Architecture and Analytics Platforms

The Architecture and Analytics Platforms team tackles major challenges in software architecture, data analytics, computing infrastructure, DevOps, and dependability. Please refer to the Disciplines below for an overview of our backgrounds. While we work on a wide range of topics, there are three major efforts of R&D in the team: the Business Process Modelling (BPM), the Data Analytics Platform and usage of Blockchain technologies – see the Research Topics section below.


Research Topics

  • Blockchain: Blockchain is an emerging technology for decentralized and transactional data sharing across a large network of untrusted participants. It enables new forms of distributed systems, where participants can find agreements on their shared states without trusting a central authority or any particular participates. Our group is mainly working on three aspects, including designing with blockchain, analyzing and improving trustworthy of blockchain, and legal reasoning with Smart Contracts on blockchain.
  • Data Analytics Platform: Data analytics and machine learning systems are increasingly used in various application areas and achieve many widely noticeable successes. Most of these systems benefit from large scale distributed system for data storage and complex computation. Our data analytics platform research target on both core distributed and parallel system techniques for running these systems on integrated data in a fast and scalable manner, and actual data analytics system development for application domains with challenging data handling problems such as health and scientific computing.
  • Business Process Modelling(BPM)
    • Process-Oriented Dependability (POD): The POD framework aims to improve the dependability of processes through behavioral anomaly detection. The approach relies on creating a process model for each operation and using that model to guide near real-time detection, diagnosis, and recovery from errors in the execution of the process.


The above activities are underpinned by expertise in the following disciplines.

  • Software ArchitectureShow more info.Hide info.
  • Data ManagementShow more info.Hide info.
  • Performance EngineeringShow more info.Hide info.
  • Dependable Cloud Computing and ApplicationsShow more info.Hide info.

We also apply empirical software engineering, AI planning, optimization and business value-driven IT management, software process research to our problems.

Contact: Shiping Chen



    • Ethviewer (Beta): A beta release of real time monitoring of the Ethereum Blockchain

    • IOkeeper
    • Lorikeet
    • Macrokey



Researchers/Engineers Students
  • Adnene Guabtni
  • Chen Wang
  • Christopher Klinkmuller
  • Dilum Bandara
  • Hugo O’Connor
  • Qinghua Lu
  • Ralph Holz
  • Sherry Xu
  • Vincent Gramoli
  • Sunny Verma
  • Bin Liu
  • Mojtaba Shahin
  • Ngoc Tran Trung
  • Renlord Yang
  • Shuai Zhang
  • Su Yen Chia
  • Sin Kuang Lo
  • Yu Shuang


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  • 2019Show more info.Hide info.

    Up to 24 March, 2019

    • Mining Process Mining Practices: An Exploratory Characterization of Information Needs in Process Analytics
      Christopher Klinkmüller, Richard Müller, and Ingo Weber
      International Conference on Business Process Management 2019. (see:
    • Mining Blockchain Processes: Extracting Process Mining Data from Blockchain Applications (Best Paper Award)
      Christopher Klinkmüller, Alexander Ponomarev, An Binh Tran, Ingo Weber, and Wil van der Aalst
      International Conference on Business Process Management 2019, Blockchain Forum
    • Dynamic role binding in blockchain-based collaborative business processes
      Orlenys López-Pintado, Marlon Dumas, Luciano García-Bañuelos, and Ingo Weber
      CAISE’19: International Conference on Advanced Information Systems Engineering, Rome, Italy, July 2019
    • Digital-Physical Parity for Food Fraud Detection
      Sin Kuang Lo, Xiwei Xu, Chen Wang, Ingo Weber, Paul Rimba, Qinghua Lu, and Mark Staples
      ICBC’19: International Conference on Blockchain, San Diego, USA, June, 2019. Accepted March, 2019
    • TEXUS: A unified framework for extracting and understanding tables in PDF documents
      Roya Rastan, Hye-Young Paik, John Shepherd
      Information Processing & Management. May 2019
    • A platform architecture for multi-tenant blockchain-based systems
      Ingo Weber, Qinghua Lu, An Binh Tran, Amit Deshmukh, Marek Gorski, and Markus Strazds
      ICSA’19: IEEE International Conference on Software Architecture, Hamburg, Germany, April 2019
    • Designing blockchain-based applications a case study for imported product traceability
      Xiwei Xu, Qinghua Lu, Yue Liu, Liming Zhu, Haonan Yao, Athanasios V Vasilakos
      Future Generation Computer Systems. Published March 2019
    • Integrating and querying similar tables from PDF documents using deep learning
      Rahul Anand, Hye-Young Paik, Cheng Wang
      arXiv preprint arXiv:1901.04672. January 2019
    • Data Governance Decisions for Platform Ecosystems
      Sung Une Lee, Liming Zhu, and Ross Jeffery
      HICSS’19: 52nd Hawaii International Conference on System Sciences, January 2019


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  • 2007 - 2015Show more info.Hide info.