Nadia Tahiri

Financement

• Subvention. (Obtenu). Cochercheur. Novel Metrics for the Comparison of Networks. Fonds Québécois de la Recherche sur la Nature et les Technologies (FQRNT). NOVA - FRQNT-NSERC PROGRAM for early-career researchers (PILOT). 225 000 $. (2023-2026)
• Subvention. (Obtenu). Chercheur principal. Établissement de la relève professorale - Nouvelle approche du regroupement des arbres phylogénétiques par l'exploration du projet de l'Arbre de Vie. Fonds de recherche du Québec - Nature et technologies (FRQNT). 99 060 $. (2023-2025)
• Subvention. (Obtenu). Chercheur principal. Subvention de démarrage - nouvelle professeure. Université de Sherbrooke. Starting grant. 30 000 $. (2021-2024)
• Subvention. (Obtenu). Chercheur principal. New algorithms for inferring multiple alternative consensus trees and supertrees. Conseil de Recherches en Sciences Naturelles et Génie du Canada (CRSNG). Tremplin vers la découverte. 12 500 $. (2022-2024)
• Subvention. (Obtenu). Candidat principal. Intégration de solutions numériques pour optimiser les processus de fermentation en microbrasserie (organisme partenaire : Siboire Microbrasserie). Mathematics of Information Technology and Complex Systems (MITACS). 10 000 $. (2023-2024)
• Subvention. (Obtenu). Candidat principal. Machine Learning in Public Health. Mathematics of Information Technology and Complex Systems (MITACS). 30 000 $. (2023-2023)
• Subvention. (Obtenu). Candidat principal. iPhylogeo: Analysis of genetic and climatic data. Mathematics of Information Technology and Complex Systems (MITACS). 15 000 $. (2023-2023)
• Subvention. (Terminé). Collaborateur. Création d'un pôle francophone en toxicologie prédictive. (2021-2023)
• Subvention. (Terminé). Chercheur principal. Centre de recherche en écologie de l’UdeS (CREUS). (2022)
• Subvention. (Terminé). Candidat principal. Stage en apprentissage automatique pour la Fabrication Additive (organisme partenaire : 3DSémantix). ITEA Award of Excellence - Innovation 2023. Mathematics of Information Technology and Complex Systems (MITACS). 15 000 $. (2022-2022)
• Bourse de recherche. (Terminé). Candidat principal. Élaboration d'une nouvelle approche pour évaluer les risques liés à l'exposition des enfants aux contaminants de l'environnement (dossier classé au 1er rang au FRQS). Fonds de recherche du Québec - Santé (FRQS). 90 000 $. (2020-2021)
• Bourse de recherche. (Terminé). Candidat principal. Apprentissage machine appliquée pour détection de fraudes pour régimes d'assurances collectives (organisme partenaire : Segic Inc.). Mathematics of Information Technology and Complex Systems (MITACS). Accelerate. 90 000 $. (2018-2019)
• Bourse d’études. (Terminé). Candidat principal. Algorithmes bioinformatiques pour la reconstruction d'arbres consensus multiples. Fonds Québécois de la Recherche sur la Nature et les Technologies (FQRNT). Doctoral Research Scholarships. 46 666 $. (2013-2015)

Publications

Articles de revue

• Koshkarov, A*; Tahiri, N. (2023). GPTree Cluster: phylogenetic tree cluster generator in the context of supertree inference. Bioinformatics Advances 3 (1), vbad023. (Article publié).
• Li, W.*; Tahiri, N. (2023). Host-Virus Cophylogeny Trajectories: Investigating Molecular Relationships between Coronaviruses and Bat Hosts. BMC Ecology and Evolution (Article soumis).
• Tahiri, N; Fichet, B; Makarenkov, V. (2022). Building alternative consensus trees and supertrees using k-means and Robinson and Foulds distance. Bioinformatics 38 (13), 3367-3376. (Article publié).
• Tahiri, N; Veriga, A; Koshkarov, A*; Morozov, B. (2022). Invariant transformers of Robinson-Foulds distance matrices for convolutional neural network. Journal of Bioinformatics and Computational Biology 20 (4), 2250012. (Article publié).
• Tahiri, N; Koshkarov, A*. (2022). New metrics for classifying phylogenetic trees using k-means and the symmetric difference metric. Classification and Data Science in the Digital Age, Springer Verlag (Article accepté).
• Marchitti, SA; Verner, MA; Tahiri, N; Dillingham, C; Chang, D; LaKind, JC; Hines, E; Fenton, S; Kenneke, JF; Goldsmith, MR. (2022). Predicting Breast Milk:Serum Partitioning Using QSAR Models. Chemical Research in Toxicology (Article soumis).
• Lévêque, L*; Tahiri, N; Goldsmith, MR; Verner, MA. (2022). Quantitative Structure-Activity Relationship (QSAR) Modeling to Predict the Transfer of Environmental Chemicals across the Placenta. Computational Toxicology (the first two authors are equal contributors and listed in alphabetical order) 21 100211. (Article publié).
• Chabane, N; Bouaoune, MA; Tighilt, RAS; Boc, A; Lord, E; Tahiri, N; Mazoure, B; Makarenkov, V. (2022). Using Clustering and Machine Learning Algorithms for Intelligent Personalized Shopping Recommendation. Plos one 17 (12), e0278364. (Article publié).
• Chabane, N; Bouaoune, MA; Tighilt, RAS; Mazoure, B; Tahiri, N; Makarenkov, V. (2022). Using clustering and machine learning methods to provide intelligent grocery shopping recommendations. Classification and Data Science in the Digital Age, Springer Verlag (Article accepté).
• Kuitche, E; Qi, Y; Tahiri, N; Parmer, J; Ouangraoua, A. (2020). DoubleRecViz: A Web-Based Tool for Visualizing Transcript-Gene-Species reconciliation. Bioinformatics 37 (13), 1920-1922. (Article publié).
• Tahiri, N; Willems, M; Makarenkov, V. (2018). A new fast method for inferring multiple consensus trees using k-medoids. BMC evolutionary biology 18 (48), 1-12. DOI. (Article publié).
• Willems, M; Tahiri, N; Makarenkov, V. (2018). Building explicit hybridization networks using the maximum likelihood and Neighbor-Joining approaches. Archives of Data Science, Series A 4 (1), 1-17. DOI. (Article publié).
• Willems, M; Tahiri, N*; Makarenkov, V. (2015). A new efficient algorithm for inferring explicit hybridization networks following the Neighbor-Joining principle. Journal of Bioinformatics and Computational Biology 12 (5), 1450024. DOI. (Article publié).

Chapitres de livre

• Makarenkov, V; Barseghyan, GS*; Tahiri, N. (2022). Inferring multiple consensus trees and supertrees using clustering: a review. Data Mining is More Than Comprehensive Analysis (1-33). Springer Nature. (Article soumis).
• Cordeiro de Amorim, R; Tahiri, N; Mirkin, B; Makarenkov, V. (2017). A Median-Based Consensus Rule for Distance Exponent Selection in the Framework of Intelligent and Weighted Minkowski Clustering. Data Science (97-110). Springer Verlag. DOI. (Article publié).
• Badescu, D; Tahiri, N; Makarenkov, V. (2016). A new fast method for detecting and validating horizontal gene transfer events using phylogenetic trees and aggregation functions. Pattern Recognition in Computational Molecular Biology: Techniques and Approaches. (1, 483-504). Wiley. DOI. (Article publié).

Articles de conférence

• Mbaye Mouhamadou, M*; Abu Salem, F*; Tahiri, N. (2023). A new machine learning workflow to create an optimal waiting list in hospitals. 7th International Conference on Medical and Health Informatics (ICMHI 2023). (Article accepté).
• Koshkarov, A.*;Tahiri, N. (2023). GPTree: Generator of Phylogenetic Trees with Overlapping and Biological Events for Supertree Inference. Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - BIOINFORMATICS. (Article publié).
• Koshkarov, A*; Tahiri, N. (2023). Novel algorithm for comparing phylogenetic trees with different but overlapping taxa. RECOMB-CG. (Article soumis).
• Li, W*; Tahiri, N. (2023). aPhyloGeo-Covid: A web interface for phylogeographic analysis of SARS-CoV-2 variation using Neo4j and Snakemake. Proceedings of the 22nd Python in Science Conference, (Article accepté).
• Tahiri, N; Koshkarov, A*. (2022). New metrics for classifying phylogenetic trees using k-means and the symmetric difference metric. International Federation of Classification Societies (IFCS). (Article accepté).
• Li, W*; Koshkarov, A*; Luu, ML*; Tahiri, N. (2022). Phylogeography: Analysis of genetic and climatic data of SARS-CoV-2. Proceedings of the 21st Python in Science Conference, (Article accepté).
• Koshkarov, A*; Li, W*; Luu, ML*; Tahiri, N. (2022). Phylogeography: Analysis of genetic and climatic data of SARS-CoV-2. Scientific Computing with Python (SciPy). (Article accepté).
• Chabane, N; Bouaoune, MA; Tighilt, RAS; Mazoure, B; Tahiri, N; Makarenkov, V. (2022). Using Clustering and Machine Learning Methods to Provide Intelligent Grocery Shopping Recommendations. International Federation of Classification Societies (IFCS). (Article accepté).
• Bocéno, A; Bloch, S; Tahiri, N; Verner, MA. (2021). Comparing an Acceptable Exposure Level Based on In Vitro Studies of PFOA Hepatotoxicity to Levels Measured in Epidemiologic Studies. Society of Toxicology (SOT), virtual conference. (Article publié).
• Tahiri, N. (2021). Invasive insects through phylogeography. 12th Annual symposium of Quebec Centre for biodiversity science (QCBS). (Article publié).
• Li, W*; Luu, ML*; Tahiri, N. (2021). La phylogéographie : à la recherche de la vérité lorsque tout est en mouvement. Nuit des chercheuses et des chercheurs (Finaliste du concours de vulgarisation scientifique). (Article accepté).
• Lévêque, L*; Tahiri, N; Goldsmith, MR; Verner, MA. (2021). Quantitative Structure-Activity Relationship (QSAR) Modeling to Predict the Transfer of Environmental Chemicals Across the Placenta. American Society for Cellular and Computational Toxicology (ASCCT). (Article publié).
• Aouabed, Z; Abdar, M; Tahiri, N; Champagne Gareau, J; Makarenkov, V. (2020). A Novel Effective Ensemble Model for Early Detection of Coronary Artery Disease. Learning and Analytics in Intelligent Systems (Springer), 480-489. (Article publié).
• Bocéno, A; Bloch, S; Tahiri, N; Verner, MA. (2020). A case study evaluating the use of in vitro data on perfluorooctanoic acid (PFOA) hepatotoxicity to derive acceptable exposure levels. The Society of Toxicology of Canada (STC), virtual conference. (Article publié).
• Tahiri, N; Lévêque, L*; Verner, MA. (2020). Predicting the Transfer of Chemicals through Lactation Using Quantitative Structure-Activity Relationship (QSAR) Modeling. Society of Toxicology (SOT). (Article publié).
• Tahiri, N; Mazoure, B; Makarenkov, V. (2019). An intelligent shopping list based on the application of partitioning and machine learning algorithms. Proceedings of the 18th Python in Science Conference, 85 - 92. (Article publié).
• Lévêque, L*; Tahiri, N; Verner, MA. (2019). Predicting the placental transfer of chemicals using quantitative structure-activity relationship (QSAR) modeling. Society of Toxicology of Canada (STC). (Article publié).
• Tahiri, N; Lévêque, L*; Verner, MA. (2019). Quantitative structure-activity relationship (QSAR) modeling as a tool to assess lactational exposure for data-poor chemicals. Society of toxicology of Canada (STC). (Article publié).
• Tahiri, N. (2018). A new fast method for inferring multiple consensus trees using k-medoids. Canadian Celebration of Women in Computing (CAN-CWiC). (Article publié).
• Tahiri, N. (2018). An intelligent shopping list based on partitioning and machine learning algorithms. Neural Information Processing Systems (NeurIPS). (Article publié).
• Tahiri, N. (2017). A new clustering method for building multiple supertrees using k-means. Proceedings of NIPS-2017, (Article publié).
• Tahiri, N; Willems, M; Makarenkov, V. (2017). A new fast method for building multiple consensus trees using k-medoids. Proceedings of SMC-2017, 31-37. (Article publié).
• Tahiri, N; Badran, N; Dion-Phénix, H; Meniaï, I; Makarenkov, V. (2017). Avancement des connaissances en bioinformatique en développant un nouvel algorithme pour l’analyse des arbres phylogeographiques. Association Canadienne-Française pour l'Avancement des Sciences (ACFAS). (Article publié).
• Tahiri, N; Badran, N. (2016). New algorithm to find the relation between genetic and geographic distribution of species. Symposium Sciences biologiques. (Article publié).
• Tahiri, N*; Willems, M; Makarenkov, V. (2015). Inférence des super-arbres multiples en utilisant l'algorithme des k-moyennes. Proceedings of SFC-2015, 110-114. (Article publié).
• Cordeiro de Amorim, R; Tahiri, N*; Mirkin, BG; Makarenkov, V. (2015). Minkowski weighted k-means clustering with amedian-based consensus rule. Proceedings of IFCS-2015, 90-110. DOI. (Article publié).
• Tahiri, N; Willems, M; Makarenkov, V. (2014). Classification d’arbres phylogénétiques basée surl’algorithme des k-moyennes. Proceedings of SFC-2014, 49-54. (Article publié).
• Tahiri, N*; Boc, A; Willems, M*; Makarenkov, V. (2012). Classification des langues Indo-Européennes basée sur un modèle d’identification de transferts horizontaux de gènes. Proceedings of SFC-2012, (Article publié).
• Rahman Sifat, MH*; Tahiri, N. New Algorithm to Building Comprehensive Consensus Trees. AAAI (GCLR), Canada, (Article accepté).

Autres contributions

Gestion d'évènements

• Scientific committee member. (2021-2024) Google Developer Groups (GDG) Cloud Sherbrooke, virtual conference, GDG 2021. (Conférence).
• Co-chair, Financial Aid Committee. (2022) for Scientific Computing with Python (SciPy), virtual conference, SciPy 2022. (Conférence).
• Co-chair. (2021) Birds of a Feather Committee for Scientific Computing with Python (SciPy), virtual conference, SciPy 2021. (Conférence).
• Committee Member, Organizing committee and Program committee. (2016-2021) Montreal Bioinformatics Users Group (MonBUG). (Séminaire).
• Committee Member. (2021) Program committee of the 1st International Applied Bioinformatics Conference (iABC), Istanbul University, Turkey, iABC 2021. (Conférence).
• Scientific committee member. (2021) Women Techmakers Montreal (WTM), virtual conference, WTM 2021. (Conférence).
• Co-Chair. (2020) Financial Aid Committee for Scientific Computing with Python (SciPy), Austin, TX, USA, SciPy 2020. (Conférence).
• Scientific committee member. (2020) Women Techmakers Montreal (WTM), virtual conference, WTM 2020. (Conférence).
• Committee Member, Organizing committee and Program committee. (2019) Scientific Computing with Python (SciPy), Austin, TX, USA, SciPy 2019. (Conférence).
• Scientific committee member. (2019) Women Techmakers Montreal (WTM), Montreal, Canada, WTM 2019. (Conférence).
• Scientific committee member. (2019) Women Techmakers Montreal (WTM-2019, Montreal, Canada). (Conférence).
• Scientific committee member. (2018) Google Developer Groups (GDG) Montreal, École de technologie supérieure (ÉTS), Montreal, Canada, GDG 2018. (Séminaire).
• Scientific committee member. (2018) Women Techmakers Montreal (WTM-2019, Montreal, Canada). (Conférence).
• Scientific committee member. (2017) Association for Computing Machinery (ACM) - Canadian Celebration Of Women In Computing, Université du Québec à Montréal (UQÀM), Montreal, Canada, CAN-CwiC-2017. (Conférence).
• Chair of Poster Session. (2017) Canadian Celebration of Women in Computing (CAN-CWiC-2017, Montreal, Canada). (Conférence).
• Chair of Grad Student Session. (2017) Canadian Celebration of Women in Computing (CANCWiC-2017, Montreal, Canada). (Conférence).

Activités de collaboration internationale

• Organizer. France. Bioinformatics Working Group - as part of the Sherbrooke-Montpellier 2022 meetings.

Présentations

• (2023). AI and Climate Change: Bridging the Past and Future. DevFest Monterrey 2023. Monterrey, Mexique
• (2023). A New Machine Learning Workflow to Create an Optimal Waiting List in Hospitals. 7th International Conference on Medical and Health Informatics (ICMHI 2023). Kyoto, Japon
• (2023). GPTree: generator of phylogenetic trees with overlapping and biological events for supertree inference. 15th International Conference on Bioinformatics Models, Methods and Algorithms. Lisbon, Portugal
• (2023). aPhyloGeo: Cross-platform application for the analysis of genetic and climatic phenomena. BIF7002 - Séminaire de Bioinformatique. Montréal, Canada
• (2022). Analyse d'arbres phylogénétiques en utilisant des données géographiques et climatiques. Centre de recherche en écologie de l'Université de Sherbrooke (CREUS). Sherbrooke, Canada
• (2022). Bio-géographie : avancées et reculs des approches. ÉcoWathever. Sherbrooke, Canada
• (2022). Modélisation de la relation quantitative de structure-activité (QSAR) du passage placentaire des contaminants environnementaux. Interdisciplinary Seminar on Bioinformatics (BIF7002). Canada
• (2022). Modélisation de la relation quantitative de structure d'activité (RQSA) du passage placentaire des contaminants environnementaux. BIF7002 - Séminaire de bio-informatique. Montréal, Canada
• (2022). New algorithms for inferring multiple alternative consensus trees and supertrees. Club Mathématique. Canada
• (2022). New metrics for classifying phylogenetic trees using k-means and the symmetric difference metric. International Federation of Classification Societies (IFCS) - Classification and Data Science in the Digital Age. Porto, Portugal
• (2022). New metrics for phylogenetic tree classification. Séminaire de Bioinformatique. Montpellier, France
• (2022). Nouvelles métriques pour la classification d’arbres phylogénétiques. Club mathématique. Sherbrooke, Canada
• (2022). Pour encourager et accompagner les jeunes femmes scientifiques à prendre leur place. Programme de Mentorat pour les femmes en sciences. Sherbrooke, Canada
• (2022). The benefits and dangers of artificial intelligence. Google Developer Groups Cloud Sherbrooke. Sherbrooke, Canada
• (2022). The impostor syndrome for scientists. Google Developer Groups Cloud Sherbrooke. Sherbrooke, Canada
• (2021). Analyse d'arbres phylogénétiques en utilisant des données géographiques et climatiques. Centre de recherche en écologie de l'Université de Sherbrooke (CRÉUS). Canada
• (2021). Classification des langues Indo-Européennes. Women Developers Academy, North America (WDA), virtual conference. Montreal, Canada
• (2021). Comprendre la phylogénie aux enfants. First edition of La Nuit des chercheur.euse.s. Sherbrooke, Canada
• (2021). La phylogénie expliquée aux niaiseux. La Nuit des chercheuses et des chercheurs au musée de la nature et des sciences de Sherbrooke (MNS2). Sherbrooke, Canada
• (2021). Quantitative Structure-Activity Relationship (QSAR) Modeling to Predict the Transfer of Environmental Chemicals across the Placenta. Meetings of the Montreal Bioinformatics Users Group (MonBUG), virtual conference. Montreal, Canada
• (2020). A case study evaluating the use of in vitro data on perfluorooctanoic acid (PFOA) hepatotoxicity to derive acceptable exposure levels. Society of Toxicology of Canada (STC), virtual conference. Montreal, Canada
• (2019). Algorithmes bio-informatiques pour la reconstruction d'arbres consensus et de super-arbres multiples. BIF7002 - Bioinformatics graduate seminar. Montreal, Canada
• (2019). MonBUG's 10 year anniversary. Meetings of the Montreal Bioinformatics Users Group (MonBUG). Montreal, Canada
• (2019). Quantitative structure-activity relationship (QSAR) modeling as a tool to assess lactational exposure for data-poor chemicals. Society of Toxicology of Canada (STC). Ottawa, Canada
• (2018). An intelligent shopping list based on the application of partitioning and machine learning algorithms. Python Conference (PyCon). Toronto, Canada
• (2018). Clustering multiple supertrees with k-means. Canadian Celebration of Women in Computing (CAN-CWiC). Halifax, Canada
• (2018). Inférence de super-arbres phylogénétiques multiples en utilisant l’algorithme des k-moyennes. INF8881 - Master's in Computer Science Seminar I. Montreal, Canada
• (2018). Une liste d'achats intelligente basée sur l'application des algorithmes de partitionnement et d'apprentissage automatique. Société Francophone de Classification (SFC). Paris, France
• (2017). A new clustering method for building multiple supertrees using k-means. European Conference on Data Analysis (ECDA). Wroclaw, Pologne
• (2017). A new fast method for building multiple consensus trees using k-medoids. Société Marocaine de Classification (SMC). Tangier, Maroc
• Nadia Tahiri. (2017). Artificial intelligence and journalism. Hacks/Hackers Montréal meetup. Montreal, Canada
• (2017). Avancement des connaissances bioinformatique en développant un nouvel algorithme pour l’analyse des arbres phylogéographiques. Association Canadienne-Française pour l'Avancement des Sciences (ACFAS), 85e ACFAS Congress - Le calcul informatique de pointe pour l’avancement des connaissances et l’innovation. Montreal, Canada
• (2017). Building explicit hybridization networks using the maximum likelihood and neighbor-joining approaches. European Conference on Data Analysis (ECDA). Wroclaw, Pologne
• (2017). Classification of phylogenetic trees. Advances and Thoughts at the Genome Centre (ATGC). Montreal, Canada
• (2017). Climate Change. Model United Nations Framework Convention (MUNF3C). Montreal, Canada
• (2016). Inférence de super-arbres phylogénétiques multiples en utilisant l’algorithme des k-moyennes. Symposium Biological Sciences of University of Montreal. Montreal, Canada