Machine Intelligence & Biocomputing (MIB) Laboratory

Welcome to Machine Intelligence & Biocomputing (MIB) Laboratory! We develop new intelligent learning methods and complex network models for biomedical knowledge discovery.


Research Interests

  • Evolutionary Computing

  • Interpretable Machine Learning

  • Complex Networks

  • Bioinformatics

  • Computational Biology


News

  • 2022-10: Congratulations to Chengyuan on graduating with his M.Sc. research on "Biomedical data mining with evolutionary computing"!

  • 2022-10: Congratulations to Jinting on graduating with her M.Sc. research on "Quantitative analysis of genotype-to-phenotype mappings in evolutionary algorithms"!

  • 2022-09: Welcome our new M.Sc. students, Emily Medema, Ronny Rochewerg, and Suruthy Sivanathan! Look forward to an exciting journey with you!

  • 2022-07: Ting is promoted to Associate Professor with tenure (many thanks to my students who wrote support letters for me, to my graduate students for all the hard work, and to all my colleagues!)

  • 2022-07: Ting was invited to chair the GP track of the 2023 Genetic and Evolutionary Computation Conference (GECCO) in Lisbon, Portugal

  • 2022-06: Our undergraduate researchers, Awni Altabaa, David Huang, Ciaran Byles-Ho, Hani Khatib, and Fabian Sosa, have their paper on "geneDRAGNN: Gene Disease Prioritization using Graph Neural Networks" accepted for publication and presentation at the 19th IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB). This was also the first-prize winning paper of ProjectX. Can't be more proud of our undergraduate students!

  • 2022-06: Our paper on "Banksformer: A Deep Generative Model for Synthetic Transaction Sequences" has been accepted for publication and presentation at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD)

  • 2022-04: Our paper on "A bio-inspired framework for machine bias interpretation" has been accepted for publication and presentation at AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES)

  • 2022-03: Our paper on "Genetic heterogeneity analysis using genetic algorithm and network science" has been accepted for publication and presentation at Genetic and Evolutionary Computation Conference (GECCO)

  • 2022-03: Our paper on "Regulatory genotype-to-phenotype mappings improve evolvability in genetic programming" has been accepted for publication and presentation at Genetic and Evolutionary Computation Conference (GECCO)

  • 2022-01: Our paper on "Permutation-invariant representation of neural networks with neuron embeddings" has been accepted for publication and presentation at European Conference on Genetic Programming (EuroGP)

  • 2022-01: Our paper on "Creating diverse ensemble for classification with genetic programming and neuro-MAP-Elites" has been accepted for publication and presentation at European Conference on Genetic Programming (EuroGP)

  • 2021-07: Our paper on "Feature selection for polygenic risk scores using genetic algorithm and network science" has been accepted for publication and presentation at IEEE Congress on Evolutionary Computation (CEC)

  • 2021-07: Our paper on "An evolutionary approach to interpretable learning" has been accepted for publicatio and presentation at Genetic and Evolutionary Computation Conference (GECCO)

  • 2021-07: Our paper on "Principled quality diversity for ensemble classifiers using MAP-Elites" has been accepted for publicatio and presentation at Genetic and Evolutionary Computation Conference (GECCO)

  • 2021-05: Our paper on "SMILE: Systems metabolomics using interpretable learning and evolution" has been accepted for publication in BMC Bioinformatics

  • 2020-05: Welcome undergraduate student Philippe Rivet (NSERC Undergraduate Student Research Award) joining our research group this summer!

  • 2021-05: Congratulations to Shengkai on graduating with his MSc research on "Genome-wide association study of colorectal cancer using evolutionary computing"!

  • 2021-04: Congratulations to Arshad on graduating with his MSc research on "Metamarker: Differential correlation network methodology and software for metabolomic data analysis"!

  • 2020-12: Ting received the School of Computing's annual Howard Staveley Teaching Award! Thanks to our undergraduate students for the nomination!

  • 2020-12: Our paper on "Statistical methods with exhaustive search in the identification of gene-gene interactions for colorectal cancer" has been accepted for publication in Genetic Epidemiology

  • 2020-10: Ting was invited to give a keynote speech at the CSearch conference. Here is a video recording of the talk.

  • 2020-09: Welcome our new PhD student Ryan Zhou!

  • 2020-08: Congratulations to our undergraduate student Chengyuan Sha on receiving Mitacs Research Training Award!

  • 2020-07: Welcome undergraduate student Tristan Samis joining our research group!

  • 2020-05: Welcome undergraduate students Jake Robertson (NSERC Undergraduate Student Research Award) and Jinting Zhang (Queen's School of Computing Undergraduate Research Fellowship) joining our research group this summer!

  • 2020-04: Presented our recent work on "Classification of autism genes using network science and linear genetic programming" virtually at EuroGP conference! A video clip can be found here.

  • 2020-03: Our paper on "Sports games modeling and prediction using genetic programming" has been accepted for presentation and publication in IEEE Congress on Evolutionary Computation (CEC) 2020

  • 2020-02: The new special issue of the journal Genetic Programming and Evolvable Machines, edited by Ting and colleagues, is out!

  • 2020-01: Our paper on "PANDA: prioritization of Autism-genes using network-based deep-learning approach" has been accepted for publication in Genetic Epidemiology

  • 2020-01: Our paper on "A network perspective on genotype-phenotype mapping in genetic programming" has been accepted for publication in Genetic Programming and Evolvable Machines

  • 2020-01: Our paper on "Classification of autism genes using network science and linear genetic programming" was accepted for publication in EuroGP 2020

  • 2019-12: Ting was interviewed by the School of Computing at Queen's as a new faculty member. Here is the interview video.

  • 2019-10: Ting was invited to give a keynote speech at the Artificial Intelligence for Design conference hosted by NRC

  • 2019-10: Congratulations to Yu on graduating with her MSc research on "PANDA: Prioritization of Autism-genes using network-based deep-learning approach"!

  • 2019-09: Our MIB lab relocated to the School of Computing at Queen's University

  • 2019-09: Congratulations to Songyuan on graduating with his MSc research on "Deep learning for genome-wide association studies and the impact of SNP locations"!

  • 2019-07: Ting was selected to serve as a member of the Computer Science Evaluation Group, NSERC Discovery Grant

  • 2019-07: Ting was interviewed by the VOCM radio station, program Open Line with Paddy Daly! Here is the interview clip

  • 2019-06: Ting and our MIB research were featured in The Gazette!

  • 2019-04: Ting was selected to chair the 23rd European Conference on Genetic Programming (EuroGP) 2020 in Seville, Spain

  • 2019-04: Our paper on "Computational methods for the discovery of metabolic markers of complex traits" was accepted for publication in Metabolites

  • 2019-02: Our paper on "Measuring the importance of vertices in the weighted human disease network" was accepted for publication in PLoS ONE

  • 2019-02: Our paper on "A network approach to prioritizing susceptibility genes for genome-wide association studies" was accepted for publication in Genetic Epidemiology

  • 2019-01: Our paper on "Complex network analysis of a genetic programming phenotype network" was accepted for publication in EuroGP 2019

  • 2019-01: Our paper on "Fault detection and classification for induction motors using genetic programming" was accepted for publication in EuroGP 2019

  • 2018-10: Our paper on "Ensemble learning for detecting gene-gene interactions in colorectal cancer" was accepted for publication in PeerJ

  • 2018-09: Welcome medical student Michael Lee to join our lab for research!

  • 2018-08: Ting was selected to chair the GP track of the 2019 Genetic and Evolutionary Computation Conference (GECCO) in Prague, Czech Republic

  • 2018-06: Welcome Science Undergraduate Research Award (SURA) student Ling Xu to join our lab this summer!

  • 2018-05: Congratulations to Mehrzad on graduating with his MSc research on "Investigation of vertex centralities in human gene-disease networks"!

  • 2018-05: Welcome our new lab member Kyle Nickerson (MSc)!

  • 2018-04: Ting was selected to chair the 22nd European Conference on Genetic Programming (EuroGP) 2019 in Leipzig, Germany

  • 2018-03: Our paper on "Measuring evolvability and accessibility using the hyperlink-induced topic search algorithm" was accepted for publication in GECCO 2018

  • 2018-03: Our first Master's student Fara has graduated with his thesis research on "Ensemble learning for detecting gene-gene interactions in colorectal cancer"!

  • 2018-02: Our paper on "Analyzing feature importance for metabolomics using genetic programming" was nominated Best Paper Award at EuroGP 2018

  • 2018-01: We received new funding from Memorial University to seed our research on the discovery of genetic markers in human diseases using evolutionary learning algorithms

  • 2018-01: Our paper on "An evolutionary learning and network approach to identifying key metabolites for osteoarthritis" was accepted for publication in PLoS Computational Biology

  • 2018-01: Our paper on "Analyzing feature importance for metabolomics using genetic programming" was accepted for publication in EuroGP 2018

  • 2018-01: Our paper on "Feature selection for detecting gene-gene interactions in genome-wide association studies" was accepted for publication in EvoApplications 2018

  • 2018-01: Welcome our new lab member Shengkai Geng (MSc)!

  • 2017-09: Welcome four new members to our lab, Asma (PhD), Zhendong (PhD), Arshad (MSc), and Yu(MSc)!

  • 2017-04: Our paper on "Lexicase selection promotes effective search and behavioural diversity of solutions in linear genetic programming" was accepted for publication in IEEE CEC 2017

  • 2016-11: Ting was selected for the Best Professor Award of the Department of Computer Science by the Computer Science Graduate Society (CSGS)


Available positions

We are recruiting M.Sc. and Ph.D. students. Applicants who are enthusiastic about our research are welcome to email Ting with your resume and research statement for an inquiry. Applicants who have an outstanding academic record and a research background in evolutionary computing, machine learning, and bioinformatics will be given a priority for consideration. In your inquiry email, please use the title [MIB lab research position inquiry].

We also always look forward to working with undergraduate students who would like to gain research experiences in machine learning, artificial intelligence, and biomedical computing. Please email Ting for potential research projects using the title [MIB lab undergraduate research project inquiry].