Publications

Publications (Google Scholar profile, ResearchGate profile)

Journals

1. (2025) Majid Haji Bagheri et al., "Sustainable Live Sound Monitoring and Classification System Enabled by a Triboelectric Nanogenerator and Machine Learning Techniques", accepted to Energy & Environmental Materials.

2. (2025) Brady Laska, Pengcheng Xi, Julio J. Valdes, Bruce Wallace, James Green, Rafik Goubran, Frank Knoefel, "Coughprint: Distilled Cough Representations from Speech Foundation Model Embeddings", accepted to IEEE Transactions on Instrumentation & Measurement.

3. (2025) Bagheri, M.H., Gu, E., Khan, A.A., Zhang, Y., Xiao, G., Nankali, M., Peng, P., Xi, P. and Ban, D. (2025), Machine Learning-Enabled Triboelectric Nanogenerator for Continuous Sound Monitoring and Captioning. Adv. Sensor Res., 4: 2400156. https://doi.org/10.1002/adsr.202400156

4. (2024) Shah, Krish, et al. "FoodVideoQA: A Novel Framework for Dietary Monitoring." Journal of Computational Vision and Imaging Systems 10.1 (2024): 95-101.

5. (2024) J. J. Valdés et al., "Human Activity Understanding Through Explainable Audio–Visual Features," in IEEE Sensors Letters, vol. 8, no. 8, pp. 1-4, Aug. 2024, Art no. 6010104, doi: 10.1109/LSENS.2024.3425760.

6. (2024) Vardhan Paliwal, Kritiprasanna Das, Sam M. Doesburg, George Medvedev, Pengcheng Xi, Urs Ribary, Ram Bilas Pachori, and Vasily A. Vakorin, "Classifying Routine Clinical Electroencephalograms With Multivariate Iterative Filtering and Convolutional Neural Networks", IEEE Transactions on Neural Systems and Rehabilitation Engineering, DOI: 10.1109/TNSRE.2024.3403198

7. (2023) Ma, K.; He, S.; Sinha, G.; Ebadi, A.; Florea, A.; Tremblay, S.; Wong, A.; Xi, P. Towards Building a Trustworthy Deep Learning Framework for Medical Image Analysis. Sensors 2023, 23, 8122. https://doi.org/10.3390/s23198122

8. (2023) Laraba I, Ward TJ, Cuperlovic-Culf M, Azimi H, Xi P, McCormick S, Hay W, Hao G, Vaughan MM. "Insights into the aggressiveness of the emerging North American population 3 (NA3) of Fusarium graminearum". Plant Dis. 2023 Feb 12. doi: 10.1094/PDIS-11-22-2698-RE. Epub ahead of print. PMID: 36774561.

9. (2023) Song J, Ebadi A, Florea A, Xi P, Tremblay S, Wong A. "COVID-Net USPro: An Explainable Few-Shot Deep Prototypical Network for COVID-19 Screening Using Point-of-Care Ultrasound". Sensors. 2023; 23(5):2621. https://doi.org/10.3390/s23052621

10. (2022) Klymenko M, Doesburg SM, Medvedev G, Xi P, Ribary U, Vakorin VA. Byte-Pair Encoding for classifying routine clinical electroencephalograms in adults over the lifespan. IEEE J Biomed Health Inform. 2023 Jan 12;PP. doi: 10.1109/JBHI.2023.3236264. Epub ahead of print. PMID: 37018726.

11. (2022) Ebadi A, Xi P, MacLean A, Florea A, Tremblay S, Kohli S, Wong A. COVIDx-US: An Open-Access Benchmark Dataset of Ultrasound Imaging Data for AI-Driven COVID-19 Analytics. Front Biosci (Landmark Ed). 2022 Jun 24;27(7):198. doi: 10.31083/j.fbl2707198. PMID: 35866396.

12. (2022) M. Cohen-McFarlane et al., "Evaluation of Respiratory Sounds Using Image-Based Approaches for Health Measurement Applications," in IEEE Open Journal of Engineering in Medicine and Biology, vol. 3, pp. 134-141, 2022, doi: 10.1109/OJEMB.2022.3202435.

13. (2022) Hilda Azimi, Jianxing Zhang, Pengcheng Xi, Hala As'ad, Ashkan Ebadi, Stéphane Tremblay, Alexander Wong, "Improving Classification Model Performance on Chest X-Rays through Lung Segmentation", submitted.

14. (2021) Salem, D.; Li, Y.; Xi, P.; Phenix, H.; Cuperlovic-Culf, M.; Kærn, M. "YeastNet: Deep-Learning-Enabled Accurate Segmentation of Budding Yeast Cells in Bright-Field Microscopy". Appl. Sci. 2021, 11, 2692.

15. (2021) As’ad, H., Azmi, H., Xi, P., Ebadi, A., Tremblay, S., & Wong, A. "COVID-19 Detection from Chest X-Ray Images Using Deep Convolutional Neural Networks with Weights Imprinting Approach". Journal of Computational Vision and Imaging Systems, 6(1), 1-3.

16. (2020) A. Ebadi, P. Xi, S. Tremblay, B. Spencer, R. Pall, A. Wong, "Understanding the temporal evolution of COVID-19 research through machine learning and natural language processing", Scientometrics 126, 725–739 (2021). https://doi.org/10.1007/s11192-020-03744-7.

17. (2020) H. Azimi, P. Xi, M. Bouchard, R. Goubran and F. Knoefel, "Machine Learning-Based Automatic Detection of Central Sleep Apnea Events from a Pressure Sensitive Mat"  in IEEE Access, vol. 8, pp. 173428-173439, 2020, doi: 10.1109/ACCESS.2020.3025808. 

18. (2019) P. Xi, H. Guan, C. Shu, L. Borgeat, R. Goubran, "An integrated approach for medical abnormality detection using deep patch convolutional neural networks", Vis Comput 36, pages1869–1882 (2019), doi:10.1007/s00371-019-01775-7.

19. (2016) P. Xi, C. Shu, R. Goubran, "Comparing 2D Image Features on Viewpoint Independence Using 3D Anthropometric Dataset", Int. J. of the Digital Human, 1(4) (2016), pp. 412-425.

20. (2015) Y. Liu, P. Xi, M. Joseph, Z. Zhuang, C. Shu, L. Jiang, M. Bergman, W. Chen, "Variations in Head-and-Face Shape of Chinese Civilian Workers", Ann. Occup. Hyg., 2015, 1–13, doi:10.1093/annhyg/mev026.

21. (2013) Z. Zhuang, C. Shu, P. Xi, M. Bergman, M. Joseph, “Head-and-Face Shape Variations of U.S. Civilian Workers”, Applied Ergonomics, 44(5) (2013), pp. 775-784 .

22. (2013) J. Boisvert, C. Shu, S. Wuhrer, P. Xi, “Three-Dimensional Human Shape Inference from Silhouettes: Reconstruction and Validation", Machine Vision and Applications, 24(1) (2013), pp. 145-157.

23. (2012) C. Shu, S. Wuhrer, P. Xi, “3D Anthropometric Data Processing", International Journal of Human Factors Modelling and Simulation, 3(2) (2012), pp. 133-146.

24. (2012) S. Wuhrer, C. Shu, P. Xi, “Posture-Invariant Statistical Shape Analysis Using Laplace Operator", Computers and Graphics, 36(5) (2012), pp. 410-416.

25. (2012) S. Wuhrer, P. Xi, C. Shu, “Human Shape Correspondence with Automatically Predicted Landmarks", Machine Vision and Applications, 23(4) (2012), pp. 821-830.

26. (2011) S. Wuhrer, C. Shu, P. Xi, “Landmark-Free Posture Invariant Human Shape Correspondence", The Visual Computer, 27(9) (2011), pp. 843-852.

27. (2010) R. Ball, C. Shu, P. Xi, M. Rioux, J. Molenbroek, D.V. Eijk, “A Comparison of Chinese and Caucasian Head Shapes", Applied Ergonomics 41(6) (2010), pp. 832-839.

28. (2009) P. Xi, C. Shu, “Consistent Parameterization and Statistical Analysis of Human Head Scans", Visual Computer Journal of Computer Graphics 25(9) (2009), pp. 863-871.

29. (2005) Z. Zhao, T. Xu, P. Xi, “A Digital Image Watermarking Scheme against Geometric Transformation Attacks", Journal of Nanjing University of Aeronautics and Astronautics, 37(1) (2005), pp. 70-74.

Book Chapters

1. (2021) G. Rouhafzay, Y. Li, H. Guan, C. Shu, R. Goubran, P. Xi, "Enhanced Lesion Detection in Breast MRI Using Parallel and Cascaded Integration of Deep Learning Models", Advances in Pattern Recognition and Artificial Intelligence. December 2021, 1-21

2. (2021) P. Xi, G. Rouhafzay, H. Guan, C. Shu, L. Borgeat, R. Goubran, "Chapter 1 - Computer-aided detection of abnormality in mammography using deep object detectors", Editor(s): Ayman S. El-Baz, Jasjit S. Suri, State of the Art in Neural Networks and their Applications, Academic Press, 2021, Pages 1-18, ISBN 9780128197400, https://doi.org/10.1016/B978-0-12-819740-0.00001-2.

3. (2019) P. Xi, R. Goubran, C. Shu, "Cardiac Murmur Classification in Phonocardiograms using Deep Recurrent-Convolutional Neural Networks", a book chapter in “Frontiers in Pattern Recognition and Artificial Intelligence” by World Scientific, Edited By: Marleah Blom, Nicola Nobile and Ching Yee Suen, https://doi.org/10.1142/11362, ISBN: 978-981-12-0335-0, pp 189-210, July 2019.

Conferences

1. Krish Shah, Siddharth Viswanath, Pengcheng Xi, Alexander Wong, Yuhao Chen, "FoodVideoQA: A novel baseline framework for dietary monitoring", accepted to CVPR 2025 MetaFood Workshop

2. Julio Valdes, Stephie Liu, Shawn Liu, Yuhao Chen, Alexander Wong, Pengcheng Xi, "Food degradation analysis using multimodal fuzzy clustering", accepted to CVPR 2025 MetaFood Workshop

3. (2024) Ostap Kalapun, Alexander Moiseev, George Medvedev, Sam Doesburg, Pengcheng Xi, Sylvain Merono, Urs Ribary, and Vasily Vakorin, "Biological age from electroencephalographic activity could be decoupled from a gradual stochastic accumulation of pathologies over adulthood", accepted at the workshop MLESP 2024

4. Chen, Y., “MetaFood3D: 3D Food Dataset with Nutrition Values”, <i>arXiv e-prints</i>, Art. no. arXiv:2409.01966, 2024. doi:10.48550/arXiv.2409.01966.

5. He, J., “MetaFood CVPR 2024 Challenge on Physically Informed 3D Food Reconstruction: Methods and Results”, <i>arXiv e-prints</i>, Art. no. arXiv:2407.09285, 2024. doi:10.48550/arXiv.2407.09285.

6. (2024) C. Zhao et al., "Leveraging Large Language Models and Fuzzy Clustering for EEG Report Analysis", accepted to IEEE Sensors 2024

7. (2024) Z. Cook et al., "Decoding Brain Age: a Self-Supervised Graph Neural Network Framework for EEG Analysis", accepted to IEEE Sensors 2024

8. (2024) M. H. Bagheri et al., "A Data-Driven Environmental Sound Classification System with Acoustic Triboelectric Nanogenerators," 2024 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), Kingston, ON, Canada, 2024, pp. 881-886, doi: 10.1109/CCECE59415.2024.10667121. 

9. (2024) C. Zhao, A. Deshpande, D. Liu, C. Bellinger, P. Xi, "An Assistive Robotic Framework for Empowering Elderly Independence", accepted to ICRA 2024 workshop on physicial human-robot interaction (pHRI), Yokohama, Japan, May 2024

10. (2024) Akil Pathiranage, Chris Czarnecki, Yuhao Chen, Pengcheng Xi, Linlin Xu, Alexander Wong, "In the wild ellipse parameter estimation for circular dining plates and bowls", accepted to CVPR 2024 workshop on MetaFood, Seattle, USA, June 2024

11. (2024) Aaryam Sharma, Chris Czarnecki, Yuhao Chen, Pengcheng Xi, Linlin Xu, Alexander Wong, "How much you ate? Food portion estimation on spoons", accepted to CVPR 2024 workshop on MetaFood, Seattle, USA, June 2024

12. (2024) Matthew Keller, Chi-en Amy Tai, Yuhao Chen, Pengcheng Xi, Alexander Wong, "NutritionVerse-Direct: exploring deep neural networks for multitask nutrition prediction form food images", accepted to CVPR 2024 workshop on MetaFood, Seattle, USA, June 2024

13. (2024) Brady Laska, Pengcheng Xi, Julio J. Valdes, Bruce Wallace, Rafik Goubran, "Zero-shot Multi-task Cough Sound Analysis with Speech Foundation Model Embeddings", accepted to MeMeA 2024

14. (2024) Brady Laska, Julio Valdes, Pengcheng Xi, Rafik Goubran, Bruce Wallace, Madison Cohen-McFarlane, Frank Knoefel, "Cough Sound Analysis using Vocal Tract Models", accepted to I2MTC 2024, Glasgow, Scotland, May 2024

15. (2024) Mahya Shahmohammadimehrjardi, Bruce Wallace, Adrian D.C. Chan, Rafik Goubran, Xi, Pengcheng, Valdes, Julio, "Multi-Level Method for Sound Source Location Measurement", accepted to I2MTC 2024, Glasgow, Scotland, May 2024

16. (2024) Zara Cook, Grant Sinha, Jack Wang, Chengzong Zhao, Nabil Belacel,  Sam Doesburg, George Medvedev, Urs Ribary, Vasily Vakorin, Pengcheng Xi, "Enhancing Brain Age Prediction: A Generative AI Approach for EEG Machine Learning Models", accepted to I2MTC 2024, Glasgow, Scotland, May 2024 (Best Undergraduate Student Paper award & Student Travel Grant)

17. (2023) S. Huq, P. Xi, R. Goubran, F. Knoefel and J. Green, "Data Augmentation and Deep Learning in Audio Classification Problems: Alignment Between Training and Test Environments," in 2023 IEEE 23rd International Conference on Bioinformatics and Bioengineering (BIBE), Dayton, OH, USA, 2023 pp. 140-146. doi: 10.1109/BIBE60311.2023.00030

18. (2023) Chengzong Zhao, Jack Wang, Zara Cook, Grant Sinha, Simon Li, Chang Shu, Pengcheng Xi, "Vision Transformers for Age Prediction from Gait Energy Image Data", accepted to CVIS 2023: 9th Annual Conference on Vision and Intelligent Systems, Waterloo, Canada, December 2023

19. (2023) Zara Cook, Grant Sinha, Chengzong Zhao, Jack Wang, Sam Doesburg, George Medvedev, Urs Ribary, Vasily Vakorin, Nabil Belacel, Pengcheng Xi, "Explainable Age Predictions from Electroencephalography Data", accepted to CVIS 2023: 9th Annual Conference on Vision and Intelligent Systems, Waterloo, Canada, December 2023

20. (2023) Grant Sinha, Nabil Belacel, Zhiyang Gu, Sam Doesburg, George Medvedev, Urs Ribary, Vasily Vakorin, Pengcheng Xi, Machine Learning Methods for Electroencephalogram-Based Age Prediction, Accepted to IEEE Sensors Conference 2023, Vienna, Austria, October 2023

21. (2023) Chi-en Amy Tai, Matthew Keller, Saeejith Nair, Yuhao Chen, Yifan Wu, Olivia Markham, Krish Parmar, Pengcheng Xi, Heather Keller, Sharon Kirkpatrick, and Alexander Wong. 2023. NutritionVerse: Empirical Study of Various Dietary Intake Estimation Approaches. In Proceedings of the 8th International Workshop on Multimedia Assisted Dietary Management (MADiMa '23). Association for Computing Machinery, New York, NY, USA, 11–19. https://doi.org/10.1145/3607828.3617799

22. (2023) Zhenyu Zhang, Yichun Shen, Julio J. Valdes, Saiful Huq, Bruce Wallace, James Green, Pengcheng Xi, Rafik Goubran, "Domestic Sound Classification with Deep Learning," 2023 IEEE Sensors Applications Symposium (SAS), Ottawa, ON, Canada, 2023, pp. 01-06, doi: 10.1109/SAS58821.2023.10254050.

23. (2023) Chi-en Amy Tai, Jason Li, Sriram Kumar, Saeejith Nair, Yuhao Chen, Pengcheng Xi, Alexander Wong, "NutritionVerse-Thin: An Optimized Strategy for Enabling Improved Rendering of 3D Thin Food Models", accepted to ICCV Women in CV Workshop, Oct. 2023, France

24. (2023) Chi-en A Tai, Matthew E Keller, Mattie Kerrigan, Yuhao Chen, Saeejith Nair, Pengcheng Xi, Alexander Wong, "NutritionVerse-3D: A 3D Food Model Dataset for Nutritional Intake Estimation", accepted to CVPR Women in CV workshop, June 2023, Canada

25. (2023) Grant Sinha, Krish Parma, Hilda Azimi, Amy Tai, Yuhao Chen, Alexander Wong, Pengcheng Xi, "Transferring Knowledge for Food Image Segmentation using Transformers and Convolutions", accepted to CVPR workshop on CV in the Wild, June 2023, Canada

26. (2023) S. Huq, P. Xi, R. Goubran, J. Valdes, F. Knoefel, J. Green, "Data Augmentation using Reverb and Noise in Deep Learning Implementation of Cough Classification", accepted to MeMeA 2023, June 2023, Korea.

27. (2022) Kai Ma, Siyuan He, Pengcheng Xi, Ashkan Ebadi, Stephane Tremblay, Alexander Wong, "A trustworthy framework for medical image analysis with deep learning", accepted to Annual Conference on Vision and Intelligent Systems 2022.

28. (2022) Chi-en Tai, Yuhao Chen, Matthew Keller, Mattie Kerrigan, Saeejith Nair, Pengcheng Xi, Alexander Wong, "Foodverse: A dataset of 3D food models for nutritional intake estimation", accepted to Annual Conference on Vision and Intelligent Systems 2022.

29. (2022) Hilda Azimi, Ashkan Ebadi, Jessy Song, Pengcheng Xi, Stephane Tremblay, Alexander Wong, "COVID-Net UV: An end-to-end spatio-temporal deep neural network architecture for automated diagnosis of COVID-19 infection from ultrasound videos", accepted to Annual Conference on Vision and Intelligent Systems 2022.

30. (2022) Julio Valdes, Karim Habashy, Pengcheng Xi, Madison Cohen-McFarlane, Bruce Wallace, Rafik Goubran, and Frank Knoefel, "Cough Classification with Deep Derived Features using Audio Spectrogram Transformer", accepted to the 2022 IEEE International Conference on Big Data (regular paper).

31. (2022) Jessy Song, Ashkan Ebadi, Adrian Florea, Pengcheng Xi, Alexander Wong, ''Detecting COVID-19 infection from ultrasound imaging with only five shots: A high-performing explainable deep few-shot learning network" accepted to MedNeurIPS 2022. 

32. (2022) K. Ma, P. Xi, K. Habashy, A. Ebadi, S. Tremblay,  A. Wong, 'Towards Trustworthy Healthcare AI: Attention-Based Feature Learning for COVID-19 Screening With Chest Radiography",  ICML 2022, Healthcare AI and COVID-19 Workshop, 2022. 

33. (2022) K. Habashy, J. Valdes, M. Cohen-McFarlane, P. Xi, B. Wallace, R. Goubran, F. Knoefel, "Cough Classification Using Audio Spectrogram Transformer", accepted to IEEE Sensors Applications Symposium 2022.

34. (2022) M. Cohen-McFarlane, F. Hassan, P. Xi, B. Wallace, R. Goubran, F. Knoefel, "Impact of Face Covering Models on Respiratory Sound Classification Applications", accepted to IEEE Sensors Applications Symposium 2022.

35. (2022) M. Kunz, C. Shu, M. Picard, D. Vera, P. Hopkinson, P. Xi, "Vision-based Ergonomic and Fatigue Analyses for Advanced Manufacturing", accepted to ICPS 2022, May 2022, UK.

36. (2022) M. Cohen-McFarlane, B. Wallace, P. Xi, R. Goubran, F. Knoefel, "Feasibility Analysis of the Fusion of Pressure Sensors and Audio Measurements for Respiratory Evaluations", accepted to MeMeA 2022, June 2022, Italy.

37. (2021) Siyuan He, Pengcheng Xi, Ashkan Ebadi, Stephane Tremblay, Alexander Wong, "Performance or Trust? Why Not Both. Deep AUC Maximization with Self-Supervised Learning for COVID-19 Chest X-ray Classifications", accepted to 7th Annual Conference on Vision and Intelligent Systems (CVIS 2021).

38. (2021) Ashkan Ebadi, Hilda Azimi, Pengcheng Xi, Stéphane Tremblay and Alexander Wong, COVID-Net FewSE: An Open-Source Deep Siamese Convolutional Network Model for Few-Shot Detection of COVID-19 Infection from X-Ray Images, accepted to 7th Annual Conference on Vision and Intelligent Systems (CVIS 2021).

39. (2021) Alexander MacLean, Ashkan Ebadi, Adrian Florea, Pengcheng Xi and Alexander Wong, An Initial Study into the Feasibility of Deep Learning-Based COVID-19 Severity Classification using Point-of-Care Ultrasound Imaging, accepted to 7th Annual Conference on Vision and Intelligent Systems (CVIS 2021).

40. (2021) Hilda Azimi, Pengcheng Xi, Miroslava Cuperlovic-Culf and Martha Vaughan, Perithecia Detection in Stubble Images Using Deep Learning, accepted to 2021 IEEE Symposium Series on Computational Intelligence (SSCI) (SSCI 2021), December 4th – 7th 2021, Orlando, Florida, USA.

41. (2021) MacLean, A., Abbasi, S., Ebadi, A., Zhao, A., Pavlova, M., Gunraj, H., Xi, P., Kohli, S. and Wong, A., 2021. COVID-Net US: A Tailored, Highly Efficient, Self-Attention Deep Convolutional Neural Network Design for Detection of COVID-19 Patient Cases from Point-of-care Ultrasound Imaging. In Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health (pp. 191-202). Springer, Cham..

42. (2021) G. Rouhafzay, Y. Li, H. Guan, C. Shu, R. Goubran, P. Xi, "Lesion Detection in Breast MRI by Deep Detector Integration", accepted to CVPR 2021 Workshop: Women in Computer Vision, June 19-25, 2021.

43. (2021) Ashkan Ebadi, Pengcheng Xi, Alexander MacLean, Stéphane Tremblay, Sonny Kohli, Alexander Wong, "COVIDx-US: An Open Benchmark Ultrasound Imaging Dataset for AI-Driven COVID-19 Diagnosis", accepted to ICLR 2021 Workshop: Machine Learning for Preventing and Combating Pandemics.

44. (2021) Jason Zhang, Pengcheng Xi, Alexander Wong, Ashkan Ebadi, Hilda Azimi, Stéphane Tremblay, "COVID-19 Detection from Chest X-ray Images using Imprinted Weights Approach", accepted to ICLR 2021 Workshop: Machine Learning for Preventing and Combating Pandemics.

45. (2021) J. Valdes, P. Xi, M. Cohen-McFarlane, B. Wallace, R. Goubran, F. Knoefel, "Analysis of cough sound measurements including COVID-19 positive cases: A machine learning characterization", accepted to IEEE MeMeA 2021 – International Symposium on Medical Measurements and Applications, June 2021.

46. (2021) M. Cohen-McFarlane, P. Xi, B. Wallace, J. Valdes, R. Goubran, F. Knoefel, "Impact of face coverings on the cough measurement characterization", accepted to IEEE MeMeA 2021 – International Symposium on Medical Measurements and Applications, June 2021.

47. (2020) S. Hajra, P. Xi, A. Law, "A Comparison of ECG and EEG metrics for in-flight monitoring of helicopter pilot workload", accepted to SMC 2020 - IEEE International Conference on Systems, Man and Cybernetics, Toronto, Canada, October 2020.

48. (2020) Y. Li, X. Zhu, R. Naud, P. Xi, "Capsule deep generative model that forms parse trees" accepted to International Joint Conference on Neural Networks (IJCNN), Glasgow, UK, July 2020. 

49. (2020) G. Rouhafzay, Y. Li, H. Guan, C. Shu, R. Goubran, P. Xi, "An Integrated Deep Approach for Lesion Detection in Breast MRI", accepted to ICPRAI 2020 - Second International Conference on Pattern Recognition and Artificial Intelligence, Zhongshan, China, May 2020 .

50. (2019) P. Xi, A. Law, R. Goubran, C. Shu, "Pilot Workload Prediction from ECG Using Deep Convolutional Neural Networks", IEEE MeMeA 2019 – International Symposium on Medical Measurements and Applications, Istanbul, Turkey, June 2019.  (Oral presentation)

51. (2019) P. Xi, R. Goubran, C. Shu, "A Unified Deep Learning Framework for Multi-Modal Multi-Dimensional Data", IEEE MeMeA 2019 – International Symposium on Medical Measurements and Applications, Istanbul, Turkey, June 2019.  (Oral presentation)

52. (2018) P. Xi, C. Shu, R. Goubran, "Abnormality Detection in Mammography using Deep Convolutional Neural Networks", IEEE MeMeA 2018 – International Symposium on Medical Measurements and Applications, Rome, Italy, June 2018. 

53. (2018) P. Xi, R. Goubran, C. Shu, "Cardiac Murmur Classification in Phonocardiograms using Deep Convolutional Neural Networks", ICPRAI 2018 - First International Conference on Pattern Recognition and Artificial Intelligence, Montreal, Canada, May 2018.  (Oral presentation)

54. (2017) C. Shu, P. Xi, A. Keefe, "Extracting Traditional Anthropometric Measurements from 3-D Body Scans ", accepted to the 5th International Digital Human Modeling Symposium, Bonn, Germany. June 26-28, 2017.

55. (2017) P. Xi, C. Shu, R. Goubran, "Localizing 3-D Anatomical Landmarks Using Deep Convolutional Neural Networks", 14th Conference on Computer and Robot Vision, Edmonton, Alberta, May 16-19, 2017. (Oral presentation)

56. (2016) A. Keefe, L. Bossi, C. Shu, P. Xi, M. Jones, "A framework for anthropometric and digital human modeling tools for the Canadian Armed Forces", The 4th International Digital Human Modeling Symposium (DHM2016), Montréal, Québec, Canada.

57. (2015) C. Shu, P. Xi, A. Keefe, "Data processing andanalysis for the 2012 Canadian Forces 3D anthropometric survey", Procedia Manufacturing, Volume 3, 2015, Pages 3745–3752, 6th International Conference on Applied Human Factors and Ergonomics (AHFE 2015).

58. (2014) A. Giachetti, E. Mazzi, F. Piscitelli, M. Aono, A. Ben Hamza, T. Bonis, P. Claes, A. Godil, C. Li, M. Ovsjanikov, V. Patraucean, C. Shu, J. Snyders, P. Suetens, A. Tatsuma, D. Vandermeulen, S. Wuhrer, P. Xi, "Automatic Location of Landmarks used in Manual Anthropometry", Eurographics Workshop on 3D Object Retrieval, 2014.

59. (2011) P. Xi, C. Shu, H. Guo, “Human Body Shape Prediction andAnalysis Using Predictive Clustering Tree", 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT), May 2011. (Oral presentation)

60. (2011) C. Shu, S. Wuhrer; P. Xi, “Geometric and Statistical Methodsfor Processing 3D Anthropometric Data”, International Symposium on Digital Human Modeling, June 14 - 16, 2011, Lyon, France.

61. (2010) J. Boisvert, F. Cheriet, C. Shu, P. Xi, H. Labelle, “A Web-Based Tool for Visualizing Scoliotic Trunk Surfaces Variations", Studies in Health Technology and Informatics, Volume 158: Research into Spinal Deformities 7, pp. 274-275, 2010.

62. (2009) P. Meunier, C. Shu, P. Xi, “Revealing the Internal Structureof Human Variability for Design Purposes," 17th World Congress on Ergonomics. August 2009.

63. (2009) C. Shu, P. Xi, Z. Ben Azouz, “Geometry Processing andStatistical Shape Analysis of 3D Anthropometry Data," 17th World Congress on Ergonomics. August 2009.

64. (2009) S. Wuhrer, C. Shu, J. Boisvert, G. Godin, P. Xi, “BendingInvariant Meshes and Application to Groupwise Correspondences", IEEE Workshop on Non-Rigid Shape Analysis and Deformable Image Alignment poster, 2009.

65. (2007) P. Xi, W.-S. Lee, C. Shu, “Analysis of Segmented Human BodyScans", Graphics Interface 2007, pp. 19-26. (Oral presentation)

66. (2007) P. Xi, W.-S. Lee, C. Shu, “A Data-Driven Approach to HumanBody Cloning Using a Segmented Body Database", Pacific Graphics 2007, pp. 139-147. (Oral)

67. (2007) P. Xi, C. Shu, M. Rioux, “Principal Components Analysis on3-D Scanned Human Heads", SIGGRAPH - International Conference and Exhibition on Computer Graphics and Interactive Techniques poster, 2007.

68. (2006) P. Xi, W.-S. Lee, G. Frederico, C. Joslin, L. Zhou, “Comprehending and Transferring Facial Expressions Based on Statistical Shapeand Texture Models", Computer Graphics International 2006, pp. 265-276. (Oral presentation)

69. (2005) P. Xi, T. Xu, Z. Zhao, “Knowledge-based Active Appearance Model Applied in Medical Image Localization", IEEE International Conference on Mechatronics and Automation 2005, pp. 637-642. (Oral presentation)

70. (2004) P. Xi, T. Xu, “De-noising and Recovering Images Based on Kernel PCA Theory", International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision poster, pp. 197-200, 2004.