Curriculum Vitae

Xuezhi Xie

PhD student, Department of Computer Science, University of Toronto

Education

• Ph.D in Computer Science, University of Toronto, 2020 - 2024 (expected)
• M.S. in Computer Science, specialization in Artificial Intelligence, Western University, 2018 - 2020
• B.S. in Biology, Minor in Computer science, University of Waterloo, 2012 - 2016

Work experience

• Research assistant (machine learning) - University of Toronto, Toronto, On, Canada, 2020 - present
  • Developed a deep generative model for novel dextrorotary helical conformations to facilitate the peptide drug design.
  • Developed and implemented various MCMC searches to optimize the synthetic data with optimized pharmetutical properties. Published the work as first author in NeuIPS Workshop (MLSB) 2021.
  • Pre-trained a graph convolutional network to reconstruct masked amino acids in proteins
  • Supervisor: Professor Philip M. Kim
• AI developer & Research assistant - Kaizhong’s lab, Western University, London, On, Canada, Sep.2018 - Apr. 2020
  • Collected peptide data from online databases (IEDB, IPD-MHC). Preprocessed, and analyzed data by using PySpark
  • Implemented and compared decision tree- and neural network-based models for predicting peptide binding.
  • Designed and developed a novel CNN-LSTM model to solve a mhc-ligand binding classification task. Achieved state of the art performance (AUC : 92.3%).
  • Published the work as first author in IEEE-BIBM (2019) and IJDMB(2020).
  • Supervisor: Professor Kaizhong Zhang

Skills

• Languages: Java, Python, C, C#, C++, JavaScript
• Software: Eclipse, Jupyter, Visual Studio/Code
• Database: SQL, MongoDB
• Frameworks: Keras, Pytorch, Tensorflow, PySpark, Hadoop MapReduce
• System: Linux, Windows
• Version Control: Git/GitHub
• Machine learning: Proficient in deep Convolutional Neural Network, LSTM, logistic regression, support vector machine, decision tree, random forest, GBDT, naive bayes, k-means, PCA, collaborative filtering.
• Computer vision: Skilled in image processing (OpenCV), object detection, object segmentation, mapping and localization, and SLAM.
• Natural language processing: Skilled in text classification, sentiment analysis and speech recognition

Publications

Antibody-SGM: Antigen-Specific Joint Design of Antibody Sequence and Structure using Diffusion Models

Xie, Xuezhi et al. "Antibody-SGM: Antigen-Specific Joint Design of Antibody Sequence and Structure using Diffusion Models." ICML - Computational Biology (2023).

HelixGAN a deep learning methodology for conditional de novo design of α-helix structures

Xie, Xuezhi, Pedro A. Valiente, and Philip M. Kim. "HelixGAN a deep-learning methodology for conditional de novo design of α-helix structures." Bioinformatics 39.1 (2023): btad036.

HelixGAN: A bidirectional Generative Adversarial Network with search in latent space for generation under constraints

Xie, &Kim . (2021). HelixGAN: A bidirectional Generative Adversarial Network with search in latent space for generation under constraints, Machine Learning for Structural Biology (MLSB) Workshop at NeurIPS.

MHCherryPan, a novel pan-specific model for binding affinity prediction of class I HLA-peptide

Xuezhi Xie, et al. MHCherryPan, a novel pan-specific model for binding affinity prediction of class I HLA-peptide, Int. J. Data Mining and Bioinformatics , Vol. 24, No. 3, 2020

MHCherryPan. a novel model to predict the binding affinity of pan-specific class I HLA-peptide

Xuezhi Xie, et al. (2019) MHCherryPan, a novel model to predict the binding affinity of pan-specific class I HLA-peptide IEEE International Conference on Bioinformatics and Biomedicine.