Assoc. Prof. Khaled Mohamed
Kazakh-British Technical University (KBTU), Kazakhstan

Biography: Dr. Khaled Mohamed is an Associate Professor at the School of Information Technology and Engineering, Kazakh-British Technical University (KBTU), Almaty, Kazakhstan. He received his Ph.D. in Materials Science and Engineering from the University of the Witwatersrand, South Africa. With over a decade of academic and research experience, his work focuses on artificial intelligence, machine learning, environmental informatics, renewable energy systems, computational materials science, and data-driven modeling.
His current research interests include deep learning, explainable AI (XAI), physics-informed machine learning, time-series forecasting, air quality prediction, intelligent energy systems, and AI for climate and environmental sustainability. He has authored numerous peer-reviewed publications in leading international journals, including Applied Energy, Applied Thermal Engineering, and Clean Energy. He is also the inventor of a U.S. patent on a high-efficiency parabolic trough solar receiver technology for concentrated solar power applications.
Dr. Mohamed serves as a reviewer and editorial board member for several international journals and has contributed to the technical committees of international conferences. His research aims to advance trustworthy and impactful AI solutions for sustainable energy, environmental monitoring, and climate resilience.

Senior Lecturer Aawag Mohsen Alawag,
Universiti Teknologi MARA (UiTM), Malaysia

Speech Title: An Artificial Intelligence-Driven Intelligent Information System for Construction Risk Prediction and Project Performance Decision Support

Abstract: The increasing complexity of construction projects generates substantial volumes of heterogeneous information related to project schedules, costs, resources, site conditions, and risk events. Although project teams collect substantial amounts of information throughout the construction process, this information is often scattered across different systems and is not fully utilised to anticipate potential risks. Traditional risk management approaches also tend to depend heavily on expert judgement and past experience, making it difficult to identify emerging problems before they significantly affect project outcomes. Artificial intelligence (AI) offers an opportunity to address these challenges by analysing project data, identifying risk patterns, and supporting more informed decision-making. This study proposes an AI-driven intelligent information system that integrates construction risk prediction with project performance management. The proposed system aims to bring together relevant project information, including historical records, cost and schedule data, and identified risk factors, to assess potential threats and their implications for project performance. Machine learning techniques will be considered to identify patterns in project data and predict possible delays, cost overruns, and performance deviations. The system will also incorporate explainable AI to help project managers understand the factors influencing predictions and assess the reliability of the generated insights. Rather than replacing professional judgement, the system is intended to complement the experience of construction professionals by providing timely, data-informed insights for risk assessment and mitigation planning. Particular attention will be given to data quality, the interpretability of AI outputs, and the reliability of the proposed approach. By connecting AI-based prediction with practical project management needs, this study aims to establish a foundation for more proactive and intelligent construction risk management. The proposed framework contributes to the application of AI and intelligent information systems in the construction sector, with future empirical evaluation needed to assess its predictive performance and practical value.

Biography: Ts. Dr. Aawag Mohsen Alawag is a Senior Lecturer in the Faculty of Civil Engineering at Universiti Teknologi MARA (UiTM), Malaysia. He holds a PhD in Civil and Environmental Engineering from Universiti Teknologi PETRONAS and is a Professional Technologist registered with the Malaysia Board of Technologists. His research focuses on construction project management, building information modelling, and the application of artificial intelligence to construction risk prediction and project decision support.

Dr. Jacek Nazdrowicz
Fujitsu Global Delivery Center, Poland

PhD, MScs of Physics, Math, Computer Sciences, Management, Electronics, Power Energy
IEEE Member.
From 2016: Fujitsu GDC:
Senior Domain Architect in Fujitsu GDC in Poland
System Engineer Expert – Storage Area Networks, Backup Systems,
Regional Fujitsu Distinguished Engineer,
Global Fujitsu Distinguished Engineer – Network
Previously: Large polish bank: Administrator of Opens Systems
Researcher and Lecturer at Lodz University of Technology – Electronics and Computer Sciences
Publications in IEEE, presenter at IEEE conferences (USA, Europe), conducting lectures in many universities in Japan, Iceland, Norway, Finland, Spain, Croatia.

Dr. John Ivan C. Maurat
National University Manila, Philippines

Biography: Dr. John Ivan C. Maurat is an Information Technology educator with more than seven years of experience in teaching IT professional and core courses in higher education. He earned his Bachelor of Science in Information Technology, Master of Information Technology, and Doctorate in Information Technology with a specialization in Social Computing from National University Manila. He is also a Green Belt Lean Six Sigma Certified professional and a Microsoft Innovative Educator Expert.
Driven by a strong commitment to academic excellence, Dr. Maurat continuously integrates research, innovation, and emerging technologies into teaching and learning practices to create meaningful, engaging, and impactful educational experiences. His research interests and scholarly contributions cover diverse areas such as artificial intelligence-assisted learning in programming education, educational game development, smart systems, sentiment analysis, augmented and virtual learning environments, social network analysis, learning analytics, and digital transformation in education.
Currently serving as an Assistant Professor 4 at National University Manila, Dr. Maurat has authored and co-authored numerous research studies that demonstrate his dedication to innovation, inclusive education, and the advancement of technology-driven learning in the digital age.

Invited Speakers of ICINT2026

Prof. Yutaka Ishibashi (Fellow of IEICE) Aichi Sangyo University, Japan	Assoc. Prof. Miloslava (Mia) Plachkinova Kennesaw State University, USA	Prof. S. Balakrishnan Vinayaka Mission's Research Foundation (Deemed to be University), India	Prof. Tariq Rahim Soomro Institute of Business Management, Pakistan	Prof. Anand Nayyar Duy Tan University, Vietnam

Prof. Hans-Henrik Hvolby act2learn, Denmark	Assoc. Prof. Herminiño C. Lagunzad National University, Philippines	Prof. Samuel Boateng Marymount University, USA	Prof. Kazuyuki Shimizu Meiji University, Japan	Assoc. Prof. Topside E. Mathonsi Tshwane University of Technology, South Africa

Assoc. Prof. T. Velmurugan University of Madras, India	Assoc. Prof. Wei-Min Huang National Chung Cheng University, Taiwan	Asst. Prof. John Ivan C. Maurat National University, Philippines	Dr. Sanjeev Shukla Indian Institute of Technology Roorkee, India	Dr.Judhistir Mahapatro National Institute of Technology (NIT) Rourkela, India

Asst. Prof Basheer M. Al-Ghazali King Fahd University of Petroleum & Minerals, Saudi Arabia	Asst. Prof. Mohammed Alaa Ala'anzy SDU University, Kazakhstan	Asst. Prof. Roger C. Primo Jr. National University, Philippines	Dr. Jacek Nazdrowicz Fujitsu Global Delivery Center, Poland	Dr. J. JANET Aarupadai Veedu Institute of Technology Chennai, India