Ning Xiong, Professor

E-mail:
ning.xiong@mdh.se
Room:
U1-126
Phone:
+46-21-151716
Division:
Division of Intelligent Future Technologies
Research group:
Learning and Optimisation


Ning Xiong is Professor of  Artificial Intelligence. He obtained the Ph.D with Excellent 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 also has been invited keynote speakers, program committee chairs for internastional conferences and guest editors of special issues for leading  journals.

Project TitleStatus
A Digital Twin Framework for Dynamic and Robust Distributed Systems active
ADAPTER: Adaptive Learning and Information Fusion for Online Classification Based on Evolving Big Data Streams active
AIM, Artificial Intelligence in Medical Applications finished
Computational Intelligence in Process Modelling and Prediction finished
CREATE ITEA2 finished
Digitalization of HVDC grids by means of smart data discovery finished
EKEN-Efficient knowledge and experience reuse within the business world finished
Embedded Sensor Systems for Health Plus finished
EMOPAC - Evolutionary Multi-Objective Optimization and Its Applications in Analog Circuit Design finished
ExAct, Intelligent experience sharing for industrial applications finished
Factory in a Box finished
Identifying key variables in monitoring of production processes in automotive industry: A deep learning method active
IEMI: Intelligent extraction of mental imagery during stroke rehabilitation finished
Improving Accuracy of the Cardiac Stress Test by Applying Advanced Signal Processing Methods to an Embedded Sensor Setting finished
InMaint - Intelligent Monitoring and Maintenance in Production Industry finished
InSecTT: Intelligent Secure Trustable Things active
Linnaeus-Palme: ECUST finished
Machine learning in power devices and power systems finished
Pain Out, WP decision support for pain relief finished
Performant and Flexible digital Systems through Verifiable AI active
PROEK, Ökad Produktivitet och Livskvalitet finished
Self-supervised learning for predictive maintenance active
V-trustEE finished
PhD students supervised as main supervisor:

Johan Hjorth
Johan Holmberg
Miguel Leon Ortiz (former)
Sarala Mohan
Sharmin Sultana Sheuly (former)

PhD students supervised as assistant supervisor:

Ella Olsson (former)
Jonatan Tidare (former)
Martin Johansson-Alvarez
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
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
Evaluation of grasp-and-extend hand dynamics and intelligent modeling of grasp hand dynamics 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