Rong Qu

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Professor

University of Nottingham

United Kingdom

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About

Rong Qu is a Professor at the University of Nottingham, UK. His research interests focus on machine learning, medical image segmentation, human activity recognition, and optimization techniques. Recent publications include advancements in deep reinforcement learning and genetic programming, as well as novel algorithms for data-driven simulation in various domains.

Recent Grants

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EV-shAIR

Open Date: 2022-10-01

Close Date: 2023-08-01

Grant: Close

Algorithm Design Engineering

Open Date: 2022-10-01

Close Date: 2023-09-01

Grant: Close

AI-Driven Secured Connected and Autonomous Vehicles (AI-DRIVEs)

Open Date: 2020-04-01

Close Date: 2020-07-01

Grant: Close

Encouraging Lifelong Learning for an Inclusive and Vibrant Europe

Open Date: 2016-10-01

Close Date: 2019-09-01

Grant: Close

Logistics Service Network Optimisation and Multi-mode Intelligent Container Transportation Scheduling

Open Date: 2015-06-01

Close Date: 2018-05-01

Rong Qu

Research Interests

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About

Recent Grants

Articles (22)

CFFormer: Cross CNN-Transformer channel attention and spatial feature fusion for improved segmentation of heterogeneous medical images

Guest Editorial Machine-Learning-Assisted Evolutionary Computation

CapMatch: Semi-Supervised Contrastive Transformer Capsule With Feature-Based Knowledge Distillation for Human Activity Recognition

Heterogeneous Mutual Knowledge Distillation for Wearable Human Activity Recognition

Automated design of local search algorithms: Predicting algorithmic components with LSTM

Advancing container port traffic simulation: A data-driven machine learning approach in sparse data environments

A pattern-based algorithm with fuzzy logic bin selector for online bin packing problem

DTCM: Deep Transformer Capsule Mutual Distillation for Multivariate Time Series Classification

Self-Bidirectional Decoupled Distillation for Time Series Classification

Deep Reinforcement Learning Assisted Genetic Programming Ensemble Hyper-Heuristics for Dynamic Scheduling of Container Port Trucks

Densely Knowledge-Aware Network for Multivariate Time Series Classification

Learning-guided cross-sampling for large-scale evolutionary multi-objective optimization

Guest Editorial Special Issue on Multiobjective Evolutionary Optimization in Machine Learning

Automated design of search algorithms based on reinforcement learning

Automated Design of Metaheuristics Using Reinforcement Learning Within a Novel General Search Framework

Community evolution prediction based on a self-adaptive timeframe in social networks

Automated algorithm design using proximal policy optimisation with identified features

A Collaborative Learning Tracking Network for Remote Sensing Videos

Models of Representation in Computational Intelligence [Guest Editorial]

Deep Contrastive Representation Learning With Self-Distillation

Cooperative Double-Layer Genetic Programming Hyper-Heuristic for Online Container Terminal Truck Dispatching

Adaptive Fuzzy Learning Superpixel Representation for PolSAR Image Classification

Collaborators (4)

Hadi Akbarzadeh Khorshidi

Manuel López-Ibáñez

Shuo Wang

Hadi Charkhgard

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