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Mathematics and Data Research Group
Our Research
The modern world is awash with data. Our ability to store, process, interpret and analyze data arising in real-world applications relies on foundational mathematics and mathematical tools. The interaction between mathematics and data is a fruitful and active area of research. Not only does the analysis of data lead to new mathematical questions and problems, novel mathematical techniques - arising often from seemingly unconnected areas - lead to new and powerful tools in data science.
丁香园AV has an active research group in contemporary applied mathematics and data science, encompassing a wide range of expertise and specialities. Our mathematics research includes: foundations of data science, discrete mathematics, optimization, mathematical modelling, compressed sensing and sparse recovery, neural networks and deep learning. We work on applications in computational biology, epidemiology, evolution and genomics, imaging, cognitive science, and develop data science methods for computational science and engineering.
Our group has collaborations with the Departments of Statistics, Biology, Molecular Biology and Biochemistry, Linguistics, Psychology, the School of Computing Science, and with 丁香园AV鈥檚 Faculty of Health Sciences. We also collaborate with other researchers throughout the lower mainland, Canada and internationally.
The Department of Mathematics offers a selection of graduate and undergraduate courses in this area. See below for a list.
People
Faculty
Mathematical Data Science, Numerical Analysis, Approximation Theory, Computational Harmonic Analysis
Cedric Chauve
Computational Genomics and Paleogenomics
Canada 150 Research Chair in Mathematics for Evolution, Infection and Public Health
Infectious disease modelling, statistics
Operations Research
Infectious Disease Modelling and Estimation, Cognitive Science, Metric Spaces, Phylogenetics
Postdoctoral Fellows & Visitors
- Elisha Are
- Amy Langdon
PhD Graduate Students
- Niloufar Abhari
- Juan Cardenas
- Omid Gheysar Gharamaleki
- Fatih Karaoglanoglu
- Aniket Mane
- Sebastian Moraga
- Nicola Mulberry
- Baraa Orabi
- Yexuan Song
- Kurnia Susvitasari
- Alice Yue
MSc Graduate Students
- Piyush Agarwal
- Saimon Islam
Recent Research
Publications:
B. Adcock, S. Brugiapaglia and C. G. Webster
SIAM, 2022
B. Adcock and S. Brugiapaglia
arXiv 2208.09045, 2022
B. Adcock, J. M. Cardenas and N. Dexter
arXiv:2208.12190, 2022
B. Adcock and M. Neyra-Nesterenko
arXiv:2203.00804, 2022
B. Adcock, J. M. Cardenas and N. Dexter
arXiv 2202.00144, 2022
J. Barnes, M. R. Blair, R. C. Walshe and P. F. Tupper
PLOS One 17(3):e0259511, 2022
S. Brugiapaglia, M. Liu and P. Tupper
Neural Computation 34(8):1756-1789, 2022
C. Colijn, D. J. D. Earn, J. Dushoff, N. H. Ogden, M. Li, N. Knox, G. Van Domselaar, K. Franklin, Kristyn, G. Jolly and S. P. Otto
Genomic surveillance of SARS-CoV-2
Preprint, 2022
G. Ebrahimi, B. Orabi, M. Robinson, C. Chauve, R. Flannigan and F. Hach
iScience 25(7):104530, 2022
M. Hayati, L. Chindelevitch, D. Aanensen and C. Colijn
Philosophical Transactions of the Royal Society B 377(1861):20210231, 2022
F. Karaoglanoglu, C. Chauve and F. Hach
BMC Genomics 23(1):129, 2022
P. Liu, P. Biller, M. Gould and C. Colijn
Systematic Biology (in press), 2022
J. Sielemann, K. Sielemann, B. Brejov谩, T. Vina艡 and C. Chauve
bioRxiv 2022.05.24.493339, 2022.
B. Sobkowiak, K. Kamelian, J. Zlosnik, J. Tyson, A. G. da Silva, L. Hoang, N. Prystajecky and C. Colijn
medRxiv 2022.03.10.22272213, 2022
A. Yue, C. Chauve, M. Libbrecht and R. R. Brinkman
Cytometry A 101(2):177-184, 2022
P. Tupper, K. W. Leung, Y. Wang, A. Jongman and J. A. Sereno
The Journal of the Acoustical Society of America 150(6):4464-4473, 2021
Talks:
C. Colijn
Artificial Intelligence for Pandemics (AI4PAN) seminar, The University of Queensland, June 2022
B. Adcock
Alan Turing Institute workshop on Interpretability, Safety, and Security in AI, December 2021
C. Colijn
Biostatistics-Biomedical Informatics Big Data (B3D) Seminar series, Harvard University, May 2021
B. Adcock
The AAAI 2021 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physics Sciences, April 2021
B. Adcock
One World Mathematics of INformation, Data, and Signals (OW-MINDS) Seminar, June 2020
C. Colijn
Phyloseminar.org seminar, January 2020
P. Tupper
Distributed Data for Dynamics and Manifolds, BIRS Oaxaca, September, 2017
T. Stephen
Fields Institute Industrial Optimization Seminar, December 2016
Recent Theses
Y. Song
Account for sampling bias in ancestral state reconstruction
MSc thesis, 2022
E. Haghshenas
PhD thesis, 2020
M. King-Roskamp
MSc thesis, 2020
Recent Courses
Fall 2022:
APMA 920 鈥� Numerical Linear Algebra
MATH 895 - Infectious Disease Modelling in Populations and Within Hosts
Spring 2022:
MATH 775 - Mathematical Topics in Data Science
Fall 2021:
APMA 923 - Numerical Methods in Continuous Optimization
MATH 709 - Numerical Linear Algebra and Optimization
Summer 2021:
APMA 940 - Mathematics of Data Science
Fall 2020:
APMA 920 鈥� Numerical Linear Algebra
Fall 2019:
APMA 923 - Numerical Methods in Continuous Optimization
MATH 709 - Numerical Linear Algebra and Optimization
Recent visitors
- Melanie Chitwood (Yale) - Fall 2022
- Tomas Vinar (Comenius University) - Spring/Summer 2022
- Brona Brejova (Comenius University) - Spring/Summer 2022