Shi-ang Qi

I am a Ph.D. student in the Department of Computing Science at the University of Alberta, under the mentorship of Dr. Russell Greiner. In addition, I work closely alongside Dr. Neeraj Kumar, contributing to extensive machine learning research projects focused in the healthcare sector.

In 2020, I obtained my M.Sc. degree in the Department of Electrical and Computer Engineering from the University of Alberta in 2020, where I was supervised by Dr. Jie Chen. Prior to this, I completed my Bachelor's degree in Biomedical Engineering at Huazhong University of Science and Technology in China.

My research passion lies at the intersection of machine learning, deep learning, bioinformatics, survival analysis, and causal inference, all within the context of healthcare applications. Currently, I'm particularly interested in the theoretical optimization of survival analysis. I also work on building effective and interpretable survival models (individual survival distributions) for identifying actionable factors of breast cancer, which is part of an ongoing collaboration with Alberta's Tomorrow Project.

Email / CV / Google Scholar / Github / Linkedin

Publication

My research direction is very multidisciplinary. My general research interests focus on machine/deep Learning for healthcare, bioinformatics, survival analysis, and causal inference for medicine tasks. Currently, I'm particularly interested in building reliable and interpretable survival models which generate individual survival distributions. I'm also interested for identifying actionable factors of breast cancer, which is collaborating with the Alberta's Tomorrow Project. Other research experiences involve recommendation system, multimodal sentiment analysis, computational psychiatry, intersection of machine learning and metabolomics, and therapeutic applications of low-intensity pulsed ultrasound.

* Equal contribution authorship.

	Conformalized Survival Distributions: A Generic Post-Process to Increase Calibration Shi-ang Qi, Yakun Yu, Russell Greiner International Conference of Machine Learning (ICML 2024) pdf/ code
	SurvivalEVAL: A Comprehensive Open-Source Python Package for Evaluating Individual Survival Distributions Shi-ang Qi, Weijie Sun, Russell Greiner Second Symposium on Survival Prediction: Algorithms, Challenges, and Applications (SPACA) pdf / code / bibtex
	Predicting Individual Survival Distributions Using ECG: A Deep Learning Approach Utilizing Features Extracted by a Learned Diagnostic Model Weijie Sun, Sunil V Kalmady, Shi-ang Qi, Nariman Sepehrvand, Abram Hindle, Russell Greiner, Padma Kaul Second Symposium on Survival Prediction: Algorithms, Challenges, and Applications (SPACA) pdf / bibtex
	Supervised Electrocardiogram(ECG) Features Outperform Knowledge-based And Unsupervised Features In Individualized Survival Prediction Yousef Nademi, Sunil V Kalmady, Weijie Sun, Shi-ang Qi, Abram Hindle, Padma Kaul, Russell Greiner Machine Learning for Health (ML4H 2023) pdf / bibtex
	iHAS: Instance-wise Hierarchical Architecture Search for Deep Learning Recommendation Models Yakun Yu, Shi-ang Qi, Jiuding Yang, Liyao Jiang, Di Niu Conference on Information and Knowledge Management (CIKM 2023) pdf / bibtex
	Using Bayesian Neural Networks to Select Features and Compute Credible Intervals for Personalized Survival Prediction Shi-ang Qi, Neeraj Kumar, Ruchika Verma, Jian-Yi Xu, Grace Shen-Tu, Russell Greiner IEEE Transactions on Biomedical Engineering (TBME 2023) pdf / code / bibtex
	An Effective Meaningful Way to Evaluate Survival Models Shi-ang Qi, Neeraj Kumar, Mahtab Farrokh, Weijie Sun, Li‑Hao Kuan, Rajesh Ranganath, Ricardo Henao, Russell Greiner International Conference on Machine Learning (ICML, 2023) pdf / code / bibtex / poster / video
	ConKI: Contrastive Knowledge Injection for Multimodal Sentiment Analysis Yakun Yu, Mingjun Zhao, Shi-ang Qi, Feiran Sun, Baoxun Wang, Weidong Guo, Xiaoli Wang, Lei Yang, Di Niu Findings of the Association for Computational Linguistics (ACL, 2023) pdf / code / bibtex
	Exploring Language-Agnostic Speech Representations Using Domain Knowledge for Detecting Alzheimer's Dementia Zehra Shah, Shi-ang Qi, Fei Wang, Mahtab Farrokh, Mashrura Tasnim, Eleni Stroulia, Russell Greiner, Manos Plitsis, Athanasios Katsamanis IEEE International Conference on Acoustics, Speech and Singal Processing (ICASSP, 2023) pdf / bibtex / video / news
	Personalized breast cancer onset prediction from lifestyle and health history information Shi-ang Qi, Neeraj Kumar, Jian-Yi Xu, Jaykumar Patel, Sambasivarao Damaraju, Grace Shen-Tu, Russell Greiner* PLOS One, 2022 pdf / bibtex
	Learning accurate personalized survival models for predicting hospital discharge and mortality of COVID‑19 patients Neeraj Kumar, Shi-ang Qi*, Li‑Hao Kuan, Weijie Sun, Jianfei Zhang, Russell Greiner Scientific Reports, 2022* pdf / code / bibtex
	High-resolution metabolomic biomarkers for lung cancer diagnosis and prognosis Shi-ang Qi, Qian Wu, Zhenpu Chen, Wei Zhang, Yongchun Zhou, Kaining Mao, Jia Li, Yuanyuan Li, Jie Chen , Youguang Huang, Yunchao Huang Scientific Reports, 2021 pdf / bibtex
	Learning Language and Acoustic Models for Identifying Alzheimer’s Dementia From Speech Zehra Shah, Jeffrey Sawalha, Mashrura Tasnim, Shi-ang Qi, Eleni Stroulia, Russell Greiner Frontiers in Computer Science, 2021 pdf / bibtex
	Safety Assessment of a Wearable Low-Intensity Pulsed Ultrasound Device for Relieving Mental Illness Symptoms Shi-ang Qi, Jie Chen IEEE Engineering in Medicine & Biology Society (EMBC 2020) pdf / bibtex
	A Review of Low-Intensity Pulsed Ultrasound for Therapeutic Applications Xiaoxue Jiang, YOleksandra Savchenko, Yufeng Li, Shi-ang Qi, Tianlin Yang, Wei Zhang, Jie Chen IEEE Transactions on Biomedical Engineering (TBME 2018) pdf / bibtex
	Design of a novel wearable lipus treatment device for mental health treatment Shi-ang Qi, Yufeng Li, Wei Zhang, Jie Chen IEEE Engineering in Medicine & Biology Society (EMBC 2018) pdf / bibtex

Competitions and Challenges

ICASSP 2023 SPGC Challenge : Multilingual Alzheimer's Dementia Recognition through Spontaneous Speech

4th place Globally, 1st place in North America, see leaderboard
News: Machine learning model able to detect signs of Alzheimer’s across languages

The ADReSS Challenge : Alzheimer's Dementia Recognition through Spontaneous Speech

3rd place Globally in Classfication task

Professional Service

Journal Reviewer

AIJ (Co-reviewer) 2022

IEEE JTEHM 2019

IEEE TBioCAS 2017

Conference Reviewer

NeurIPS 2023 (Co-reviewer), 2024

SPACA 2023

IEEE ICDM 2021

Teaching Experience

Fall 2022 - CMPUT 261: Introduction to Artificial Intelligence

Winter 2021/2022 - CMPUT 366: Intelligent Systems

Fall 2020/2023 - CMPUT 101: Introduction to Computing

Winter 2020 - ECE 212: Introduction to Microprocessors

Winter 2019 - ENCMP 100: Computer Programming for Engineers

Fall 2018/2019 - ECE 312: Embedded System Design

Fall 2017 - ECE 340: Discrete Time Signals and Systems

Misc.

During my free time, I enjoy swimming, snowboarding, and hiking with my family. I'm also a big fan of Miami Heat basketball team and Real Madrid football club. ¡Hala Madrid!

Website Credits to Jon Barron source code and Xin Liu source code