Last updated: 08-10-2024
Dr. Feng LIANG (梁锋)
Email: liangfengsid \at gmail \dot com or fliang \at smbu \dot edu \dot cn
Associate Professor with Artificial Intelligence Research Institute, Shenzhen MSU-BIT University (SMBU)

Former founder&CTO, Shenzhen Qmaple Technology Co., Ltd and previously a senior research engineerer in Huawei
Obtained Ph.D. Degree in computer science from The University of Hong Kong (2012-2017)
Obtained B.Eng. Degree in software engineering from Nanjing University (2008-2012)
PhD Supervisor: Prof. Francis C.M. Lau
Research interest: Distributed systems and databases, machine learning systems, large-scale deep learning

Selected Publications: (* Equal contribution, # Correspoding author) Journal Conference Preprint
• F. Liang, Z. Zhang, H. Lu, C. Li, V. C. M. Leung, Y. Guo, and X. Hu, "Resource Allocation and Workload Scheduling for Large-Scale Distributed Deep Learning: A Survey", 2024. [link |pdf]
• F. Liang, Z. Zhang, H. Lu, V. C. M. Leung, Y. Guo, and X. Hu, "Communication-Efficient Large-Scale Distributed Deep Learning: A Comprehensive Survey", 2024. [link |pdf]
• D. Chen, F. Fang, S. Ni, F. Liang, R. Xu, M. Yang, C. Li, "Lower Layer Matters: Alleviating Hallucination via Multi-Layer Fusion Contrastive Decoding with Truthfulness Refocused", 2024. [link |pdf]
• H. Lu, J. Chen, F. Liang, M. Tan, R. Zeng, and X. Hu, "Understanding Emotional Body Expressions via Large Language Models", 39th Annual AAAI Conference on Artificial Intelligence (AAAI), Philadelphia, USA, 2025, to appear. (CCF-A, AR: 23.4%) [pdf]
• T. Li*, F. Liang*, J. Quan, C. Huang, T. Wang, R. Huang, J. Wu, and X. Hu, "Taste: Towards Practical Deep Learning-based Approaches for Semantic Type Detection in the Cloud", 28th International Conference on Extending Database Technology (EDBT), pp. 324-336, Barcelona, Spain, 2025. (core A, CCF-B, AR: 20.8%) [pdf | code]
• F. Liang, F.C.M. Lau, H. Cui, Y. Li, B. Lin, C. Li, and X. Hu, "RelJoin: Relative-cost-based Selection of Distributed Join Methods for Query Plan Optimization", Information Sciences (INS), vol. 658, 2024. (CAS S1) [link | pdf | code]
• W. Guo, B. Lin, G. Chen, Y. Chen, and F. Liang, "Cost-Driven Scheduling for Deadline-Based Workflow Across Multiple Clouds", IEEE Transactions on Network and Service Management (TNSM), vol. 15, no. 4, pp. 1571-1585, Dec. 2018. (Q1) [link | pdf]
• F. Liang, F.C.M. Lau, H. Cui, and C.-L. Wang, "Confluence: Speeding Up Iterative Distributed Operations by Key-dependency-aware Partitioning", IEEE Transactions on Parallel and Distributed Systems (TPDS), 2018. (CCF-A) [link | pdf]
• J. Jiang, S. Zhao, D. Alsayed, Y. Wang, H. Cui, F. Liang, and Z. Gu, "Kakute: A Precise, Unified Information Flow Analysis System for Big-data Security", 33rd Annual Computer Security Applications Conference (ACSAC), Orlando, USA, 2017. (core A, CCF-B, *Distinguished Paper Award, AR: 19.8%) [link | pdf | code]
• F. Liang and F.C.M. Lau, "BAShuffler: Maximizing Network BAndwidth Utilization in the Shuffle of YARN", 25th ACM Symposium on High-Performance Parallel and Distributed Computing (HPDC), Kyoto, Japan, May 31 - June 4, 2016. (core A, CCF-B, AR: 22.5%) [link | pdf]
• F. Liang and F.C.M. Lau, "SMapReduce: Optimising Resource Allocation by Managing Working Slots at Runtime", 29th IEEE International Parallel & Distributed Processing Symposium (IPDPS), Hyderabad, India, May 25-29, 2015. (core A, CCF-B, AR: 22.0%) [link | pdf]

Patents:
[PCT/CN] "Log Processing Method, Related Device, and System", LU Yuanfei, LIANG Feng and LIU Cunwei, owned by Huawei, Pub. No.: WO/2019/109953, June 2019.
[PCT/CN] "Configuration Modification Method for Storage Cluster, Storage Cluster and Computer System", ZHOU Siyi, LIANG Feng, ZHI Yanan and HUANG Xihua, owned by Huawei, Pub. No.: WO/2019/085875, May 2019.

Teaching Experience:
Programming Design and Practice, fall 2023
Parallel and Distributed Progamming, spring 2024
Teaching assistant of Computer Architecture, Programming in C++, Operating System, Web Technology, 2012-2016

Academic activities:
Publicity Chair, 8th IEEE International Conference on Smart Internet of Things (SmartIoT) 2024
TPC Member, 10th International Conference on Big Data Computing and Communications (BIGCOM) 2024
TPC Member, 44th IEEE International Conference on Distributed Computing Systems (ICDCS), 2024
Distinguished contributor, 19th EAI International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness (Qshine), 2023
TPC Member, The 2nd International Workshop on Social and Metaverse Computing and Networking (SocialMeta), 2023
Session chair, the 11th WorkShop on High-Performance, Power-Aware Computing (IPDPS-HPPAC), 2015
Reviewer of Journal of Interconnection Network (JOIN), 2013
Reviewer of The 22nd IEEE International Conference on Parallel and Distributed Systems (ICPADS), 2016

Awards and Grants:
Overseas High-Caliber Personnel in Shenzhen, China
Shenzhen Overseas Entrepreneurship Fund, 2020-2021
Semi-finalists of the Innovation and Entrepreneurship Competition of Shenzhen, 2020
Semi-finalists of the China Innovation and Entrepreneurship Competition for SMEs, 2019&2020, respectively
TCPP Conference Travel Grant (2015)
Postgraduate Scholarship of The University of Hong Kong, 2012-2016
Outstanding Graduate, Nanjing University, 2012
Excellent Award of the Innovation Cup, Software Institute, Nanjing University, 2011
Excellent Student Award, Software Institute, Nanjing University, 2009&2010, respectively
Second prize of People's Scholarship, and Second prize of Social Work Scholarship, Nanjing University, 2010
Excellent Staff of Student Union, Software Institute, Nanjing University, 2010
First prize of People's Scholarship, Nanjing University, 2009

Events:
Program Chair of Canadian Computing Competition Hong Kong Contest (CCC), 2014
Web Master of Lap-Chee College, The University of Hong Kong, 2013-2015

***New*** Open source project:

TensorOnSpark

TensorOnSpark is a fast, scalable and reliable distributed framework for machine learning (deep learning). TensorFlow programs can run on Spark seamlessly with redundant distributed resources and high accuracy. It currently supports Python on Linux and Mac OS. The release and source and can be downloaded via Pypi and Github, respectly.
Github     Pypi Repository

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