Alimul Rajee | Computer Science | Young Scientist Award

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Mr. Alimul Rajee | Computer Science | Young Scientist Award

Mr. Alimul Rajee, Dept. of ICT, Comilla University, Kotbari, Bangladesh

Alimul Rajee is a Lecturer at the Department of Information and Communication Technology, Comilla University. His academic journey includes a stellar performance with a CGPA of 3.69 in his M.Sc. in Information Technology from Jahangirnagar University. Rajee’s research interests span Machine Learning, Data Science, Artificial Intelligence, Cyber Security, and Robotics, with a focus on real-world applications such as traffic accident data analysis and smart waste management. He has contributed significantly to several research projects, and his work has been published in prestigious journals, such as Knowledge-Based Systems and Heliyon. In addition to his research, Rajee is an active educator, mentoring students and supervising projects in areas like IoT and deep learning. His dedication extends beyond the classroom to extracurricular activities, where he has received multiple awards and recognitions, including an international award for his project at Fujitsu Research Institute in Tokyo.

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Suitability Summary of Young Scientist Awards

Alimul Rajee stands out as an excellent candidate for the Research for Young Scientist Award due to his impressive academic achievements, significant research contributions, and commitment to advancing in the fields of Machine Learning, Data Science, Artificial Intelligence, Cyber Security, and IoT. He has a strong educational background, earning his M.Sc. and B.Sc. with high CGPA rankings from Jahangirnagar University, which reflects his deep knowledge and dedication to his field.

Rajeeโ€™s research work is highly commendable, with several publications in reputable, Scopus-indexed journals such as Knowledge-Based Systems and Heliyon, where he has contributed to the development of novel algorithms and methodologies, especially in big data analysis, sentiment analysis, and AI-based applications. His ongoing and completed research projects, including a hybrid smart waste management system and aspect-based sentiment analysis for Bengali text, further showcase his innovative thinking and practical application of emerging technologies to address real-world problems. Additionally, his leadership in supervising over 40 academic projects and his participation in global training programs, like those held at the Fujitsu Research Institute in Japan, illustrate his proactive approach to both learning and teaching.

๐ŸŽ“ย ย Education

Alimul Rajee completed his M.Sc. in Information Technology from Jahangirnagar University, securing a CGPA of 3.69 out of 4, ranking 6th in his batch. Before this, he earned his B.Sc. (Hons.) in the same field, also from Jahangirnagar University, with a CGPA of 3.71, again securing the 6th position. Rajee’s academic excellence dates back to his secondary education, where he achieved the highest CGPA of 5.00 in both his HSC and SSC exams from Govt. Ananadamohan College and Islamnagar Sailampur High School. His continuous pursuit of academic excellence earned him merit-based scholarships throughout his education. His academic prowess has laid a strong foundation for his research and professional career, as he continues to excel in his field with a focus on cutting-edge technologies such as AI and IoT.

๐Ÿ’ผย Professional Experience

Alimul Rajee’s professional career began as a Junior Data Scientist at Oculin Tech BD Ltd., where he worked from March 2020 to May 2021. He then served as a Senior Officer (ICT) at Sonali Bank PLC for a brief period before becoming a Lecturer at Comilla University in November 2021, where he currently teaches. Rajee’s teaching journey includes roles at Bangladesh University of Business and Technology (BUBT) and Jahangirnagar University (IIT-JU), where he was a Teacher Assistant. His extensive experience also includes supervising over 40 academic projects focused on machine learning, deep learning, and IoT. As an educator, he fosters a positive learning environment, guiding students through complex technical concepts while contributing to the development of innovative research and real-world applications.

๐Ÿ…ย ย Awards and Recognition

Alimul Rajee’s achievements have been recognized at both national and international levels. He has received several awards, including the UGC Research Grant from Comilla University for consecutive fiscal years, which is a testament to his research capabilities. Rajeeโ€™s work has been recognized by prestigious institutions such as Fujitsu Research Institute (FRI) in Tokyo, where his final project won 1st prize. He has also been a reviewer for the International Conference on Embracing Industry 4.0 for Sustainable Business Growth. His consistent academic and research excellence has earned him regular merit-based scholarships and fellowships, such as the National Science & Technology Fellowship from the ICT Division of Bangladesh.

๐ŸŒย Research Skills On Computer Science

Alimul Rajee specializes in the application of cutting-edge technologies such as Machine Learning, Artificial Intelligence, Cyber Security, and IoT. His research includes a diverse range of topics like traffic accident data analysis, sentiment analysis of Bengali text, and smart waste management. Rajee has honed his expertise in Data Science and deep learning methods, contributing to several high-impact publications in renowned journals such as Knowledge-Based Systems and Heliyon. His current research projects include Aspect-Category-Opinion-Sentiment Quad Extraction for Bengali Text and a Hybrid Smart Waste Management Technique using Deep Learning and IoT. Rajee’s proficiency in data analysis, algorithm design, and system integration showcases his strong research skills and his commitment to advancing technology for societal benefit.

๐Ÿ“– Publication Top Notes

  • “Aspect-based sentiment analysis for Bengali text using bidirectional encoder representations from transformers (BERT)”
    • Authors: MM Samia, A Rajee, MR Hasan, MO Faruq, PC Paul
    • Citation: International Journal of Advanced Computer Science and Applications, 13(12)
    • Year: 2022
  • “Detecting the provenance of price hike in agri-food supply chain using private Ethereum blockchain network”
    • Authors: MH Sayma, MR Hasan, M Khatun, A Rajee, A Begum
    • Citation: Heliyon, 10(11)
    • Year: 2024
  • “Analyzing depression on social media utilizing machine learning and deep learning methods”
    • Authors: PC Paul, MT Ahmed, MR Hasan, A Rajee, K Sultana
    • Citation: Indian Journal of Computer Science and Engineering, 14(5), 740-746
    • Year: 2023
  • “WFFSโ€”An ensemble feature selection algorithm for heterogeneous traffic accident data analysis”
    • Authors: A Rajee, MS Satu, MZ Abedin, KMA Ali, S Aloteibi, MA Moni
    • Citation: Knowledge-Based Systems, 113089
    • Year: 2025

SAMEERCHAND PUDARUTH | Artificial Intelligence | Academic Excellence Award

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Assoc. Prof. Dr. SAMEERCHAND PUDARUTH | Artificial Intelligence | Academic Excellence Award

Assoc. Prof. Dr. SAMEERCHAND PUDARUTH, University of Mauritius, Mauritius

Dr. Sameerchand Pudaruth is an Associate Professor in the Faculty of Information, Communication & Digital Technologies at the University of Mauritius. With a PhD in Artificial Intelligence, his expertise spans machine learning, computational linguistics, and data science. His academic journey reflects a deep commitment to technological advancement and knowledge dissemination. Having served as Head of the ICT Department (2019โ€“2021), he played a key role in shaping academic policies and research initiatives. Dr. Pudaruth is an accomplished author and a sought-after researcher, contributing significantly to AI, distributed systems, and digital transformation. His membership in prestigious organizations such as IEEE, ACM, and IAENG highlights his standing in the global research community. Beyond academia, he is dedicated to mentoring students, fostering innovation, and driving interdisciplinary collaboration in AI. His work continues to bridge the gap between theoretical research and practical AI applications, making significant strides in Mauritius and beyond.

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Suitability for the Research for Best Researcher Award โ€“ Associate Professor Dr. Sameerchand Pudaruth

Dr. Sameerchand Pudaruth is a distinguished academic and researcher in Artificial Intelligence, Computer Science, and related fields, with a strong background in teaching, research, and leadership. With over two decades of experience, he has contributed significantly to the advancement of AI, distributed systems, multimedia, and computational linguistics. His PhD in Artificial Intelligence, combined with his legal studies, positions him uniquely at the intersection of AI and law, demonstrating an interdisciplinary approach to research.

His extensive publication record, including book chapters, conference proceedings, and journal articles, highlights his dedication to pushing the boundaries of AI, machine learning, and computational methodologies. His research contributions in legal text classification, intelligent systems, and IT support services optimization have real-world applications, making his work both academically rigorous and practically relevant. His leadership roles, including serving as Head of the ICT Department and holding senior positions in IEEE and ACM, reflect his commitment to advancing research and fostering collaboration in the global research community.

๐ŸŽ“ Education

Dr. Sameerchand Pudaruth holds a PhD in Artificial Intelligence from the University of Mauritius, awarded in 2020, focusing on AI-driven decision-making systems. His academic portfolio includes an MSc in Computer Science with a specialization in Distributed Systems and Multimedia (2004โ€“2006) and a BSc (Hons) in Computer Science and Engineering (First Class) from the same institution (2000โ€“2003). In addition, he pursued legal studies, earning an LLB from the University of London (2009โ€“2012) and completing the Law Practitionerโ€™s Vocational Course (2013). This diverse educational background equips him with a unique interdisciplinary perspective, blending AI, computational intelligence, and legal analytics. His continuous professional development is evident through active participation in research forums, conferences, and international collaborations. Dr. Pudaruth’s academic journey reflects a commitment to lifelong learning, innovation, and thought leadership in artificial intelligence and digital technologies.

๐Ÿ’ผ Professional Experience

Dr. Sameerchand Pudaruth has been an integral part of the University of Mauritius since 2007. Currently serving as an Associate Professor (since 2022), he previously held the positions of Senior Lecturer (2016โ€“2022) and Lecturer (2007โ€“2016). He also served as Head of the ICT Department (2019โ€“2021), where he spearheaded academic advancements and research collaborations. His career is marked by expertise in AI, machine learning, and data-driven technologies, leading various projects focused on intelligent systems. He has mentored numerous postgraduate students and contributed extensively to curriculum development. Dr. Pudaruth’s industry collaborations have reinforced his reputation as a pioneer in applied AI research. His leadership in conferences and symposiums underscores his commitment to advancing knowledge in computational sciences. As an educator, researcher, and innovator, he continuously pushes the boundaries of AI applications, influencing both academia and industry.

๐Ÿ… Awards and Recognition

Dr. Sameerchand Pudaruthโ€™s contributions to AI and computational research have earned him numerous accolades. He has been a Senior IEEE Member since 2020, recognizing his significant professional achievements. His role as a founding member and Vice-Chair of IEEE Mauritius Section (2018โ€“2021) highlights his leadership in fostering AI research communities. He has received research grants and recognition for outstanding publications in AI, machine learning, and computational linguistics. His book “Python in One Week” (2010) and multiple Springer book chapters have cemented his reputation in AI education. His work on machine learning applications in law and data science has been widely cited, further amplifying his global impact. His membership in ACM, IAENG, and the Association for Computational Linguistics reflects his standing in the international AI research community. Through groundbreaking research, academic leadership, and scholarly contributions, Dr. Pudaruth continues to be a driving force in AI innovation.

๐ŸŒ Research Skills On Artificial Intelligence

Dr. Sameerchand Pudaruth specializes in artificial intelligence, machine learning, and computational linguistics. His expertise spans natural language processing, legal informatics, and AI-driven decision-making models. He has pioneered research in AI applications for law, healthcare, and distributed systems. With a deep understanding of neural networks, deep learning, and intelligent automation, he has contributed significantly to AI-driven knowledge systems. His work includes feature selection using evolutionary algorithms, predictive modeling, and sentiment analysis. He has led interdisciplinary collaborations to advance AI ethics, data privacy, and algorithmic fairness. His ability to translate complex AI concepts into real-world applications has led to impactful research publications. As a member of international AI organizations, he remains at the forefront of technological advancements, constantly exploring innovative solutions. Dr. Pudaruth’s research continues to influence academia, industry, and public policy, making AI more accessible and applicable across diverse domains.

ย ๐Ÿ“– Publication Top Notes

  1. Plant leaf recognition using shape features and colour histogram with K-nearest neighbour classifiers
    • Authors: T. Munisami, M. Ramsurn, S. Kishnah, S. Pudaruth
    • Citations: 262
    • Year: 2015
  2. People factors in agile software development and project management
    • Authors: V. Lalsing, S. Kishnah, S. Pudaruth
    • Citations: 195
    • Year: 2012
  3. Predicting the price of used cars using machine learning techniques
    • Authors: S. Pudaruth
    • Citations: 183
    • Year: 2014
  4. Automatic Recognition of Medicinal Plants using Machine Learning Techniques
    • Authors: A. Begue, V. Kowlessur, U. Singh, F. Mahomoodally, S. Pudaruth
    • Citations: 123
    • Year: 2017
  5. A review of mobile ad hoc NETwork (MANET) Protocols and their Applications
    • Authors: D. Ramphull, A. Mungur, S. Armoogum, S. Pudaruth
    • Citations: 98
    • Year: 2021
  6. Authorship attribution using stylometry and machine learning techniques
    • Authors: H. Ramnial, S. Panchoo, S. Pudaruth
    • Citations: 71
    • Year: 2016
  7. Sentiment analysis from Facebook comments using automatic coding in NVivo 11
    • Authors: S. Pudaruth, S. Moheeputh, N. Permessur, A. Chamroo
    • Citations: 53
    • Year: 2018
  8. Forgotten, excluded or included? Students with disabilities: A case study at the University of Mauritius
    • Authors: U. Singh, S. Pudaruth, R. Gunputh
    • Citations: 30
    • Year: 2017
  9. Resource allocation in 4G and 5G networks: A review
    • Authors: L.N. Degambur, A. Mungur, S. Armoogum, S. Pudaruth
    • Citations: 29
    • Year: 2021
  10. SuperFish: A Mobile Application for Fish Species Recognition using Image Processing Techniques and Deep Learning
  • Authors: P. Sameerchand, N. Nadeem, A. Chandani, K. Somveer, V. Munusami, S. Pudaruth
  • Citations: 26
  • Year: 2021

Iustina Ivanova | Computer Science | Best Researcher Award

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Mrs. Iustina Ivanova | Computer Science | Best Researcher Award

๐Ÿ‘คย 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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๐ŸŒŸย 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 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, 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.

๐ŸŽ“ย 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’ผย ย Professional Experienceย 

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.

๐Ÿ…Awards and Recognitionย 

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 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: 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 – 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 – 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 – 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 – Proceedings of the 3rd International Workshop on Multimedia Content Analysis in Sports
    • Year: 2020
    • Pages: 53โ€“60