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
Explainable AI
Complex Networks
Bioinformatics
Computational Biology
News
2024-09: Congratulations to Ronny Rochwerg on successfully definding his MSc thesis titled "Building interpretable learning models with evolutionary algorithms"!
2024-09: Congratulations to Emily Medema on successfully defending her MSc thesis titled "Why would the Internet lie to me?: Analyzing the performance of misinformation on Twitter utilizing large language models, machine learning, and evolutionary computing"!
2023-12: Congratulations to Zhendong on successfully defending his PhD thesis titled "Genetic data analysis and interpretation via feature selection and network science"!
2023-06: Congratulations to Kyle on successfully defending his PhD thesis titled "A deep generative model framework for creating high quality synthetic transaction sequences"!! We are so proud of Kyle, our lab's first PhD!
2023-05: Ting is named a Champion of Mental Health. Thanks to our students for the nomination and thanks to Queen's Campus Wellness for the recognition!
2023-05: Welcome undergraduate students Matthew Vandergrift and Shrinidhi Thatahngudi Sampath Krishnan joining our research group this summer!
2023-04: Congratulations to Emily on publishing her paper "A comprehensive framework for the development of ethical machine learning in medicine" at the Graduate Student Symposium (GSS) of the Canadian AI conference!
2023-02: Congratulations to Zhendong on publishing his paper "NSPA: characterizing the disease association of multiple genetic interactions at single-subject resolution" in the journal Bioinformatics Advances!
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 won the Best Student Award at the 19th IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB). This was also the First-Prize winning paper of ProjectX. Read about this here!
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!
2020-05: 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].
