Ning Xiong, Professor


Ning Xiong obtained the Ph.D with outstanding distinction from the University of Kaiserslautern (Germany) in 2000. His research addresses various aspects of computational intelligence techniques, incuding machine learning and big data analytics, evolutionary computing, fuzzy systems, uncertainty management, as well as multi-sensor data fusion, for building self-learning and adaptive systems in industrial and medical domains. He is serving as editorial board members for three international journals. He has been lead guest editor for a special issue in the journal "Neural Processing Letters" (Springer). He also has been programme committee members for a number of conferences and invited referee for many leading international journals.

Relevant conference information:

2018 the  3rd IEEE Conference on Computational Intelligence and Applications (ICCIA2018), Hongkong, July 28-30, 2018, http://www.iccia.org/

[Show all publications]

[Google Scholar author page]

Latest publications:

Enhancing Adaptive Differential Evolution Algorithms with Rank-Based Mutation Adaptation (Jul 2018)
Miguel Leon Ortiz, Ning Xiong
IEEE Congress on Evolutionary Computation (IEEE CEC'18)

MPADE: An Improved Adaptive Multi-Population Differential Evolution Algorithm Based on JADE (Jul 2018)
Javier Ramos , Miguel Leon Ortiz, Ning Xiong
IEEE Congress on Evolutionary Computation (IEEE CEC'18)

MapReduce distributed highly random fuzzy forest for noisy big data (Jul 2017)
Faruk Mustafic , Ning Xiong, Francisco Herrera, Sergio Ramrez
13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery 2017 (ICNC-FSKD-2017)

Big data stream learning based hybridized Kalman filter and backpropagation through time (Jul 2017)
He Fan, Ning Xiong
13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery 2017 (ICNC-FSKD-2017)

Alopex-Based Mutation Strategy in Differential Evolution (Jun 2017)
Miguel Leon Ortiz, Ning Xiong
IEEE Congress on Evolutionary Computation 2017 (IEEE CEC'17)

Adaptive Differential Evolution Supports Automatic Model Calibration in Furnace Optimized Control System (Jan 2017)
Miguel Leon Ortiz, Magnus Evestedt , Ning Xiong
Computational Intelligence (CI)

PhD students supervised as main supervisor:

Jonatan Tidare
Miguel Leon Ortiz

PhD students supervised as assistant supervisor:

Ella Olsson (former)
Per Hellström
Tomas Olsson (former)

MSc theses supervised (or examined):
Thesis TitleStatus
available
Data Stream Mining with the PRAAG change detection algorithm available
Developing Simulation Models of Data Center Infrastructure available
Dynamic modelling of ship behavior using recurrent neural networks available
Fitness approximation in expensive optimization problems available
Similarity learning in case-based reasoning available
USING DOMAIN KNOWLEDGE FUNCTIONS TO ACCOUNT FOR HETEROGENEOUS CONTEXT FOR TASKS IN DECISION SUPPORT SYSTEM FOR PLANNING selected
Autonomous robot collecting waste bins in an office environment in progress
Design of an Active Boom Suspension System in a Hybrid Wheel Loader in progress
Evaluation of grasp-and-extend hand dynamics and intelligent modeling of grasp hand dynamics in progress
Evolutionary computation in continuous optimisation and machine learning in progress
INTELLIGENT MATCHING FOR CLINICAL DECISION SUPPORT SYSTEM FOR CEREBRAL PALSY USING DOMAIN KNOWLEDGE in progress
Intelligent orange-picking robot in progress
The Influence of Bitcoin on Ethereum Price Predictions in progress
Using ant colony optimization as pathfinding in a changing environment in progress
Using AI and Statistics on Structured Electronic Patient Records for Clinical Decision Support Systems finished
Case-based approach for process modeling finished
Clinical Decision Support System for Cerebral Palsy finished
Combining different feature weighting methods for case-based reasoning finished
Enhancing the human-team awareness of a robot finished
Generating Fuzzy Rules from Case Base for Classification Problems finished
Monitoring system for free form modeling machines at Digital Mechanics. finished
NOISY BIG DATA CLASSIFICATION USING MAPREDUCE DISTRIBUTED FUZZY RANDOM FOREST finished
OBJECT RECOGNITION THROUGH DEEP CONVOLUTIONAL LEARNING FOR FPGA finished
Ocean Waves Estimation finished
Real-time Process Modelling Based on Big Data Stream Learning finished