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

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

👤 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, Ghulam’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

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🌟  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 Master’s in Computer Science from the University of Florida and a Bachelor’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 students’ learning in areas such as Artificial Intelligence, Machine Learning, and Software Engineering.

🎓 Education

Ghulam Mohi-ud-din’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.

 💼  Professional Experience

Ghulam Mohi-ud-din’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.

🏅 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, Ghulam’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.

🌍 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.

📖 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 VANET’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

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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