Ji Xu | Big Data Analytics | Best Researcher Award

Posted on by sciencefather

Prof. Ji Xu | Big Data Analytics | Best Researcher Award

Prof. Ji Xu, Guizhou University, China

Ji Xu (Mโ€™22) is an associate professor at the State Key Laboratory of Public Big Data, Guizhou University, China. He obtained his B.S. in Computer Science from Beijing Jiaotong University in 2004 and earned his Ph.D. in Computer Science from Southwest Jiaotong University in 2017. With expertise in data mining, granular computing, and machine learning, he has significantly contributed to the field through extensive research and publications. Dr. Xu has authored and co-authored over 30 papers in prestigious international journals, including IEEE TFS, IEEE TCYB, and Information Sciences. He also serves as a reviewer for top-tier journals like IEEE TNNLS, IEEE TFS, and Pattern Recognition. As an active member of IEEE, CCF, and CAAI, he remains at the forefront of technological advancements in artificial intelligence and big data analytics. His work continues to shape the future of intelligent computing and large-scale data processing.

Professional Profile

Google Scholar

Summary of Suitability for the Research for Best Researcher Award

Ji Xu is highly suitable for the โ€œResearch for Best Researcher Awardโ€ due to his impressive academic and professional achievements in the field of computer science, with a particular focus on data mining, granular computing, and machine learning. His educational background includes a Bachelorโ€™s degree from Beijing Jiaotong University and a Ph.D. from Southwest Jiaotong University, which demonstrate his foundational expertise in these critical fields. As an associate professor at the State Key Laboratory of Public Big Data at Guizhou University, Xu has a clear commitment to advancing research in his area of specialization.

Xuโ€™s research productivity further demonstrates his suitability for the award. He has authored over 30 peer-reviewed papers in prestigious international journals such as IEEE TFS, IEEE TCYB, IEEE JIoT, Information Sciences, and others. His contributions to these journals reflect his high-level expertise and ability to make significant advancements in his field. Furthermore, Xu has co-authored a book, showcasing his ability to synthesize and communicate complex ideas to a broader audience.

๐ŸŽ“ Education 

Ji Xuโ€™s academic journey began at Beijing Jiaotong University, where he obtained his Bachelor of Science (B.S.) in Computer Science in 2004. He later pursued advanced studies at Southwest Jiaotong University, earning his Doctor of Philosophy (Ph.D.) in Computer Science in 2017. His doctoral research focused on artificial intelligence, data mining, and computational intelligence, laying a strong foundation for his contributions to big data analytics. Throughout his academic career, he demonstrated exceptional analytical skills and a deep understanding of machine learning techniques. His education provided him with the technical expertise required to explore complex datasets and develop intelligent computing models. Additionally, his training at two leading Chinese universities equipped him with interdisciplinary knowledge in software engineering, algorithms, and large-scale data processing. His academic background remains a cornerstone of his professional research, guiding his work in advanced computational methods and innovative AI applications.

๐Ÿ’ผ Professional Experience

Dr. Ji Xu is currently an associate professor at the State Key Laboratory of Public Big Data, Guizhou University. In this role, he leads research in big data analytics, machine learning, and granular computing. His professional experience spans academia and research, with a focus on developing intelligent algorithms for large-scale data processing. Over the years, he has collaborated with industry and academia on high-impact projects related to artificial intelligence and computational intelligence. As an active member of IEEE, CCF, and CAAI, he contributes to the global research community through technical publications, conference presentations, and journal reviews. In addition to his research, he mentors graduate students, guiding them in innovative AI and data science projects. His expertise in handling complex data-driven challenges has established him as a prominent researcher in the field. Dr. Xuโ€™s work continues to influence advancements in big data and artificial intelligence applications.

๐Ÿ… Awards and Recognition

Dr. Ji Xu has received multiple accolades for his contributions to computer science, particularly in big data analytics, machine learning, and granular computing. He has been recognized for his research excellence through numerous best paper awards at international conferences. His extensive publication record in prestigious journals such as IEEE TFS, IEEE TCYB, and Neurocomputing has earned him a reputation as a leading researcher in artificial intelligence. Additionally, he serves as a reviewer for top-tier journals, including IEEE TNNLS, IEEE TFS, and Pattern Recognition, demonstrating his influence in shaping the field. As a distinguished member of IEEE, CCF, and CAAI, he actively participates in research communities and contributes to major advancements in computational intelligence. His innovative work in data science and AI continues to garner international recognition, positioning him among the top researchers driving the future of intelligent data processing and analytics.

๐ŸŒ Research Skills On Big Data Analytics

Dr. Ji Xuโ€™s research expertise encompasses data mining, granular computing, and machine learning. His ability to analyze large-scale datasets and develop intelligent algorithms has led to groundbreaking contributions in big data analytics. He specializes in computational intelligence, predictive modeling, and pattern recognition, applying advanced AI techniques to solve complex real-world problems. His skills extend to deep learning, natural language processing (NLP), and algorithm optimization, enabling him to create efficient data-driven solutions. With a strong foundation in mathematical modeling and statistical analysis, he excels in deriving meaningful insights from high-dimensional data. His role as a reviewer for IEEE TFS, IEEE TNNLS, and Pattern Recognition reflects his deep understanding of AI methodologies. Additionally, he collaborates on interdisciplinary projects, integrating AI with emerging technologies such as IoT and edge computing. His research continues to push the boundaries of artificial intelligence, transforming data analytics and intelligent systems.

๐Ÿ“– Publication Top Notes

  • DenPEHC: Density peak based efficient hierarchical clustering
    Authors: J Xu, G Wang, W Deng
    Journal: Information Sciences, 373, 200-218
    Citations: 142
    Year: 2016

  • A survey of smart water quality monitoring system
    Authors: J Dong, G Wang, H Yan, J Xu, X Zhang
    Journal: Environmental Science and Pollution Research, 22(7), 4893-4906
    Citations: 139
    Year: 2015

  • Granular computing: from granularity optimization to multi-granularity joint problem solving
    Authors: G Wang, J Yang, J Xu
    Journal: Granular Computing, 2(3), 105-120
    Citations: 138
    Year: 2017

  • Self-training semi-supervised classification based on density peaks of data
    Authors: D Wu, M Shang, X Luo, J Xu, H Yan, W Deng, G Wang
    Journal: Neurocomputing, 275, 180-191
    Citations: 130
    Year: 2018

  • Review of big data processing based on granular computing
    Authors: J Xu, GY Wang, H Yu
    Journal: Chinese Journal of Computers, 38(8), 1497-1517
    Citations: 59
    Year: 2015

  • ๅŸบไบŽ็ฒ’่ฎก็ฎ—็š„ๅคงๆ•ฐๆฎๅค„็† (Big Data Processing Based on Granular Computing)
    Authors: ๅพ่ฎก (J Xu), ็Ž‹ๅ›ฝ่ƒค (G Wang), ไบŽๆดช (H Yu)
    Journal: ่ฎก็ฎ—ๆœบๅญฆๆŠฅ (Chinese Journal of Computers), 38(8), 1497-1517
    Citations: 50
    Year: 2015

  • Fat node leading tree for data stream clustering with density peaks
    Authors: J Xu, G Wang, T Li, W Deng, G Gou
    Journal: Knowledge-Based Systems, 120, 99-117
    Citations: 44
    Year: 2017

  • Piecewise two-dimensional normal cloud representation for time-series data mining
    Authors: W Deng, G Wang, J Xu
    Journal: Information Sciences, 374, 32-50
    Citations: 40
    Year: 2016

  • A multi-granularity combined prediction model based on fuzzy trend forecasting and particle swarm techniques
    Authors: W Deng, G Wang, X Zhang, J Xu, G Li
    Journal: Neurocomputing, 173, 1671-1682
    Citations: 37
    Year: 2016

  • Local-Density-Based Optimal Granulation and Manifold Information Granule Description
    Authors: J Xu, G Wang, T Li, W Pedrycz
    Journal: IEEE Transactions on Cybernetics
    Citations: 28
    Year: 2017

SAMEERCHAND PUDARUTH | Artificial Intelligence | Academic Excellence Award

Posted on by sciencefather

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.

Professional Profile

Scopus 

Orcid

Google Scholar

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. Pudaruthโ€™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. Pudaruthโ€™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 โ€œPython in One Weekโ€ (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. Pudaruthโ€™s research continues to influence academia, industry, and public policy, making AI more accessible and applicable across diverse domains.

 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

Ghulam Mohi-ud-din | AI | Best Researcher Award

Posted on by sciencefather

Prof. Ghulam Mohi-ud-din | AI | Best Researcher Award

๐Ÿ‘ค Prof. Ghulam Mohi-ud-din, Northwestern Polytechnical University, China

Ghulam Mohi-ud-din is a highly skilled and accomplished professional in Software Engineering and Computer Science. Born in Rawalpindi, Pakistan, he has garnered extensive international experience in academia and industry. Holding a PhD in Software Engineering from the University of Florida, he has contributed to the field through teaching, research, and product development roles. With experience at prestigious institutions such as IBM, Oracle, and Nanchang Hangkong University, Ghulamโ€™s work focuses on Artificial Intelligence, Machine Learning, and Software Engineering. His expertise in developing and coordinating large-scale projects and mentoring students has earned him recognition in the tech community.

Professional Profile

Orcid

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

Ghulam Mohi-ud-din is highly suitable for the Research for Best Researcher Award due to his extensive academic background, international exposure, and remarkable contributions to the fields of software engineering, artificial intelligence, and computer science. He has obtained a Ph.D. in Software Engineering from the prestigious University of Florida, USA, further solidifying his academic expertise. His earlier degrees, including a Masterโ€™s in Computer Science from the University of Florida and a Bachelorโ€™s in Software Engineering from the University of Arizona, reflect his strong foundation in both theoretical and practical aspects of software development.

His professional journey demonstrates a unique combination of teaching, research, and industry experience. As a faculty member at Nanchang Hangkong University in China, he has significantly impacted studentsโ€™ learning in areas such as Artificial Intelligence, Machine Learning, and Software Engineering.

๐ŸŽ“ Education

Ghulam Mohi-ud-dinโ€™s educational journey is marked by excellence in software engineering and computer science. He completed his PhD in Software Engineering from the University of Florida, USA, in January 2022, furthering his research in Artificial Intelligence. Prior to this, he obtained his Master of Science in Computer Systems Networking and Telecommunications from the same university in 2010. His academic career began with a Bachelor of Science in Software Engineering from the University of Arizona, USA, in 2007. Throughout his studies, Ghulam consistently demonstrated a strong aptitude for problem-solving and innovative thinking, especially in areas involving AI and data communication. His educational background laid a robust foundation for his subsequent professional achievements.

 ๐Ÿ’ผ  Professional Experience

Ghulam Mohi-ud-dinโ€™s career spans academia and industry, where he has made significant contributions. He currently serves as a faculty member at Nanchang Hangkong University in China, teaching courses in Artificial Intelligence, Machine Learning, Software Engineering, and Networking. Before this, he was a Product Development Coordinator at ResearchEx Ltd. in London, managing project costs, schedules, and performance. His previous roles at IBM as a Data Administrator and at Oracle Corporation as a Database Administrator allowed him to develop expertise in database management, system administration, and project coordination. Additionally, Ghulam has extensive experience in mentoring students, overseeing research projects, and securing funding for various academic initiatives. His work reflects a blend of technical knowledge and practical application, making him a key player in both academia and the technology industry.

๐Ÿ… Awards and Recognition

Throughout his career, Ghulam Mohi-ud-din has earned numerous accolades and recognition for his exceptional work in software engineering and academia. His research contributions in Artificial Intelligence and Machine Learning have been widely recognized in both academic and professional circles. He has successfully secured funding for various research projects, including a $25,000 grant for his work at Oracle Corporation. His leadership in the academic community, particularly in teaching and mentoring students, has made a lasting impact. Additionally, Ghulamโ€™s innovative work in database management and system administration at IBM and Oracle garnered praise for its strategic insights and efficiency. His dedication to advancing technology and education has positioned him as a respected figure in the field of computer science.

๐ŸŒ Research Skills On AI

Ghulam Mohi-ud-din possesses a robust skill set in software engineering and artificial intelligence research. His expertise spans data analysis, machine learning, AI algorithms, and system architecture. He is proficient in applying research methodologies to develop innovative solutions in complex technological fields, including network communications and software testing. Throughout his academic and professional career, he has demonstrated an exceptional ability to design and execute research projects that lead to meaningful outcomes, including published papers and conference presentations. His work involves creating security protocols, optimizing system performance, and contributing to cutting-edge AI research. Ghulam is also skilled at managing interdisciplinary teams, coordinating projects, and mentoring students to foster research excellence. His research is characterized by a blend of theoretical knowledge and practical application, making him a versatile and accomplished researcher in his field.

๐Ÿ“– Publication Top Notes

  • A Wireless Sensor Network for Coal Mine Safety Powered by Modified Localization Algorithm
    • Authors: Hafiz Zameer ul Hassan, Anyi Wang, Ghulam Mohi-ud-din
    • Citation: Heliyon (2024-12)
  • Click-level Supervision for Online Action Detection Extended from SCOAD
    • Authors: Xiang Zhang, Yuhan Mei, Ye Na, Xia Ling Lin, Genqing Bian, Qingsen Yan, Ghulam Mohi-ud-din, Chen Ai, Zhou Li, Wei Dong
    • Citation: Future Generation Computer Systems (2024-12)
  • Unmanned Aerial Vehicle Intrusion Detection: Deep-meta-heuristic System
    • Authors: Shangting Miao, Quan Pan, Dongxiao Zheng, Ghulam Mohi-ud-din
    • Citation: Vehicular Communications (2024-04)
  • Real-time Portrait Image Retouching Extended from DualBLN
    • Authors: Xiang Zhang, Dawei Yan, Genqing Bian, Chengzhe Lu, Sifei Wang, Ghulam Mohi-ud-din, Qingsen Yan, Wei Dong
    • Citation: Expert Systems with Applications (2024-03)
  • Intrusion Detection Using Hybrid Enhanced CSA-PSO and Multivariate WLS Random-Forest Technique
    • Authors: Ghulam Mohi-ud-din, Liu Zhiqiang, Zheng Jiangbin, Wang Sifei, Lin Zhijun, Muhammad Asim, Yuxuan Zhong, Yuxin Chen
    • Citation: IEEE Transactions on Network and Service Management (2023-12)
  • Intrusion Detection Using Hybridized Meta-heuristic Techniques with Weighted XGBoost Classifier
    • Authors: Ghulam Mohiuddin, Zhijun Lin, Jiangbin Zheng, Junsheng Wu, Weigang Li, Yifan Fang, Sifei Wang, Jiajun Chen, Xinyu Zeng
    • Citation: Expert Systems with Applications (2023-12)
  • Intrusion Detection in Wireless Sensor Network Using Enhanced Empirical Based Component Analysis
    • Authors: Liu Zhiqiang, Ghulam Mohiuddin, Zheng Jiangbin, Muhammad Asim, Wang Sifei
    • Citation: Future Generation Computer Systems (2022-10)
  • NIDS: Random Forest Based Novel Network Intrusion Detection System for Enhanced Cybersecurity in VANETโ€™s
    • Authors: Ghulam Mohi-ud-din, Jiangbin Zheng, Zhiqiang Liu, Muhammad Asim, Jiajun Chen, Jinjing Liu, Zhijun Lin
    • Citation: 2022 International Conference on Virtual Reality, Human-Computer Interaction and Artificial Intelligence (VRHCIAI) (2022-10)
  • A Novel Deep Learning-Based Security Assessment Framework for Enhanced Security in Swarm Network Environment
    • Authors: Zhiqiang Liu, Ghulam Mohi-ud-din, Jiangbin Zheng, Sifei Wang, Muhammad Asim
    • Citation: International Journal of Critical Infrastructure Protection (2022-09)
  • Modeling Network Intrusion Detection System Using Feed-Forward Neural Network Using UNSW-NB15 Dataset
    • Authors: Liu Zhiqiang, Ghulam Mohi-ud-din, Li Bing, Luo Jianchao, Zhu Ye, Lin Zhijun
    • Citation: 2019 IEEE 7th International Conference on Smart Energy Grid Engineering (SEGE) (2019-08)

Iustina Ivanova | Computer Science | Best Researcher Award

Posted on by sciencefather

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.

Professional Profile

Scopus

Orcid

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