Phong Lam Nguyen Duy | Computer Science | Best Researcher Award

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

๐Ÿ‘ค Mr. Phong Lam Nguyen Duy, University of Engineering and Technology โ€“ 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.

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Suitability for the โ€œResearch for Best Researcher Awardโ€

Summary of Suitability:
Phong Lam Nguyen Duy demonstrates remarkable potential as a candidate for the โ€œResearch for Best Researcher Award.โ€ 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 todayโ€™s rapidly evolving technological landscape, showcasing his alignment with contemporary research priorities.

Phongโ€™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, โ€œLeveraging Local and Global Relationships for Corrupted Label Detectionโ€ (2025), reflects his ability to contribute to academic discourse and address challenges in machine learningโ€”a field critical for advancements in artificial intelligence.

๐ŸŽ“ 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 universityโ€™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.

๐Ÿ’ผ 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 Lamโ€™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.

๐Ÿ… 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 Lamโ€™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.

๐ŸŒ 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.

๐Ÿ“– Publication Top Notes

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

Syed Mohammod Minhaz Hossain | Computer Science | Best Researcher Award

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Assoc. Prof. Dr. Syed Mohammod Minhaz Hossain | Computer Science | Best Researcher Award

๐Ÿ‘ค Assoc. Prof. Dr. Syed Mohammod Minhaz Hossain, Premier University, Bangladesh

Syed Mohammod Minhaz Hossain is a passionate researcher and IT professional dedicated to advancing the field of Computer Science and Engineering. He is currently pursuing a Ph.D. in Computer Science & Engineering at Chittagong University of Engineering & Technology (CUET). With a strong academic background, he earned his M.Sc. and B.Sc. in Computer Science & Engineering from CUET, securing notable positions. Hossain is committed to skillful learning and aims to create a synergy between industry and academia. He has published numerous research papers and contributed significantly to the scientific community, particularly in the areas of AI, machine learning, and environmental studies. Apart from his academic journey, he is a fervent advocate of education, believing in the power of teaching to shape well-rounded professionals who can contribute to societyโ€™s progress.

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 ๐ŸŒŸ  Suitability of Syed Mohammod Minhaz Hossain for the Research for Best Researcher Award:

Syed Mohammod Minhaz Hossain demonstrates strong academic and professional qualifications, making him a highly suitable candidate for the Research for Best Researcher Award. His dedication to academic excellence and research is reflected in his substantial academic achievements, including a Ph.D. in Computer Science and Engineering from Chittagong University of Engineering & Technology (CUET), and his outstanding undergraduate and postgraduate performance. His consistent recognition, such as the UGC Ph.D. Fellowship and multiple scholarships, underscores his commitment to research and academic growth.

Hossain has made notable contributions to the research community, particularly in the fields of artificial intelligence, machine learning, and environmental science. His extensive publication record includes numerous articles in high-impact journals such as PLoS ONE, Chemosphere, and Annals of Data Science, with a variety of topics ranging from water quality assessments to disease classification and COVID-19 detection using deep learning. His research not only focuses on technological advancements but also addresses pressing societal challenges, such as public health, environmental sustainability, and cybersecurity.

๐ŸŽ“  Education

Syed Mohammod Minhaz Hossainโ€™s academic journey is marked by consistent excellence. He is currently pursuing his Ph.D. in Computer Science & Engineering at Chittagong University of Engineering & Technology (CUET). Prior to that, he completed his M.Sc. in Computer Science & Engineering at CUET in 2022, where he earned a CGPA of 3.42. He also holds a B.Sc. in the same field from CUET, securing a remarkable CGPA of 3.56. His foundation in education started at Chittagong Collegiate School, where he excelled with a GPA of 4.63 in his SSC and later earned a GPA of 4.50 in his HSC at Chittagong College. Throughout his academic career, Hossain has received multiple scholarships, including the UGC PhD Fellowship (2021-2022) and various merit-based awards, underlining his dedication and outstanding performance in the field of Computer Science.

๐Ÿ’ผ Professional Experience

Syed Mohammod Minhaz Hossainโ€™s professional experience blends academia and industry, underscoring his passion for teaching and research. As a faculty member at Premier University, Bangladesh, Hossain conducts web system and program applications courses, integrating real-world industry skills into the classroom. His expertise is further demonstrated through his role in various research projects, focusing on areas such as artificial intelligence, deep learning, and environmental science. Hossainโ€™s experience includes collaborating with international researchers, contributing to high-impact journals and conferences. His role in designing and developing academic curricula reflects his commitment to fostering future IT professionals who are not only skilled but also socially responsible. Additionally, Hossainโ€™s involvement in the University of Technology, Sydney (UTS) Collegeโ€™s academic programs highlights his global outlook and the application of advanced research in practical teaching settings.

๐Ÿ… Awards and Recognitions 

Syed Mohammod Minhaz Hossainโ€™s journey is characterized by numerous academic and research accolades. He received the prestigious UGC PhD Fellowship for 2021-2022, showcasing his commitment to advancing knowledge in Computer Science. Hossain earned the fourth position in his B.Sc. at CUET and was a recipient of the Board Scholarship in his HSC in 2003. He was also honored with the Junior Merit Scholarship in 1998 and the Primary Merit Scholarship in 1995, underlining his consistent academic excellence from an early age. His research contributions have been widely recognized, with multiple publications in high-impact journals such as PLoS ONE, Annals of Data Science, and Chemosphere. Furthermore, Hossainโ€™s work on machine learning models for health-related issues and his involvement in international book chapters reflect his growing influence in the global research community.

๐ŸŒ Research Skills On Computer Science

Syed Mohammod Minhaz Hossain possesses a broad range of research skills that span artificial intelligence, machine learning, deep learning, and data science. His expertise includes applying these advanced technologies to solve complex problems in areas like health diagnostics, environmental monitoring, and cybersecurity. Hossain has developed proficiency in using deep neural networks, self-attention mechanisms, and convolutional models, as seen in his research on plant leaf disease recognition and heart disease prediction. Additionally, he has contributed to studies focused on the detection of COVID-19 fake news, Parkinsonโ€™s disease classification, and coastal water quality assessment. His research methodology includes leveraging large datasets, conducting statistical analyses, and employing advanced algorithms to create efficient and scalable solutions. Hossainโ€™s ability to integrate interdisciplinary knowledge into his projects further enhances his capability to make impactful contributions to both academic and practical fields.

๐Ÿ“– Publication Top Notes

  • Cyber Intrusion Detection Using Machine Learning Classification Techniques
    • Authors: H Alqahtani, IH Sarker, A Kalim, SMM Hossain, S Ikhlaq, S Hossain
    • Citations: 189
    • Year: 2020
  • A Data-Driven Heart Disease Prediction Model Through K-Means Clustering-Based Anomaly Detection
    • Authors: RC Ripan, IH Sarker, SMM Hossain, MM Anwar, R Nowrozy, MM Hoque
    • Citations: 66
    • Year: 2021
  • Rice Leaf Diseases Recognition Using Convolutional Neural Networks
    • Authors: SMM Hossain, MMM Tanjil, MAB Ali, MZ Islam, MS Islam, S Mobassirin
    • Citations: 49
    • Year: 2021
  • Plant Leaf Disease Recognition Using Depth-Wise Separable Convolution-Based Models
    • Authors: SMM Hossain, K Deb, PK Dhar, T Koshiba
    • Citations: 34
    • Year: 2021
  • Amassing the Covid-19 Driven PPE Wastes in the Dwelling Environment of Chittagong Metropolis and Associated Implications
    • Authors: MJ Abedin, MU Khandaker, MR Uddin, MR Karim, MSU Ahamad
    • Citations: 22
    • Year: 2022
  • Assessment of Coastal River Water Quality in Bangladesh: Implications for Drinking and Irrigation Purposes
    • Authors: MR Uddin, MU Khandaker, S Ahmed, MJ Abedin, SMM Hossain
    • Citations: 13
    • Year: 2024
  • Spam Filtering of Mobile SMS Using CNNโ€“LSTM Based Deep Learning Model
    • Authors: SMM Hossain, JA Sumon, A Sen, MI Alam, KMA Kamal, H Alqahtani
    • Citations: 13
    • Year: 2021
  • Plant Leaf Disease Recognition Using Histogram-Based Gradient Boosting Classifier
    • Authors: SMM Hossain, K Deb
    • Citations: 13
    • Year: 2021
  • Content-Based Spam Email Detection Using an N-gram Machine Learning Approach
    • Authors: NJ Euna, SMM Hossain, MM Anwar, IH Sarker
    • Citations: 9
    • Year: 2023
  • Trash Image Classification Using Transfer Learning-Based Deep Neural Network
    • Authors: D Das, A Sen, SMM Hossain, K Deb
    • Citations: 9
    • Year: 2022

 

Iustina Ivanova | Computer Science | Best Researcher Award

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Mrs. Iustina Ivanova | Computer Science | Best Researcher Award

๐Ÿ‘ค 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 Masterโ€™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.

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๐ŸŒŸ Summary of Suitability for the Research for Best Researcher Award

Iustina Ivanova demonstrates exceptional qualifications for the โ€œResearch for Best Researcher Award.โ€ 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 Masterโ€™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 undertakenโ€”such as her contributions to recommender systems and computer visionโ€”showcases her ability to address complex, real-world problems.

Professionally, Iustinaโ€™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.

๐ŸŽ“ 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.

๐Ÿ’ผ  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. Iustinaโ€™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.

๐Ÿ…Awards and Recognition 

Iustina Ivanovaโ€™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 climbersโ€™ recommender systems and sensor data analysis, have received wide acclaim for their innovation and real-world impact.

๐ŸŒ Research Skills On Computer Science

Iustina Ivanovaโ€™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.

๐Ÿ“– 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: 1158โ€“1164
  • How can we model climbersโ€™ future visits from their past records?
    • Authors: Ivanova, I., Wald, M.
    • Citation: UMAP 2023 โ€“ Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization
    • Year: 2023
    • Pages: 60โ€“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: 12โ€“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 โ€“ Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization
    • Year: 2022
    • Pages: 41โ€“45
  • Climbing Route Difficulty Grade Prediction and Explanation
    • Authors: Andric, M., Ivanova, I., Ricci, F.
    • Citation: ACM International Conference Proceeding Series
    • Year: 2021
    • Pages: 285โ€“292
  • Climber behavior modeling and recommendation
    • Author: Ivanova, I.
    • Citation: UMAP 2021 โ€“ Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization
    • Year: 2021
    • Pages: 298โ€“303
  • Knowledge-based recommendations for climbers
    • Authors: Ivanova, I., Andriฤ‡, 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 โ€“ Companion Publication of the 2020 International Conference on Multimodal Interaction
    • Year: 2020
    • Pages: 245โ€“249
  • Video and Sensor-Based Rope Pulling Detection in Sport Climbing
    • Authors: Ivanova, I., Andriฤ‡, M., Moaveninejad, S., Janes, A., Ricci, F.
    • Citation: MMSports 2020 โ€“ Proceedings of the 3rd International Workshop on Multimedia Content Analysis in Sports
    • Year: 2020
    • Pages: 53โ€“60