Su Myat Noe
I am Su Myat Noe, a passionate and multidisciplinary researcher in Computer Science, specializing in Computer Vision, Artificial Intelligence, Machine Learning, and Deep Learning. I recently completed my Ph.D. at the University of Miyazaki, Japan, where I focused on developing deep learning-based methods for detecting estrus in cattle using multi-camera tracking systems. Currently, I am working as a Project Researcher at the National Institute of Informatics (NII), Tokyo, Japan, contributing to cutting-edge research in vision-language modeling, RAG systems, agentic AI, Video Question Answering (VideoQA), and video summarization. Through my publications in leading conferences and journals, I aim to advance impactful and practical AI solutions.
Beyond academia, I actively engage in leadership and advocacy roles within the AI community. As the Ambassador of Women in AI Myanmar, I work tirelessly to promote gender inclusivity and diversity in the AI domain. Additionally, serving as the Google Developer Student Club Lead of Japan 2022-2023 allows me to connect with fellow AI enthusiasts, providing them with valuable learning opportunities and resources. I find great joy in organizing and speaking at tech events and conferences worldwide, where I share my knowledge and experiences, inspiring others to pursue their aspirations in AI.
I am always keeping a lookout for new gigs. Do you have a perfect gig for me? I am only an email away.
Education
Ph.D.
University of Miyazaki , Japan
Department of Materials and Informatics,
Computer Science and Bioinformatics Course,
Visual Information Processing Lab
Advisor: Dr. Thi Thi Zin
M.Eng.
University of Miyazaki
Department of Energy and Electronics, Visual Information
Processing Lab
Advisor: Dr. Thi Thi Zin
B.C.Sc.
University of Information Technology, UIT, Myanmar
Department of Computer Science
Major of Knowledge Engineering
RESEARCH INTERESTS
Working on computer vision and multimodal AI with focus on multi-camera tracking, object detection, VideoQA, and video summarization. Exploring RAG models, agentic systems, and automated annotation using vision-language techniques for real-world applications.
EXPERIENCE
Research and Development Center For Large Language Models - Project Researcher
Working closely with professors and team members at the Research and Development Center for Large Language Models on advancing Vision-Language Models (VLM), Retrieval-Augmented Generation (RAG), and diffusion-based image generation.
Developing multimodal systems for Video Question Answering (VideoQA), integrating visual content with natural language understanding to improve real-world information retrieval and comprehension.
Dr. Thi Thi Zin - Visual Information Processing Lab, Research Student
Worked closely with professors and team members in developing Cattle Monitoring System using various image processing methods and deploying AI Models
Explored and integrated object segmentation and classification algorithms like SVM (support vector machine) using state of the art deep learning algorithms and neural networks
HONORS & AWARDS
2025 Encouragement Women Research Award, University of Miyazaki, Japan
2024 Best Student Paper Award, 2024 , ICGEC Conference, Miyazaki, Japan
2024-2025 University of Miyazaki, President’s Research Funding Award
Google Developer Student Club
2022 Ministry of Japan Science Technology (JST) Researchers Grant for Doctoral Studies (2022- 2025)
2022 NEC C&C Non-Japanese Foreign Researchers Grant for Doctoral (2022-2023)
2022 Scholarship, JASSO Scholarship for International Student, Japan
2021 Women in Engineering Best Paper Award, 2021 IEEE 3rd Global Conference on LifeTech, Japan
2020 Full Scholarship, Naoji Iwatani Full Scholarship for Master Program, Japan
2019 Scholarship, JASSO Scholarship for International Student, Japan
PUBLICATIONS
Journal Papers
[1]Su Myat Noe, Thi Thi Zin, Pyke Tin, and Ikuo Kobayashi, 2025. Optimizing black cattle tracking in complex open ranch environments using YOLOv8 embedded multi-camera system. Scientific Reports, 15, Article no. 6820. Available at: https://doi.org/10.1038/s41598-025-13850-6
[2] Su Myat Noe, Thi Thi Zin, Pyke Tin, and Ikuo Kobayashi, "Precision Livestock Tracking: Advancements in Black Cattle Monitoring for Sustainable Agriculture", Journal of Signal Processing, 2024 Volume 28 Issue 4 Pages 179-182 , DOI:10.2299/jsp.28.179.
[3] Su Myat Noe, Thi Thi Zin, Pyke Tin, and Ikuo Kobayashi, “Automatic detection and tracking of mounting behavior in cattle using a deep learning-based instance segmentation model”, International Journal of Innovative Computing, Information and Control, Volume 18, Number 1, February 2022, ISSN1349-4198.
[4] Su Myat Noe, Thi Thi Zin, Pyke Tin and Kobayashi, Ikuo Kobayashi, “Comparing State-of-the-Art Deep Learning Algorithms for the Automated Detection and Tracking of Black Cattle”, Sensors, 23(1), p.532, DOI:10.3390/s23010532 (Scopus, IF: 3.9)
International Conference Papers and Symposiums
[1] Su Myat Noe, Thi Thi Zin, Pyke Tin, H. Hama, “Detection of Estrus in Cattle by using Image Technology and Machine Learning Methods”, Proc. of IEEE 9th Global Conf. on Consumer Electronics (GCCE 2020), Kobe, Japan, DOI: 10.1109/GCCE50665.2020.9291987, pp. 320-321, Dec. 2020.
[2] Su Myat Noe, Thi Thi Zin, Pyke Tin, Ikuo Kobayashi, “Automatic Detection of Mounting Behavior in Cattle using Semantic segmentation and classification”, Proc.of IEEE Global Conference on Life Sciences and Technologies (LifeTech 2021), Nara, Japan, DOI: 10.1109/LifeTech52111.2021.9391980, pp. 227-228, April 2021. (IEEE WIE Student Paper Award)
[3] Su Myat Noe, Thi Thi Zin, Pyke Tin, Ikuo Kobayashi, “A Deep Learning-based Instance Segmentation Model using Mask-RCNN for Automated Detection and Tracking of Mounting Behavior in Cattle”, Proc.of the 15th International Conference on Innovative Computing, Information and Control (ICICIC2021) September 15-16, 2021, online.
[4] Su Myat Noe, Thi Thi Zin, Pyke Tin, and Ikuo Kobayashi. "A Deep Learning-based solution to Cattle Region Extraction for Lameness Detection" In 2022 IEEE 4th Global Conference on Life Sciences and Technologies (LifeTech), pp. 572-573. IEEE, 2022, DOI: 10.1109/LifeTech53646.2022.9754780.
[5] Thi Thi Zin, Su Myat Noe, Moe Zet Pwint, and Ikuo Kobayashi. "An Intelligent Method for Detecting Lameness in Modern Dairy Industry'' on 2022 IEEE 4th Global Conference on Life Sciences and Technologies (LifeTech), pp. 564-565. IEEE, 2022, DOI: 10.1109/LifeTech53646.2022.9754941.
[6] Su Myat Noe, Thi Thi Zin, Pyke Tin, and Ikuo Kobayashi. " A Study on Automatic Black Cattle Tracking with Computer Vision and Deep Learning” In The Second Sakura Workshop, Taichung Taiwan , March 2023.
[7] Su Myat Noe, Thi Thi Zin, Pyke Tin, and Ikuo Kobayashi. "Efficient Segment-Anything Model for Automatic Mask Region Extraction in Livestock Monitoring" In IEEE ICCE-Berlin 2023, DOI: 10.1109/ICCE-Berlin58801.2023.10375624.
[8] Su Myat Noe, Thi Thi Zin, Pyke Tin, and Ikuo Kobayashi. "Enhancing Precision Agriculture: Innovative Tracking Solutions for Black Cattle Monitoring" In NCSP-Hawaii 2024 [Presented, Best Student Paper Award]
Doctoral Thesis
[1] Su Myat Noe, "A Study on Deep Learning-based Automated Detection and Tracking of Estrus Behavior in Black Cattle", Doctorals Thesis, University of Miyazaki, Japan. 2022.
Master’s Thesis
[1] Su Myat Noe, “Cow Estrus Detection and Tracking based on Image Technology with the Enforcement of Deep Learning Methods”, Master’s Thesis, University of Miyazaki, Japan, Jan. 2022.
Bachelor’s Thesis
[1] Su Myat Noe, Khine Myat Thwe, “Question Answering System using Bi-Directional Attention Flow”, Bachelor’s Thesis, University of Information Technology (UIT), Yangon, Myanmar, Sept. 2018.
Technical Workshop , Poster Presentation
[1] Su Myat Noe. "Towards Automatic Tracking of Black Cattle by Combining with Computer Vision and Deep Learning Approach". NOKOH Student Seminar in English, November 1, 2022, University of Miyazaki. (Oral and Poster Presentation)
[2] Su Myat Noe, Thi Thi Zin, Pyke Tin, and Ikuo Kobayashi. "A Study on Automatic Black Cattle Tracking with Computer Vision and Deep Learning". In The Second Sakura Workshop, Taichung Taiwan , March 2023.
INTERNSHIP EXPERIENCE
BAGAN INNOVATION TECHNOLOGY, JUNIOR DATA SCIENTIST
Collaboratively built Natural Language Processing (NLP) models for Myanmar Language that works with limited resource settings.
Performed text mining and web scraping from online data sources using Python libraries.
Developed data pipelines and machine learning models for Sentiment Analysis for Myanmar Language to be used in chat-bot offerings.
FUJITSU JAPAN, JUNIOR SYSTEM DEVELOPER
Performed day to day duties such as testing functionalities of the system to ensure the software quality.
Developed a Hotel Reservation System with PHP, JavaScript, and jQuery Language by following the fast-paced agile development cycle.
Produced source codes by converting logical sequences and workflows from the project requirements.
TECHNICAL SKILLS
Programming: Python, C++, MATLAB
Computer Vision Skills: OpenCV, Image Processing, CNN Models
Deep Learning Skills: TensorFlow, Keras, CUDA, Machine Learning, Deep Learning, Development and implementation of data/image processing algorithms, Automatic Dataset Generation, Building Datasets from Scratch, Supervised Learning, Unsupervised Learning
Libraries: Pandas, Numpy, Matplotlib, TensorFlow, Keras, OpenCV
Additional Data Processing Skills: Data Pipelines, Advanced digital data/image processing techniques, Natural Language Processing, Sentiment Analysis
SOFT SKILLS
Languages:
English (TOEFL IBT 81, TOEIC 850)
Japanese (JLPT N3)
INVITED TALKS
2019 Jul: Technical Workshop at University of Information Technology Myanmar “How to Build a Machine Learning Community in a Developing Country”.
2022 Jul: Google Developer Expert, DevFest, Yangon, Myanmar (Virtually), “Knowledge Sharing About Computer Vision Kaggle”
2022 Nov: Google Developer Expert, DevFest, Yangon, Myanmar (Virtually), “Object Detection and Instance Segmentation with Detectron 2 Framework”
VOLUNTEERING
WOMEN IN AI Myanmar, Ambassador
Since December 2020, I've served as an Ambassador for Women in AI Myanmar, a chapter dedicated to promoting gender equality in the field. My focus lies on empowering women to take leadership positions within AI and machine learning industries, while also creating opportunities for underprivileged youth, particularly girls, to gain valuable skills and knowledge in this rapidly evolving field.
Google Developer Student Club Lead, Japan
Through the Google Developer Student Club (GDSC) network, I spearheaded initiatives to empower next-generation undergraduate students to innovate through emerging AI technologies. This involved introducing engaging campus activities that fostered hands-on learning and exploration of cutting-edge AI tools.