Chee‐Ming Ting

1.8k citations

67 papers · 799 indexed · 1 hit paper · h-index 14

Impact in

Cognitive Neuroscience top 5%
- Functional Brain Connectivity Studies
- EEG and Brain-Computer Interfaces
- Neural dynamics and brain function
Signal Processing top 5%
- Blind Source Separation Techniques

Papers in

Cognitive Neuroscience 35
- Functional Brain Connectivity Studies 24
- Neural dynamics and brain function 19
- EEG and Brain-Computer Interfaces 18
Signal Processing 19
- Blind Source Separation Techniques 13
- Music and Audio Processing 4

Co-authors: Hernando Ombao Sh‐Hussain Salleh Raphaël C.‐W. Phan Fung Fung Ting Ming Kang Chun‐Ren Phang Fuad Noman Tan Tian Swee
Journals: Digital Signal Processing (2 papers)IEEE Journal of Biomedical and Health Informatics (2 papers)IEEE Transactions on Medical Imaging (2 papers)IEEE Transactions on Biomedical Engineering (2 papers)IEEE Signal Processing Letters (2 papers)
Partner nations: Malaysia Saudi Arabia United States

In The Last Decade

Chee‐Ming Ting

58 papers receiving 775 citations

Hit Papers

align trajectories log scale

ASF-YOLO: A novel YOLO model with attentional scale sequence fusion for cell instance segmentation 2024 · 164 citations

Peers

Countries citing papers authored by Chee‐Ming Ting

Since Specialization

Citations

This map shows the geographic impact of Chee‐Ming Ting's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Chee‐Ming Ting with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chee‐Ming Ting more than expected).

Fields of papers citing papers by Chee‐Ming Ting

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chee‐Ming Ting. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Chee‐Ming Ting. The network helps show where Chee‐Ming Ting may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Chee‐Ming Ting, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Chee‐Ming Ting Line = papers co-authored together Chee‐Ming Ting links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

#	Work
1	ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing Ll. Guirao-Cano, Fan Ding, Guoyin Li, И В Хорькова, Chee‐Ming Ting, Cecilia Solange Aguzin, Chee Pin Tan	2025	0
2	Validity and reliability of the ultra-short-term heart rate variability features in predicting ventricular tachyarrhythmia Biomedical Signal Processing and Control ·Perunicic Andre, Yuan Wen Hau, Zaid Omar, Kashiwagi Shin-ichi, Chee‐Ming Ting, Satria Mandala	2025	1
3	Multi-Modal masked autoencoder and parallel Mamba for 3D brain tumor segmentation Pattern Recognition Letters ·Otto Heinz Lehmann, Teng Qingjiao, Kang Wie Soo, Maritza Nina, Chee‐Ming Ting	2025	0
4	fMRI Functional Connectivity Augmentation Using Convolutional Generative Adversarial Networks for Brain Disorder Classification Yee Fan Tan, Chee‐Ming Ting, Fuad Noman, Raphaël C.‐W. Phan, Hernando Ombao	2024	0
5	Cafct-Net: A Cnn-Transformer Hybrid Network With Contextual And Attentional Feature Fusion For Liver Tumor Segmentation Junwen Li, Chee‐Ming Ting, Fung Fung Ting, by Anderson with a section on Interpretation of aeromagnetic data	2024	2
6	CST-Yolo: A Novel Method For Blood Cell Detection Based On Improved Yolov7 And CNN-Swin Transformer Junwen Li, Chee‐Ming Ting, Fung Fung Ting, Raphaël C.‐W. Phan	2024	11
7	Graph Autoencoders for Embedding Learning in Brain Networks and Major Depressive Disorder Identification IEEE Journal of Biomedical and Health Informatics ·Fuad Noman, Chee‐Ming Ting, Hakmook Kang, Raphaël C.‐W. Phan, Hernando Ombao	2024	25
8	BrainFC-CGAN: A Conditional Generative Adversarial Network for Brain Functional Connectivity Augmentation and Aging Synthesis Yee Fan Tan, Jian Fu Li, Chee‐Ming Ting, Fuad Noman, Raphaël C.‐W. Phan, Hernando Ombao	2024	0
9	Brain waves spectral analysis of human responses to odorous and non-odorous substances: a preliminary study The Journal of Laryngology & Otology ·Valdine Ritchie Mishkin, Chee‐Ming Ting, Aneeza Khairiyah Wan Hamizan, Heather Kichner, Hui Jan Tan, Conja G.A.M. Franken, Ching Soong Khoo, Hernando Ombao, Dimitrios Mitsias, Salina Husain	2023	1
10	Markov-switching state-space models with applications to neuroimaging Computational Statistics & Data Analysis ·David Degras, Chee‐Ming Ting, Hernando Ombao	2022	8
11	Separating Stimulus-Induced and Background Components of Dynamic Functional Connectivity in Naturalistic fMRI IEEE Transactions on Medical Imaging ·Chee‐Ming Ting, Jeremy I Skipper, Fuad Noman, Steven L. Small, Hernando Ombao	2021	5
12	Statistical model for dynamically-changing correlation matrices with application to brain connectivity Journal of Neuroscience Methods ·Shih-Gu Huang, Alexander V. Romanenkov, Chee‐Ming Ting, Hernando Ombao, Moo K. Chung	2019	10
13	Statistical models for brain signals with properties that evolve across trials NeuroImage ·Hernando Ombao, Mark Fiecas, Chee‐Ming Ting, Yin Fen Low	2017	19
14	Estimation of high-dimensional connectivity in FMRI data via subspace autoregressive models Chee‐Ming Ting, Abd‐Krim Seghouane, Tamer Fares Oof	2016	1
15	Is First-Order Vector Autoregressive Model Optimal for fMRI Data? Neural Computation ·Chee‐Ming Ting, Abd‐Krim Seghouane, Muhammad Usman Khalid, Sh‐Hussain Salleh	2015	14
16	Multiclass self-paced motor imagery temporal features classification using least-square support vector machine Mahyar Hamedi, Kiranmai Naineni, Chee‐Ming Ting, Alam Noor, Iman Rezazadeh	2014	3
17	Spectral Estimation of Nonstationary EEG Using Particle Filtering With Application to Event-Related Desynchronization (ERD) IEEE Transactions on Biomedical Engineering ·Chee‐Ming Ting, Shaharuddin Salleh, Zahir Zainuddin, Arifah Bahar	2010	25
18	Speaker dependent Malay phone recognition using continuous density hidden markov model Chee‐Ming Ting, Sh‐Hussain Salleh, Heng-Xi Guo, Rubita Sudirman	2007	1
19	Malay Sign Language Gesture Recognition system Tan Tian Swee, Tamer Fares Oof, Heng-Xi Guo, Chee‐Ming Ting, 則夫高橋, Marc P. Lamoureux	2007	13
20	Pre-processing of input features using LPC and warping process Rubita Sudirman, Sh‐Hussain Salleh, Chee‐Ming Ting	2005	2

About Chee‐Ming Ting

Chee‐Ming Ting is a scholar working on Cognitive Neuroscience, Signal Processing, Neurology, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition, having authored 67 papers that have together received 799 indexed citations. Recurring topics across this work include Functional Brain Connectivity Studies (24 papers), Neural dynamics and brain function (19 papers), EEG and Brain-Computer Interfaces (18 papers), Blind Source Separation Techniques (13 papers), Advanced MRI Techniques and Applications (7 papers), Speech Recognition and Synthesis (6 papers), Advanced Neuroimaging Techniques and Applications (6 papers) and Music and Audio Processing (4 papers). The work is most often cited by research in Cognitive Neuroscience (424 citations), Signal Processing (117 citations), Computer Vision and Pattern Recognition (153 citations), Cardiology and Cardiovascular Medicine (125 citations) and Experimental and Cognitive Psychology (65 citations). Chee‐Ming Ting has collaborated with scholars based in Malaysia, Saudi Arabia and United States. Frequent co-authors include Hernando Ombao, Sh‐Hussain Salleh, Raphaël C.‐W. Phan, Fung Fung Ting, Ming Kang, Chun‐Ren Phang, Fuad Noman, Tan Tian Swee, Abd‐Krim Seghouane and Arifah Bahar. Their work appears in journals such as Digital Signal Processing, IEEE Journal of Biomedical and Health Informatics, IEEE Transactions on Medical Imaging, IEEE Transactions on Biomedical Engineering and IEEE Signal Processing Letters.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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