Phong Lam Nguyen Duy | Computer Science | Best Researcher Award

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Mr. Phong Lam Nguyen Duy | Computer Science | Best Researcher Award

👤 Mr. Phong Lam Nguyen Duy, University of Engineering and Technology – Vietnam National University, Vietnam

Phong Lam Nguyen Duy is a motivated undergraduate student in the Computer Science Department at the University of Engineering and Technology, Vietnam National University, Hanoi. Born on July 6, 2004, in Ha Dong, Hanoi, Phong Lam is passionate about exploring cutting-edge technologies in data science and artificial intelligence. His primary research interests include automated data quality assurance, machine learning algorithms, and advancements in large language models. Apart from academics, Phong Lam is actively involved in volunteering, demonstrating a commitment to fostering community development through initiatives like the ICPC Asia Pacific Championship and Hanoi Green Summer programs. A proactive learner and aspiring researcher, Phong Lam has already contributed as a university research assistant at the Intelligence Software Engineering Laboratory, where he leverages his problem-solving skills and technical expertise. Phong Lam aspires to contribute significantly to the field of Computer Science and aims to bridge gaps between theoretical concepts and real-world applications.

Professional Profile

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Suitability for the “Research for Best Researcher Award”

Summary of Suitability:
Phong Lam Nguyen Duy demonstrates remarkable potential as a candidate for the “Research for Best Researcher Award.” Currently pursuing undergraduate studies in the Computer Science Department at Vietnam National University, Hanoi, Phong has already begun contributing to cutting-edge research fields, including automated data quality assurance, machine learning, and large language models. These areas are highly relevant and impactful in today’s rapidly evolving technological landscape, showcasing his alignment with contemporary research priorities.

Phong’s involvement as a university research assistant at the Intelligence Software Engineering Laboratory since February 2024 highlights his active engagement in research at an early stage of his academic career. His recent publication, “Leveraging Local and Global Relationships for Corrupted Label Detection” (2025), reflects his ability to contribute to academic discourse and address challenges in machine learning—a field critical for advancements in artificial intelligence.

🎓 Education 

Phong Lam Nguyen Duy is pursuing his undergraduate degree in Computer Science at the University of Engineering and Technology, Vietnam National University, Hanoi. Since his enrollment in September 2022, he has been immersed in a rigorous academic curriculum focused on Information and Communication Technologies. The program emphasizes critical areas such as software development, data analysis, and systems design, providing him with a robust foundation in computer science. The university’s strong research culture has further fueled his interest in machine learning and automated data quality assurance. Phong Lam has actively engaged in research initiatives and academic projects, allowing him to apply his theoretical knowledge in practical contexts. The vibrant academic environment at Vietnam National University has cultivated his technical skills and problem-solving abilities, enabling him to stay at the forefront of technological advancements. He views his education as the stepping stone to a thriving career in computer science and artificial intelligence.

💼 Professional Experience 

Phong Lam Nguyen Duy is currently a research assistant at the Intelligence Software Engineering Laboratory, located in Hanoi, Vietnam. Since February 2024, he has been collaborating with faculty and fellow researchers to tackle challenges in automated data quality assurance and machine learning. His work primarily involves developing methodologies that improve data accuracy and reliability while optimizing machine learning models for large-scale datasets. Phong Lam’s role includes conducting literature reviews, designing experiments, and implementing cutting-edge algorithms to solve complex problems. His contributions are instrumental in advancing projects that integrate theoretical computer science with practical applications. As a research assistant, he has honed his analytical, programming, and communication skills, fostering his growth as a budding researcher. This professional experience has not only solidified his technical expertise but also instilled a passion for lifelong learning and innovation, preparing him for future endeavors in the rapidly evolving field of artificial intelligence.

🏅 Awards and Recognition 

Phong Lam Nguyen Duy has been recognized for his academic excellence, volunteer contributions, and research potential. His participation as a volunteer for the prestigious ICPC Asia Pacific Championship 2024 earned him commendations for his organizational skills and dedication to promoting computer science education. Additionally, his involvement in the Hanoi Green Summer 2023 showcased his commitment to community service, where he actively participated in environmental sustainability initiatives. Phong Lam’s academic achievements at Vietnam National University include consistent top performance in his courses, particularly in areas related to machine learning and data science. His appointment as a research assistant at the Intelligence Software Engineering Laboratory further highlights his aptitude and potential for innovation in the field. Through these accolades, Phong Lam has established himself as a well-rounded individual, excelling academically while contributing to society and pursuing impactful research in computer science.

🌍 Research Skills On Computer Science

Phong Lam Nguyen Duy possesses a strong skill set in computational research and data science. His expertise includes automated data quality assurance, where he develops methodologies to identify and correct errors in datasets, ensuring reliability for machine learning applications. Phong Lam has a keen understanding of machine learning algorithms and their optimization, with experience in designing and training models for diverse applications. His research focus also encompasses advancements in large language models, where he explores their capabilities for natural language processing tasks. As a research assistant, he has gained hands-on experience in experimental design, data preprocessing, and implementing scalable solutions. Proficient in programming languages like Python and R, Phong Lam is adept at leveraging tools such as TensorFlow and PyTorch for deep learning projects. His analytical mindset and problem-solving abilities make him an invaluable contributor to the ever-evolving landscape of artificial intelligence and computer science research.

📖 Publication Top Notes

Title: Leveraging local and global relationships for corrupted label detection
  • Journal: Future Generation Computer Systems
  • Year: 2025

Iustina Ivanova | Computer Science | Best Researcher Award

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Mrs. Iustina Ivanova | Computer Science | Best Researcher Award

👤 Mrs. Iustina Ivanova, FBK, Italy

Iustina Ivanova is an accomplished researcher in the field of Artificial Intelligence (AI) with a focus on computer vision and machine learning applications in real-world scenarios. She holds a Master’s degree in Artificial Intelligence from the University of Southampton, where she earned distinction for her research on neural networks for object detection. Currently, Iustina is engaged in AI research in smart agriculture at the Fondazione Bruno Kessler in Italy. Over the years, she has contributed to a variety of high-impact projects, including developing a recommender system for outdoor sport climbers and researching sensors for sports activity analysis. Her work has earned her several well-regarded publications and recognition in the AI and computer vision communities.

Professional Profile

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🌟 Summary of Suitability for the Research for Best Researcher Award

Iustina Ivanova demonstrates exceptional qualifications for the “Research for Best Researcher Award.” Her academic background, professional experience, and research contributions highlight her significant impact on the fields of artificial intelligence (AI), machine learning, and computer vision. Her academic journey is distinguished by a Master’s degree in Artificial Intelligence with distinction from the University of Southampton and ongoing research pursuits during her Ph.D. studies. While her Ph.D. remains incomplete, the work she has undertaken—such as her contributions to recommender systems and computer vision—showcases her ability to address complex, real-world problems.

Professionally, Iustina’s research experience is diverse and impactful. At the Fondazione Bruno Kessler, she has been actively involved in applying AI to smart agriculture, addressing sustainability and innovation in the domain. Her previous roles, including as a Computer Vision Data Scientist and Data Science Moderator, further demonstrate her ability to bridge academia and industry.

🎓 Education

Iustina Ivanova has an impressive academic background in computer science and AI. She completed her Master of Science in Artificial Intelligence with distinction at the University of Southampton, UK, in 2018. Before that, she earned a Specialist degree in Software Engineering from Bauman Moscow State Technical University, Russia, in 2013. In 2019, she pursued a PhD in Computer Science at the Free University of Bolzano, Italy, although she later decided to focus more on practical AI applications. Her academic journey includes notable achievements such as developing research in neural networks for object detection, which has been the cornerstone of her professional career in AI.

💼  Professional Experience 

Iustina Ivanova has a diverse and robust professional background in AI and computer vision. She currently works as a researcher at the Fondazione Bruno Kessler, Italy, specializing in the use of AI for smart agriculture. Prior to this, Iustina served as a Data Science Moderator at Netology, Russia, where she designed and delivered online courses in statistics and mathematics for data science students. She also worked as a Computer Vision Data Scientist at OCRV, Russia, where she helped develop a video-based tracking system for railway workers, focusing on object detection and worker time measurement. Iustina’s role as a teacher of informatics and mathematics at Repetitor.ru involved preparing high school students for their final exams, ensuring that many students successfully entered top universities. Throughout her career, she has collaborated on numerous innovative projects in AI, particularly in outdoor sports and smart agriculture.

🏅Awards and Recognition 

Iustina Ivanova’s dedication and excellence in the field of AI have been recognized through multiple prestigious awards and accolades. Notably, she won several editions of the NOI Hackathon, including the SFSCON Edition (2021, 2022, 2024) and the Open Data Hub Edition (2022), showcasing her ability to create cutting-edge solutions in AI and data science. Her contributions to research and development in AI for sports activity analysis and computer vision have been published in highly regarded journals and conferences, such as the ACM Conference on Recommender Systems and IEEE Conferences. Iustina has also received recognition for her teaching contributions, inspiring future generations of data scientists. Her projects, especially those related to sports climbers’ recommender systems and sensor data analysis, have received wide acclaim for their innovation and real-world impact.

🌍 Research Skills On Computer Science

Iustina Ivanova’s research expertise spans artificial intelligence, machine learning, computer vision, and recommender systems. She is particularly skilled in using AI techniques to solve complex problems in real-world applications. Her work with neural networks for object detection and sensor data analysis has led to significant advancements in both sports and smart agriculture sectors. Iustina is proficient in Python, OpenCV, machine learning frameworks like PyTorch and TensorFlow, and data analysis tools such as Jupyter Notebook and Git. She is well-versed in the development of recommender systems and has implemented innovative solutions for outdoor sports, including climbing crag recommendations. Her interdisciplinary approach combines knowledge from software engineering, data science, and AI to design systems that enhance user experience and improve decision-making. Iustina is committed to the continual development of her skills, evident in her participation in advanced data science and deep learning courses, as well as her extensive practical work in AI.

📖 Publication Top Notes

  • Climbing crags repetitive choices and recommendations
    • Author: Ivanova, I.
    • Citation: Proceedings of the 17th ACM Conference on Recommender Systems, RecSys 2023
    • Year: 2023
    • Pages: 1158–1164
  • How can we model climbers’ future visits from their past records?
    • Authors: Ivanova, I., Wald, M.
    • Citation: UMAP 2023 – Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization
    • Year: 2023
    • Pages: 60–65
  • Introducing Context in Climbing Crags Recommender System in Arco, Italy
    • Authors: Ivanova, I.A., Wald, M.
    • Citation: International Conference on Intelligent User Interfaces, Proceedings IUI
    • Year: 2023
    • Pages: 12–15
  • Climbing crags recommender system in Arco, Italy: a comparative study
    • Authors: Ivanova, I., Wald, M.
    • Citation: Frontiers in Big Data
    • Year: 2023
    • Volume: 6, Article: 1214029
  • Map and Content-Based Climbing Recommender System
    • Authors: Ivanova, I.A., Buriro, A., Ricci, F.
    • Citation: UMAP2022 – Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization
    • Year: 2022
    • Pages: 41–45
  • Climbing Route Difficulty Grade Prediction and Explanation
    • Authors: Andric, M., Ivanova, I., Ricci, F.
    • Citation: ACM International Conference Proceeding Series
    • Year: 2021
    • Pages: 285–292
  • Climber behavior modeling and recommendation
    • Author: Ivanova, I.
    • Citation: UMAP 2021 – Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization
    • Year: 2021
    • Pages: 298–303
  • Knowledge-based recommendations for climbers
    • Authors: Ivanova, I., Andrić, M., Ricci, F.
    • Citation: CEUR Workshop Proceedings
    • Year: 2021
    • Volume: 2960
  • Climbing activity recognition and measurement with sensor data analysis
    • Authors: Ivanova, I., Andric, M., Janes, A., Ricci, F., Zini, F.
    • Citation: ICMI 2020 Companion – Companion Publication of the 2020 International Conference on Multimodal Interaction
    • Year: 2020
    • Pages: 245–249
  • Video and Sensor-Based Rope Pulling Detection in Sport Climbing
    • Authors: Ivanova, I., Andrić, M., Moaveninejad, S., Janes, A., Ricci, F.
    • Citation: MMSports 2020 – Proceedings of the 3rd International Workshop on Multimedia Content Analysis in Sports
    • Year: 2020
    • Pages: 53–60