Symposium Series

School of Mining and Geosciences, Nazarbayev University

Symposium Chair: Dr. Mian Umer Shafiq, Assistant Professor in Nazarbayev University

The symposium “Application of Machine Learning in Engineering” was held on August 19, 2025, at the School of Mining and Geosciences, Nazarbayev University. By providing data-driven solutions to complex problems in engineering, especially focusing on branches of petroleum engineering like exploration, drilling, production, and energy transition, machine learning (ML) is quickly revolutionizing the industry. ML focuses on algorithms that learn from data to gradually increase performance. It has established itself as an essential tool for improving safety, reducing costs, and enhancing operational efficiency due to its ability to process large datasets, uncover hidden patterns, and generate predictive insights. Applications of machine learning in petroleum engineering include predicting reservoir properties like porosity and permeability, optimizing drilling by predictive modeling of parameters like stress and penetration rate, and accelerating reservoir simulation and history matching. By forecasting critical characteristics like viscosity in H₂–cushion gas mixtures, which is crucial for assessing injectivity and storage capacity, machine learning (ML) supports hydrogen geological storage in the context of energy transition. For example, gradient boosting regression models have demonstrated great accuracy in viscosity prediction, saving time and money in comparison to laboratory testing. AI and ML have potential for future developments in real-time analytics, autonomous operations, and sustainability objectives. The oil and gas sector may become more innovative, resilient, and efficient by combining physical models with intelligent algorithms.

Beijing Computer Federation Blockchain and Digital Finance Specialized Committee

Symposium Chair: Prof. Wang Juan, Postdoctoral fellow at the University of Florida, and director of the Beijing Computer Federation

On June 7, 2025, the 2nd Workshop on Blockchain and Financial Technology — Beijing Symposium of the 7th International Conference on Computing and Data Science — was successfully convened.

This academic event was co-organized by the Beijing Computer Federation, with ETHPanda, LXDAO, and OurTinTinLand serving as the main organizers. It received additional support from Yidawi Academic Press, the Blockchain Association of Beijing University of Posts and Telecommunications, the Center for Network Emergency and Informatization Research at Peking University, and the Center for Market Economy Research at Peking University. The forum brought together experts and scholars from diverse fields including law, scientific research, software development, and infrastructure technology.

The symposium featured in-depth discussions on cutting-edge topics in blockchain technology. Jiaqi Huang presented a jurisprudential framework for resolving disputes arising from smart contracts. A system architect from HashKey Chain examined regulatory and compliance challenges related to real-world assets (RWA). An ambassador from EigenLayer introduced the modular security architecture of the restaking mechanism. Shuxun Wang, a graduate student at the Institute of Automation, Chinese Academy of Sciences, showcased AI applications for cross-modal retrieval of NFTs. A contributor from LXDAO discussed the significance of solo staking from the perspective of decentralization. Moreover, scalable solutions for parallel EVM (Ethereum Virtual Machine) architecture were also elaborated upon.

This symposium served as an important platform for advancing academic exchange and fostering deep integration among industry, academia, and research institutions. It contributed meaningfully to both theoretical innovation and practical application in the domains of blockchain and financial technology.