# It's a website!

## Manuchehr Aminian

- Applied mathematician
- Email: maminian@cpp.edu (web scrapers and bot emails welcome)
- Assistant professor, Mathematics & Statistics, Cal Poly Pomona
- Github
- ORCiD
- Google Scholar
- Previously...
- Postdoc: Colorado State University, with Michael Kirby
- PhD: UNC Chapel Hill, 2016; with Rich McLaughlin and Roberto Camassa
- BS: University of Colorado Denver, 2010. Cool mentors: Andrei Knyazev, Julien Langou, Lynn Schreyer, Mike Kawai

## Recent and upcoming events

Just in case you want to find me, say hello, have coffee, etc. (or regret that you missed me)-
**Upcoming:**Joint Math Meetings, January 2024 (San Francisco) -
**Upcoming:**ICIAM 2023 in August 2023 - Data Science and Social Justice extended workshop June-July 2023 at ICERM link
- Graduate Student Math Modeling Camp (as a mentor), and subsequent Math Problems in Industry, June 2023
- Southern California Applied Math Symposium, May 2023, at UC Irvine (linky)
- Invited talk at Joint Math Meetings 2023 re: topological data analysis and mice time series link
- Accepted talk at CSU Mathematical Conference 2022 re: passive tracers link
- Organized minisymposium re: integrating data in infectious disease modeling at SIAM MDS 2022 link

## Research and other activities

- Asymptotic analysis and numerical simulation with passive tracer problems (partial differential equations)
- Analysis of *omics data associated with host dynamics of infectious disease (L1 regularization; bioinformatic data wrangling)
- Analysis of time series data for within-host dynamics of infectious disease (anomaly detection; health scoring; clustering; multimodal data analysis)
- Algorithm development for applied topological data analysis (mostly interested in generators right now)
- Mathematical modeling, spectral/network methods, machine learning; data visualization
- Tool development associated with small town police accountability (QSIDE's SToPA lab)

## Teaching

Short of giving my full teaching history, I generally teach:- Programming for computational mathematics
- Linear algebra, differential equations
- Numerical analysis
- Mathematical modeling

I also have a small thing for integrating historical documents to enrich my teaching and students' learning.