Minh-Son Dao | Deep Learning | Best Researcher Award

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Dr. Minh-Son Dao | Deep Learning | Best Researcher Award

Researcher at The National Institute of Information and Communications Technology (NICT), Japan.

Dr. Minh-Son DAO is a distinguished Senior Researcher and Research Manager at the Big Data Integration Research Center, National Institute of Information and Communications Technology (NICT), Japan. With over two decades of research and leadership experience across academia and government, he leads cutting-edge initiatives in artificial intelligence, big data analytics, and smart IoT systems. He has played a pivotal role in Japan’s Society 5.0 vision through projects like MMCRAI and collaborative smart-city platforms. Dr. DAO is also a committed educator, serving as a thesis supervisor and adjunct lecturer across multiple international universities. His work has earned him numerous accolades, including multiple Best Challenge Awards, national recognitions, and research excellence honors. With over 100 peer-reviewed publications and international partnerships spanning Europe and Asia, he continues to bridge academic rigor with real-world impact. His current focus lies in multimodal AI frameworks and data-driven societal innovation.

Professional Profile

Suitability For Best Researcher Award – Dr. Minh-Son Dao

Dr. Minh-Son DAO exemplifies the qualities of an outstanding researcher through his sustained, interdisciplinary contributions to artificial intelligence, big data analytics, and smart IoT systems. With over 20 years of research leadership, a strong publication record (100+ peer-reviewed papers), and international collaboration across Europe and Asia, he has significantly influenced both theoretical advancements and real-world applications. His active role in Japan’s Society 5.0 vision and the development of the MMCRAI framework further underscore his commitment to data-driven societal innovation. Dr. DAO also demonstrates excellence in mentoring, editorial roles, and academic service, enriching the broader research ecosystem.

Education

Dr. Minh-Son DAO holds a Ph.D. in Information and Communications Technology from Trento University, Italy, where his research focused on similarity measures and shape matching using genetic algorithms. His doctoral dissertation introduced the Edge Potential Function (EPF), a novel contribution to shape-based image retrieval. Prior to that, he earned a Master’s degree in Computer Science from Vietnam National University, specializing in handwritten character recognition using Convolutional Neural Networks—an early demonstration of his interest in deep learning. His Bachelor’s degree, also in Computer Science from the University of HCM City, Vietnam, emphasized image processing and hypertext applications. These academic milestones laid a strong foundation in AI, machine learning, and multimedia processing, enabling him to merge theoretical knowledge with practical innovation throughout his career. His educational journey reflects a continuous pursuit of excellence across diverse computational and applied domains.

Experience

Dr. Minh-Son DAO brings over 20 years of extensive research and leadership experience across Asia and Europe. Currently, he serves as Research Manager and Senior Researcher at NICT Japan, spearheading national AI and Smart IoT initiatives. His prior roles include Deputy Director and Senior Assistant Professor at Universiti Teknologi Brunei, where he also founded the ELEDIA@UTB lab focused on smart farming and wireless technologies. He has held prestigious research roles at Trento University, Osaka University (as a JSPS Fellow), and GraphiTech Italy. He has supervised more than 40 postgraduate students, co-authored over 100 publications, and led multi-institutional projects in smart cities, multimedia analytics, and health informatics. His teaching portfolio spans creative multimedia, data science, and database systems. Known for building strong global research networks, Dr. DAO has established successful collaborations with institutions in Norway, Ireland, Vietnam, and Switzerland, playing a vital role in cross-disciplinary and cross-cultural scientific advancements.

Professional Development

Dr. Minh-Son DAO has consistently invested in professional development to enhance his academic and leadership capabilities. He completed the UTB Faculty Development Program and the Foundations of University Learning and Teaching at Universiti Teknologi Brunei, gaining proficiency in teaching pedagogy, assessment strategies, and flipped classroom techniques. He also holds Oracle certifications in SQL, PL/SQL, and web application development. His involvement as a guest editor for high-impact journals such as IEEE ACCESS, ACM TOMM, and Frontiers in Big Data, along with his participation as program committee member for numerous international conferences, highlights his role as a thought leader in multimedia, AI, and big data. Dr. DAO frequently chairs and organizes conferences and workshops, including ICMLSC, ICCRD, and MediaEval. His holistic development in research, teaching, industry consulting, and international collaboration exemplifies a well-rounded professional commitment to lifelong learning and knowledge dissemination in cutting-edge computing technologies.

Research Focus

Dr. Minh-Son DAO’s research primarily focuses on multidisciplinary applications of Artificial Intelligence, Big Data Analytics, and Smart IoT systems, aligning closely with the vision of a data-driven, intelligent society (Society 5.0). His most notable initiative, the Multimodal and Cross-modal AI Framework (MMCRAI), demonstrates his commitment to converting raw multimodal data into actionable insights across domains like environmental monitoring, health informatics, multimedia forensics, and smart cities. He has applied his research to real-world challenges such as air pollution prediction, disaster management, and cheapfake detection. His work spans from foundational AI techniques to practical societal applications, including the integration of sensor networks, robotics, and citizen-driven data platforms. Through collaborative international projects, he explores the intersections between cyber-physical-social systems, smart urban planning, and sustainable development. This focus enables him to address complex problems with scalable, intelligent solutions that impact public health, education, urban resilience, and digital media integrity.

Research Skills

Dr. Minh-Son DAO possesses a comprehensive suite of research skills that bridge theoretical and applied domains. He is proficient in machine learning, deep learning, multimedia retrieval, and big data analytics, often applying these in cross-modal and multimodal AI frameworks. His technical abilities include programming in C++, R, SQL, HTML/JavaScript, and Python, and working with AI tools such as TensorFlow and Keras. Dr. DAO’s expertise spans data fusion, smart sensor integration, pattern recognition, event detection, and AI-based forecasting models, enabling him to tackle large-scale and heterogeneous data sources. Additionally, he has extensive experience in research project management, proposal writing, international collaboration, and supervising graduate students. His editorial and peer-review roles in IEEE, Springer, and Elsevier journals further reflect his analytical and evaluative skill set. These capabilities have allowed him to lead multi-disciplinary teams and create impactful AI-driven solutions for urban management, environmental monitoring, and personalized health analytics.

Awards and Honors

Dr. Minh-Son DAO has received numerous national and international awards recognizing his research excellence and innovation. Notably, he won the Best Challenge Awards at ICMR 2023 and ACM MM 2022 for his groundbreaking work in cheap fake detection. He was honored with the Excellent Performance Award by Japan’s NICT in 2022, reflecting his leadership in national projects. Earlier, he earned first-place awards at prestigious competitions such as image CLEF 2018 and Media Eval 2017 for his contributions to multimedia understanding and disaster response. He received the Research Excellence Mid-Career Academic Award from University Technology Brunei in 2017. His early career was marked by competitive international fellowships, including the JSPS International Fellowship (Japan) and ERCIM Fellowship (Europe), and he was awarded Vietnam’s highest youth scientific honor, the Creative Youth Medal. These accolades affirm his sustained contributions to AI, data science, and societal innovation across multiple countries and disciplines.

Conclusion

Dr. Minh-Son DAO’s profile aligns exceptionally well with the criteria for a Best Researcher Award. His work bridges high-impact research, global collaboration, and societal benefit. His innovations in AI and multimodal systems, combined with his leadership in international research initiatives and dedication to mentorship, make him a deserving candidate. His recognition through prestigious awards and fellowships across continents further validates his global research excellence.

Publication Top Notes

1. Deep learning for mobile multimedia: A survey

  • Authors: K Ota, MS Dao, V Mezaris, FGBD Natale

  • Journal: ACM Transactions on Multimedia Computing, Communications, and Applications

  • Cited by: 188

  • Year: 2017

Summary:
This comprehensive survey explores how deep learning techniques have been adapted and optimized for mobile multimedia applications. It covers both theoretical advancements and practical implementation challenges. The paper also discusses energy efficiency and processing limitations of mobile devices. It has become a foundational reference in mobile multimedia research.

2. Exploring convolutional neural network architectures for EEG feature extraction

  • Authors: I Rakhmatulin, MS Dao, A Nassibi, D Mandic

  • Journal: Sensors, Vol. 24(3), Article 877

  • Cited by: 62

  • Year: 2024

Summary:
This paper investigates CNN-based methods for extracting features from EEG signals, a key step in brain-computer interface development. Multiple CNN architectures are compared for performance and accuracy. The study demonstrates significant improvement in signal interpretation. It contributes to the emerging field of AI-powered neuro technology.

3. Daily human activities recognition using heterogeneous sensors from smartphones

  • Authors: MS Dao, TA Nguyen-Gia, VC Mai

  • Journal: Procedia Computer Science, Vol. 111, pp. 323–328

  • Cited by: 34

  • Year: 2017

Summary:
The paper presents a method for recognizing daily human activities using various smartphone sensors. It highlights sensor fusion techniques to improve detection accuracy. The approach is lightweight and suitable for real-time implementation. It holds potential for fitness, health, and smart environment applications.

4. A real-time complex event discovery platform for cyber-physical-social systems

  • Authors: MS Dao, S Pongpaichet, L Jalali, K Kim, R Jain, K Zettsu

  • Conference: International Conference on Multimedia Retrieval

  • Cited by: 34

  • Year: 2014

Summary:
This work proposes a real-time platform for discovering complex events from integrated cyber, physical, and social sources. It focuses on fusing multi-modal data streams for event detection. The platform is designed for smart city and situational awareness applications. It bridges the gap between social sensing and real-time analytics.

5. Edge potential functions (EPF) and genetic algorithms (GA) for edge-based matching of visual objects

  • Authors: MS Dao, FGB De Natale, A Massa

  • Journal: IEEE Transactions on Multimedia, Vol. 9(1), pp. 120–135

  • Cited by: 33

  • Year: 2006

Summary:
This paper introduces edge potential functions (EPF) combined with genetic algorithms for visual object matching. It enhances robustness in noisy or occluded conditions. The method shows improvements in object recognition performance. It contributes foundational techniques for multimedia and computer vision systems.

Rohan Duppala | Machine Learning | Young Researcher Award

Published on by Computer Vision Awards

Mr. Rohan Duppala | Machine Learning | Young Researcher Award

Student at VIT-AP University, India

Rohan Duppala is an emerging researcher and technologist with a strong foundation in artificial intelligence, machine learning, deep learning, and natural language processing. As a final-year B.Tech Computer Science student at VIT-AP University, he has demonstrated exceptional research capabilities, developing innovative solutions in healthcare, education, and smart transportation. Rohan has published multiple papers in reputed journals, including Scientific Reports and MDPI, and has worked on diverse AI-driven projects, from infant cry classification and Alzheimer’s detection to generative AI-based educational tools. His ability to integrate advanced AI models with real-world applications reflects a rare combination of academic rigor and practical insight. In addition to academic work, Rohan has engaged with leading technologies like Gemini, Llama 3, and Weights & Biases, earning several certifications and accolades. With a forward-thinking mindset and a passion for impactful research, he aspires to contribute meaningfully to global challenges through AI and interdisciplinary innovation.

Professional Profile 

Education🎓

Rohan Duppala is currently pursuing his Bachelor of Technology in Computer Science and Engineering at VIT-AP University in Andhra Pradesh. His education has provided a rigorous grounding in core computer science principles while enabling him to explore advanced technologies such as artificial intelligence, machine learning, and natural language processing. Prior to his undergraduate studies, he completed his intermediate education in the Mathematics, Physics, and Chemistry (MPC) stream at Narayana Junior College in Visakhapatnam. He also completed his schooling at Sri Chaitanya School in Palasa, Andhra Pradesh. Throughout his academic journey, Rohan has demonstrated consistent excellence and a strong inclination toward analytical thinking and computational problem-solving. This solid educational background has laid the foundation for his research endeavors and technical accomplishments in AI, edge computing, and intelligent systems.

Professional Experience📝

Rohan gained hands-on industry experience as an IoT Specialist at Prayana Electric between June and August 2024. During his tenure, he was instrumental in integrating IoT solutions into electric bicycles, leveraging microcontrollers, GPS, and LoRa technologies to enable real-time monitoring and smart navigation. He also spearheaded the development of a pothole detection system, optimized specifically for edge deployment on Raspberry Pi Pico, seamlessly integrating it into the e-bike ecosystem. This professional experience not only expanded his understanding of smart transportation and embedded systems but also allowed him to apply theoretical AI knowledge to practical, scalable solutions. Rohan’s work at Prayana Electric reflects his ability to bridge the gap between academic research and industry requirements, highlighting his skills in system design, data analysis, and sensor integration. His initiative, problem-solving abilities, and adaptability in a real-world setting underscore his potential as a well-rounded researcher and future technology leader.

Research Interest🔎

Rohan Duppala’s research interests lie at the intersection of artificial intelligence, healthcare, education, and smart systems. He is particularly focused on building explainable and ethically sound AI systems that can be deployed in real-world settings. His work in medical diagnostics, including projects on Alzheimer’s and Parkinson’s disease detection using deep learning, underscores a commitment to socially impactful research. Rohan also explores Generative AI and Large Language Models, applying them to applications such as automated script evaluation, infant care, and educational feedback systems. His interest in edge AI and IoT-enabled smart devices reflects a drive to create scalable, efficient, and context-aware solutions for real-time environments. By combining transformer models, retrieval augmented generation (RAG), signal processing, and explainable AI (XAI) techniques, Rohan aims to push the boundaries of intelligent automation in human-centric domains. His interdisciplinary approach and ethical consideration make his research both innovative and future-ready.

Award and Honor🏆

Rohan Duppala has been recognized for his academic and technical excellence with several awards and honors. He received a Certificate of Honor from OpenCV University in recognition of his outstanding performance in deep learning applications and project execution. Additionally, he was awarded a unique NFT (Non-Fungible Token) honor from The Hashgraph Association, celebrating his innovation and engagement in the decentralized technology community. His publications in reputed platforms such as Scientific Reports (Nature) and MDPI further reflect the quality and impact of his research. These accolades highlight not only his technical achievements but also his ability to stand out in competitive, global academic and developer communities. His participation in specialized bootcamps, advanced workshops, and certificate programs offered by Google, AWS, Cisco, and Weights & Biases has further solidified his position as an accomplished early-career researcher poised for excellence in AI-driven innovation.

Research Skill🔬

Rohan Duppala possesses an advanced and versatile skill set tailored for research in artificial intelligence and related domains. He is proficient in Python and Java, with hands-on experience in building custom convolutional neural networks, implementing transformer models, and deploying real-time deep learning systems on edge devices like Raspberry Pi. His practical expertise spans data preprocessing, hyperparameter tuning, model evaluation, explainable AI (XAI) techniques like LIME and Saliency Maps, and fine-tuning large models like LLaMA 3 8b using LoRA. He has also worked with tools such as Hugging Face Transformers, Weights & Biases, and Streamlit for model development and deployment. Rohan is skilled in retrieval augmented generation (RAG), multimodal data processing, and prompt engineering. His ability to combine AI techniques with IoT, computer vision, and NLP enables him to develop interdisciplinary solutions. These research skills, backed by strong implementation and critical thinking abilities, make him a technically mature and innovation-ready researcher.

Conclusion💡

Rohan Duppala is a highly deserving candidate for the Best Researcher Award, owing to his exceptional drive, technical acumen, and impactful research contributions at an early stage of his academic journey. His work spans critical societal applications—from medical diagnostics using deep learning to educational tools powered by large language models—demonstrating both depth and relevance. With peer-reviewed publications in reputed journals like Scientific Reports and MDPI, and hands-on innovation in smart technologies and AI systems, he has already laid a strong foundation for a distinguished research career. Given his dedication, continuous learning, and visionary approach to solving real-world problems, Rohan holds immense potential for future leadership in the fields of artificial intelligence and intelligent healthcare systems.

Publications Top Noted✍

  • Title: An extensive experimental analysis for heart disease prediction using artificial intelligence techniques
    Authors: D. Rohan, G.P. Reddy, Y.V.P. Kumar, K.P. Prakash, C.P. Reddy
    Year: 2025
    Citations: 4

  • Title: A Custom Convolutional Neural Network Model-Based Bioimaging Technique for Enhanced Accuracy of Alzheimer’s Disease Detection
    Authors: P. Reddy G., S.M.A. Kareem, Y.V.P. Kumar, P.P. Kasaraneni, M. Janapati
    Year: 2025
    Citations: 1

  • Title: Artificial intelligence-based effective detection of Parkinson’s disease using voice measurements
    Authors: G. Pradeep Reddy, D. Rohan, Y.V.P. Kumar, K.P. Prakash, M. Srikanth
    Year: 2024
    Citations: 1