  • Lin, P.-C., Yu, C.-Y., & Odle, E. (2024). Prototype for a Personalized Music Recommendation System Based on TL-CNN-GRU Model with 10-Fold Cross-Validation. In Proceedings of the 2024 7th Artificial Intelligence and Cloud Computing Conference (AICCC 2024) (pp. 87–94). ACM. DOI: 10.1145/3719384.3719396

2022

  • Odle, E., Lin, P.-C., & Farjudian, A. (2022). Comparing Recurrent Neural Network Types in a Music Genre Classification Task: Gated Recurrent Unit Superiority using the GTZAN Dataset. In Transactions on Computational Science & Computational Intelligence. Springer.

Research Interests

  • Machine Learning and Deep Learning
  • Music Information Retrieval and Classification
  • Natural Language Processing
  • Evolutionary Biology and Bioinformatics
  • Web Development and DevOps
  • AI Integration in Quality Assurance Systems

Open Source Projects

  • xLSTM-genre-classifier: Music Genre Research Project (MGRP) - A comprehensive music genre classification framework supporting multiple model architectures (FC, CNN, LSTM, GRU, xLSTM, Transformer, VGG16, ViT) with tools for data processing, training, evaluation, and analysis.

  • GINSA: GbIf Next-gen Sequence Analyzer - A tool for extracting small ribosomal subunit (SSU) sequences from metagenomic data by pairing GBIF occurrence data with EMBL's ENA repository, enabling researchers to gather species-specific sequence data for their research.

  • Space Cubics Website: Company website for Space Cubics, Inc. - A static site built with modern web technologies, showcasing the company's work in aerospace and technology solutions.

  • GenreDiscern: Music genre discriminator via artificial neural network modeling, focusing on automated music classification using deep learning techniques.

  • Semantic-Positioning-Model-for-Japanese-Adverbs: Exploration of BERT's ability to preserve semantic relationships among Japanese adverbs, combining natural language processing with fuzzy theory for nuanced linguistic analysis.