# Hannah Aizenman haizenman@ccny.cuny.edu github/twitter/most socials: @story645 linked in: https://www.linkedin.com/in/hannah-aizenman/ ## Education PhD Candidate, Computer Science, GC CUNY, 10/2010-present B.E. Computer Engineering, CCNY, 2005-2010 ## Research ### GC CUNY/CCNY, 10/2007-present #### Current: Topological Equivariant Artist Model mathematical formalism of visualization to drive a rearchitecture of Matplotlib to better support complex structured, often labeled, data. (Funded by CZI EOSS 1 and 3) #### Previous: Climate related projects Worked on projects including NYC 311 as proxy for infrastructure failures, MODIS snow product evaluation, River delta risk factor analysis, Long term probabilistic forecast evaluation: ## Teaching ### Adjunct Lecturer, CCNY, 10/2020-06/2019 #### PSYCH 31170: Tech skills for psychology students: https://github.com/ccnypsych/psy31170 Project based introduction to Python, simple web apps, and data science, course is managed via a Jupyter hub environment #### CSC212 - Data Structures in C/C++: https://github.com/ccnycs/csc212 Using inline C++ to illustrate use of data structure, and build homeworks using googletest, and continuous integration #### CREST-HIRES summer high school REU https://github.com/story645/EAS213 workshops on analysing spatiotemporal geographic and climate data #### CS102 (Intro to Prog. for Non-Majors in C/C++): https://github.com/story645/cs102 Developed curriculum for incorporating peer based learning (PLTL) into CS102 #### CS100: Introductory survey course on topics in Computer Science (Python) final project was an interregation of current events using technical lense #### FIQWS/ENGR101: 5 week freshman seminar on simple data analysis (Python) colloboratively developed the instructional material and syllabi for these courses ### Digital Fellow, GC CUNY, 10/2015-07/2018 #### Teaching Created and taught workshops on visualization, data analysis, and machine learning to a primarily academic humanities and social science audience. Participated in planning and curriculum development for Digital Humanities Research Institute (http://dhinstitutes.org/). #### Service Supported humanities students building digital projects. Co-organized in house Python Users Group, office hours, and one on one consultations. Co-organized Installathon with Learn Python NYC, organized NYC branch of the doc-a-thon (https://bids.github.io/docathon/), and Visualization Seminar ## Volunteering ### Matplotlib maintainer, 10/2016-present community manager, core developer, social media manager, mentor for funded special projects such as Google Summer of Code (GSoc), Gooogle Season of Docs (GSoD), John Hunter Fellowship, and cheatsheet small development grant. Implemented support for categorical data as a GSoC student. Matplotlib is an open source Python visualization library ### Planning committee, Annual Python Symposium, American Meteorological Society, 01/2014-present Advocated for a session on tutorials and a session on tools - the latter became a panel and both are some of the most popular sessions of the tutorial. Have also given tutorials on pandas, geopandas, and using Jupyter notebooks in teaching (https://github.com/story645/ams_tutorials). ## Selected Publications ### An Introduction to Python Programming for Scientists and Engineers, Cambridge University Press, 2020 Johnny Wei-Bing Lin, University of Washington, Bothell, Hannah Aizenman, City College, City University of New York, Erin Manette Cartas Espinel, Envestnet Tamarac, Washington, Kim Gunnerson, University of Washington, Bothell, Joanne Liu, Biota Technology Inc., California ### ## Selected Talks ### Update on re-desiging Matplotlib’s data model, Scipy 2021 Coauthored with Thomas Caswell and Michael Grossberg Update on the research progress, including understanding of the problem space. ### Redesiging Matplotlib's Data Model, Scipy 2020 Coauthored with Thomas Caswell and Michael Grossberg Discuss problems with current architecture and present practical implications of mathematical model of visualization to an audience of mostly scienctists and programmers.