Office Hours

Below is the current schedule for DSI office hours. While drop-ins are encouraged, hours are subject to change and thus we recommend you contact us in advance when possible. Including a very brief description of your problem/questions in your email is helpful.

SPRING 2018

Director's Office Hours (DSI Conference Room, Shields 362)

Thursdays 12-1pm

  • Dr. Duncan Temple Lang: DSI Director and Statistics Professor. Duncan provides expertise in advanced topics in data science.

Tuesdays & Thursdays 11-noon

  • Dr. Carl Stahmer*: DSI Associate Director for the Humanities and Director of Digital Scholarship at the UC Davis Library. Carl provides expertise on natural language processing (NLP) and other methods of text mining and language processing.

Affiliate & Postdoc Office Hours (DSI Classroom, Shields 360)

DSI affiliates are available for drop-in office hours in the DSI Classroom to help with your data science problems. Drop ins are welcome, but it is recommended that you email the individual you want to meet with in advance in case of any schedule changes.

Mondays 1-3pm

  • Dr. Dan Hicks: R, RStudio, visualization, philosophy Dan's postdoc at the DSI focuses on data-driven academic institutional effectiveness. He received his PhD in philosophy from Notre Dame and MS in Mathematics from the University of Illinois, Chicago. Prior to coming to the DSI he was a AAAS Science & Technology Policy Fellow at the EPA and NSF, and a postdoc at the University of Western Ontario. During office hours, Dan can provide feedback on: bibliometrics (including the Scopus web interface and API); beginner through intermediate skills in R (ggplot, igraph, dplyr, etc.); and philosophical issues in statistics and Data Science.

Tuesdays 10-11am

  • Ryan Philips: SQL, R, Git Ryan is a PhD student in neuroscience and can help you get started with and use SQL. When it comes to large (1M+ rows) datasets, the SQL family of languages is the industry standard for data manipulation and subsetting, but it can also be used for smaller-scale data analysis. Ryan can also assist with introductory to intermediate questions in Python, Git, command line, and R. He can also talk about his experience working at a startup in San Francisco.

Tuesdays 11am-1pm

*Hugo Mailhot: NLP, text mining, Python, Jupyter Hugo is a PhD student on Computer Science specialized in natural language processing. He's happy to discuss any NLP topic. He can also help with Python programming, interactive data analysis and development with Jupyter, and command line tools such as Git, Vim, Tmux, SSH, bash, and zsh.

Wednesdays 11am-noon

*Nick Bowden: Nick is a PhD student in the Energy Graduate Group focusing on electric power system operations and economics. He works with R and Python to run cross-section, time series and panel data analysis with a focus on causal inference. He is using XML and web technologies like RCurl to pull information from html and pdf documents.

Thursdays 5-6pm

*Jared Joseph: R, RStudio, Networks, Natural Language Processing Jared is a Ph.D. student in sociology who studies crime, networks and political corruption. He is proficient in R (though has little experience with the tidyverse), and uses it for his own work on networks. He is familiar with the tools surrounding computational social sciences, including openRefine, Unix, git, parallel processing in R, APIs, and basic web scraping.

Fridays 8:30-9:30am

  • Andrew Bradshaw: Python, notebooks Andrew is a postdoc in Physics working on fitting physical models to measurements made in the lab and on the sky. He has experience in exploratory data analysis on large catalogs. He uses python and Linux almost exclusively, but has familiarity with other languages and environments. He can help you get set up with python notebooks, from reading in data and writing/debugging code to making scientific figures.

Fridays 2-3pm

Fridays 2-3pm *Nistara Randhawa: R, GIS, git, visualization Nistara is a PhD candidate in Epidemiology and can provide help with R, including installing and setting up R/RStudio and troubleshooting code, writing R functions to improve code efficiency, and making basic R packages. She can also introduce you to using git/github, getting started with ArcMap/QGIS and using R for creating interactive maps.