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Manuchehr Aminian

Applied mathematician
Email: maminian@cpp.edu (web scrapers and bot emails welcome)
Assistant professor, Mathematics & Statistics, Cal Poly Pomona
Github
LinkedIn
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.

Upcoming: AMS Fall Western Sectional Meeting (Riverside, CA) (link)
Upcoming: SIAM Conference on Mathematics of Data Science (Atlanta, GA) (link)
SIAM Annual Meeting, July 2024 (Spokane, WA) (link)
ICMS Maths for Humanity, June 2024 (Edinburgh, Scotland)
NetSci, Quebec, Quebec, June 2024 (Quebec, Quebec) (link)
Optimal Point Distributions, ICERM June 2024 ((link))
AMS Western Sectional Meeting, May 2024 (San Francisco)
SOCAMS 2024 at UCSD, April 2024; (link)
<codes> seminar talk at Emory; April 2024
Mathematical Approaches for Connectome Analysis; IPAM; February 2024 (link)
Joint Math Meetings, January 2024 (San Francisco)
Complex Networks Winter Workshop, December 2023 (Quebec)
Datathon4Justice 2023, November 17-19, 2023 (link)
CSU Mathematical Sciences Conference, Bakersfield, CA, November 2023 (link)
NISS workshop on statistical challenges in the analysis of police use of force, Northfield, MN, November 2023 (link)
ICIAM 2023, 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

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 analysis of police activity and use of force
Network models of synchronization; polarization

Teaching

Short of giving my full teaching history, I typically teach:

Programming for computational mathematics
Linear algebra, differential equations
Numerical analysis
Mathematical modeling

I've been teaching undergraduates for about 12 years now (since graduate school). I think I stand out from my peers in how I emphasize programming and computational methods during my teaching, to test the boundaries of theorems. Maybe not so controversial, but I think it's still relatively uncommon.

I also have a small thing for integrating historical documents to enrich my teaching and students' learning.

Advice

A mentor once told me, the advice you get is worth as much as you pay for it. Nevertheless...