Professor, Qingdao Huanghai University | Adjunct Postdoctoral Scholar & Adjunct Member of the Faculty of Graduate Studies, Dalhousie University | Software Engineering · AI · Blockchain
Dr. Christian Gang Liu (刘玄睿) is an Adjunct Postdoctoral Scholar in the Faculty of Computer Science and an Adjunct Member of the Faculty of Graduate Studies at Dalhousie University. While holding these Dalhousie appointments, he has also served, since July 2026, as a Professor in the School of Information Science and Engineering at Qingdao Huanghai University.
His work is on model-driven generation of smart contracts. The DE-HSM multi-modal model and the TABS, TABS+ and TABS+R tools turn BPMN and DMN models into executable smart contracts that support long-term transactions, nested collaborative transactions, and upgrade and repair of deployed contracts. Results appear in ACM Distributed Ledger Technologies (2024), Elsevier Blockchain: Research and Applications (2023, 2025), Future Internet (2026) and at IEEE and ACM conferences.
He led a Mitacs Accelerate project on long-term transactions in smart contracts for small and medium-sized enterprises (SMEs). In a separate project, he worked with Peer Ledger Inc. on CANVerify, a verifiable-credential system for supplier qualification used by Public Services and Procurement Canada; it passed the W3C Verifiable Credentials 2.0 conformance suite in July 2026.
He holds a Ph.D. (2024) and an M.Sc. (2021) in Computer Science from Dalhousie University, a Master of Applied Computer Science from Concordia University (2007), and a Master of Engineering from Huazhong University of Science and Technology (2003). Before returning to research he spent more than twenty years in industry at Ericsson, CGI and IBM in Canada and at Samsung in China. From 2018 to 2024 he taught databases, cloud computing, business intelligence and rapid prototyping at Dalhousie and Saint Mary's University, and created Dalhousie's first accredited blockchain course, CSCI 6313.
Reviewer for the following journals (18 verified reviews, 2024–2026, recorded on ORCID):
2026
Multi-Stage Payments in a Smart Contract as a Service from BPMN Models
Liu, C. G.; Bodorik, P.; Jutla, D.
2026 IEEE International Conference on Digital Transformation and Intelligent Society (IEEE DTISO 2026), Barcelona, Spain, 17–20 November 2026.
Accepted for oral presentation (IEEE, EI indexed); to appear.
Compliance-Gated Payments in Smart Contract as a Service from BPMN Models
Liu, C. G.; Bodorik, P.; Jutla, D.
2026 IEEE International Conference on Cybersecurity Systems (IEEE CCSS 2026), Paris, France, October 2026.
Accepted as a full paper for oral presentation (IEEE, EI indexed); to appear.
TAEKR: A Computational Framework for Cross-Lingual Knowledge Divergence Analysis
Liu, C. G.
2026 IEEE 11th International Conference on Computational Intelligence and Applications (IEEE ICCIA 2026), Qingdao, China, 14–16 August 2026. Paper A529.
Accepted as a full paper; presented orally (IEEE, EI indexed); to appear.
Liu, C. G.; Bodorik, P.; Jutla, D.
Future Internet, 18(2): 110. February 2026.
2025
Liu, C. G.; Bodorik, P.; Jutla, D.
In 5th Intelligent Cybersecurity Conference (ICSC 2025). 2025. (8 pages)
Liu, C. G.; Bodorik, P.; Jutla, D.
Elsevier Journal of Blockchain: Research and Applications, 100285. September 2025.
Impact Factor: 6.9 | CiteScore: 11.3
In our previous research, we addressed the problem of automated transformation of models, represented using the Business Process Model and Notation (BPMN) standard, into the methods of a smart contract. The transformation supports BPMN models that contain complex multi-step activities supported using our concept of multi-step nested trade transactions. In this paper, we present a methodology for repairing a smart contract that cannot be completed due to unanticipated events. The repair process starts with the original BPMN model fragment causing the issue and amends the pattern based on successful completion of previous activities. This paper describes the tool TABS+R, developed by extending TABS+, to allow repair of smart contracts.
2023
Liu, C. G.; Bodorik, P.; Jutla, D.
Book chapter in Communications in Computer and Information Science, pp. 141–155. Springer. November 2023.
Bodorik, P.; Liu, C. G.; Jutla, D.
Elsevier Journal of Blockchain: Research and Applications, vol. 4, 100115, pp. 1–26. 2023.
Impact Factor: 6.9 | CiteScore: 11.3
Research on blockchains addresses multiple issues, with one being automated creation of smart contracts. We report on a new approach to develop smart contracts with the objective to automate the process to increase developer efficiency and reduce risks. We use Business Process Model and Notation (BPMN) to describe an application targeting the trade vertical. The system transforms a BPMN model into a multi-modal model combining Discrete Event (DE) modeling with Hierarchical State Machines (HSMs), then further transforms the DE-HSM model into smart contract methods. The system lets the modeler decide which independent patterns should be deployed on a sidechain for cost reduction and/or privacy.
2022
Liu, C. G.; Bodorik, P.; Jutla, D.
2022 Fourth International Conference on Blockchain Computing and Applications (BCCA), IEEE, pp. 11–19. 2022.
Liu, C. G.; Bodorik, P.; Jutla, D.
Journal of Advances in Information Technology (JAIT), vol. 13, no. 3, pp. 213–223. 2022.
The power and correctness of smart contracts have been the focus of much research. We propose a new approach for developing smart contracts that uses multi-modal modeling to represent the application logic for the trade domain. We use discrete events modeling for concurrency combined with FSM modeling to use concurrent FSMs to simplify the design process, scale blockchain applications, and facilitate identifying parts of a smart program suitable for off-chain processing on a sidechain that also provides privacy.
2021
Liu, C. G.; Bodorik, P.; Jutla, D.
2021 IEEE International Conference on Engineering and Emerging Technologies (ICEET), pp. 1–7. October 2021.
Scalability, privacy, and interoperability are major issues in blockchain research. We concentrate on the trade finance vertical, developing a new modeling approach for automatic transformation of a BPMN application into a smart contract deployed on a blockchain. We describe how the BPMN model is transformed into a multimodal model combining DE-HSM modeling, and how the DE-HSM model is automatically transformed into deployable smart contracts that interact to form a distributed application, providing interoperability and privacy via private sidechains.
Bodorik, P.; Liu, C. G.; Jutla, D.
2021 3rd ACM International Conference on Blockchain Technology (ICBCT '21), pp. 28–34. Shanghai. 2021.
This paper proposes a new algorithm for blockchain software developers and architects to determine what computations of a smart contract can be effectively done off-chain without loss of trust. Our algorithm uses FSMs or HSMs to create smart contract patterns using graphs, then uses pattern recognition to identify which parts should be moved off-chain. Expert software developer inspection, in the context of a Trade Finance use case, validates our algorithm's ability to find optimal patterns.
Liu, C. G.; Bodorik, P.; Jutla, D.
3rd ACM International Symposium on Blockchain and Secure Critical Infrastructure (BSCI '21), pp. 103–109. Virtual Event. 2021.
This paper proposes a new approach and tool for blockchain software developers to determine which computations of a smart contract can be effectively done off-chain without loss of trust, and how they can be moved off-chain automatically. Our approach uses FSM and HSM modeling to create smart contract patterns, then uses pattern properties to identify candidates for off-chain execution.
Liu, C. G.
Master's Thesis, Dalhousie University. April 2021.
