Education

• Ph.D in Computer Science, Tongji University, 2017
• BEng in Computer Scicence and Technology, Tongji University, 2011

Work experience

• April 2019 - present
  Lecturer in Computing and Data Science
  University of Derby
  

• June 2017 - April 2019
  KTP Data Scientist (PostDoc)
  University of Derby and Solutions for Retail Brands (S4RB)
  Innovate UK project “To use intelligent analytics to discover insights and patterns within retail data.”

Current Research Projects

• Knowledge Transfer Partnerships (KTP) Project in Virtual Reality (University of Derby & Bloc Digital) 2019 – 2021
• Knowledge Transfer Partnerships (KTP) Project in Network Services (University of Derby & FP Solutions) 2019 – 2022

Skills

• Data Science
  • Applied Machine Learning
  • Cloud Architectures
  • Data Processing Pipelines
  • Data Warehousing Services
  • Business Intelligence Solutions
• Deep Learning
  • CNN, LSTM, RNN
  • Tensorflow
  • PyTorch
• Big data Analytics
  • Design Big Data Application using Spark or Hadoop
  • Data processing with R, Python
  • Visualisation with Tableau

PhD Students

• Muhammad Sadiq Hassan Zada; 2020 - present;
  Research Topic: ‘An efficient graph integration framework based on novel graph probabilistic dependencies’
• Rabia Saleem; 2020 - present;
  Research Topic: ‘Trustworthy and Explainable Artificial Intelligence using Graph Theoretic Models’
• Thankgod Anthony Njoku; 2019 - present (co-supervision);
  Research Topic:’Data Security and Privacy Platform using Machine Learning for Blockchain in Smart Government’
• Bilal Arshad; 2016 - present (co-supervision);
  Research Topic: ‘Graph Based Data Integration for SystemIntegrity and Scalable Analytics’
• Danielle Turvill; 2016 - present (co-supervision);
  Research Topic: ‘Machine Learning in Accelerator-based High Energy Physics’

Looking for self-motivated PhD candidates to embark upon the most trending AI and Data Science research. Do not hesitate to get in touch if you are interested.

Teaching

• Foundations of Computer Science (UG Level 4; Spring Semester)
• Data Management and Business Intelligence (UG Level 5; Spring Semester)
• Database Development (PG Level 7; Autumn Semester)
• Personal Academic Tutoring (UG and PG)
• Placement Visiting Tutoring (UG)

Professional Service

• Regular reviewer:
  

  IEEE Transactions on Industrial Informatics; Peer-to-Peer Networking and Applications; IEEE Access; IEEE Internet of Things Journal; ACM Transactions on Intelligent Systems and Technology; Information Sciences - Journal

• Conference Service:
  

  PC member and Workshop co-chair of ScalCom 2019; Proceeding chair and local organizing chair of UCC2016; PC member of UCC2015, UCC2016, BDCAT2016

Recent Journal Publications

• B. Yuan, J. Panneerselvam, L. Liu, N. Antonopoulos, and Y. Lu, “An Inductive Content-Augmented Network Embedding Model for Edge Artificial Intelligence,” IEEE Transactions on Industrial Informatics, pp. 4295-4305, 2019. (Impact Factor 9.112)

• B. Yuan, L. Liu, and N. Antonopoulos, “Efficient service discovery in decentralized online social networks,” Future Generation Comp. Syst., vol. 86, pp. 775-791, 2018. (Impact Factor 5.768)

• Jiang, L. Shi, L. Liu, J. Yao, B. Yuan, and Y. Zheng, “An Efficient Evolutionary User Interest Community Discovery Model in Dynamic Social Networks for Internet of People,” IEEE Internet of Things Journal, pp. 1-1, 2019. (Impact Factor 9.936)

• Y. Sun, B. Yuan, T. Zhang, B. Tang, W. Zheng, and X. Zhou. “Research and Implementation of Hybrid Intelligent Wargame Based on Prior Knowledge-DQN Algorithm.” Electronics. 2020; 9(10):1668. (Impact Factor 2.412)

• Y. Lu, L. Liu, J. Panneerselvam, B. Yuan, J. Gu and N. Antonopoulos, “A GRU-Based Prediction Framework for Intelligent Resource Management at Cloud Data Centres in the Age of 5G,” in IEEE Transactions on Cognitive Communications and Networking, vol. 6, no. 2, pp. 486-498, June 2020, doi: 10.1109/TCCN.2019.2954388.(Impact Factor 4.574)

• J. Panneerselvam, J. Hardy, L. Liu, B. Yuan, N. Antonopoulos, “Mobilouds: An Energy-Efficient MCC Collaborative Framework with Extended Mobile Participation for Next-Generation Networks,” in IEEE Access, vol.PP, no.99, pp.1-1 doi: 10.1109/ACCESS.2016.2602321. (Impact Factor 3.745)

Recent Conference Papers

• M. S. H. Zada, B. Yuan, A. Anjum, M. A. Azad, W. A. Khan and S. Reiff-Marganiec, “Large-scale Data Integration Using Graph Probabilistic Dependencies (GPDs),” 2020 IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT), Leicester, UK, 2020, pp. 27-36, doi: 10.1109/BDCAT50828.2020.00028.

• R. Saleem, B. Yuan, F. Kurugollu and A. Anjum, “Explaining probabilistic Artificial Intelligence (AI) models by discretizing Deep Neural Networks,” 2020 IEEE/ACM 13th International Conference on Utility and Cloud Computing (UCC), Leicester, UK, 2020, pp. 446-448, doi: 10.1109/UCC48980.2020.00070.

• D. Turvill, L. Barnby, B. Yuan and A. Zahir, “A Survey of Interpretability of Machine Learning in Accelerator-based High Energy Physics,” 2020 IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT), Leicester, UK, 2020, pp. 77-86, doi: 10.1109/BDCAT50828.2020.00025.

• B. Yuan, A. Anjum, J. Panneerselvam, L. Liu. 2019, November. Exploring Network Embedding for Efficient Message Routing in Opportunistic Mobile Social Networks. In 2019 International Conference on Data Mining Workshops (ICDMW) (pp. 497-504). IEEE.

• B. Yuan, J. Gu, and L. Liu. “A Privacy-Preserved Probabilistic Routing Index Model for Decentralised Online Social Networks.” 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI). IEEE, 2019