Teaching
- November 14, 2019 Carnegie Mellon University: D3 Deconstructed (Guest Lecture)
- October 22, 2019 Carnegie Mellon University: Introduction to data visualization with D3.js (Guest Lecture)
- Spring 2019 Carnegie Mellon University: Interactive Art (TA)
- Spring 2018 Carnegie Mellon University: Art and Machine Learning (TA)
- Spring 2016 USF: Intro to Information and Data Visualization (Curriculum + Instructor)
- Spring 2016 Gray Area Foundation for the Arts: Creative Code Immersive (Curriculum + Instructor)
- Summer 2015 Gray Area Foundation for the Arts: Creative Code Immersive (Curriculum + Instructor)
- Spring/Summer 2015 GalvanizeU: Machine Learning and Data Analysis (Curriculum + Instructor)
- March 4, 2015 Galvanize: Real-time data driven web applications (Guest Lecture)
- Fall 2014 Zipfian Academy/Galvanize: Data Science Immersive (Curriculum + Instructor)
- Summer 2014 Zipfian Academy: Data Fellowship Program (Curriculum + Mentor)
- Spring 2014 Zipfian Academy: Data Science Immersive (Curriculum + Instructor)
- Fall 2013 Zipfian Academy: Data Science Immersive (Curriculum + Instructor)
- Spring 2013 Hack Reactor: Software Engineering Immersive (Curriculum + TA)
- Fall 2012/Spring 2013 General Assembly: Introduction to Web Development (TA)
- Summer 2012 General Assembly: Programming Fundamentals using Ruby on Rails (TA)
Speaking
- Oct 28, 2020 Open Data Science Conference (West): Communicating COVID: Visualization, Models, and Uncertainty during a Pandemic
- Sept 10, 2020 O’Reilly + Pearson: Bayesian Hyperparameter Optimization
- Sept 1, 2020 O’Reilly + Pearson: Distributed Machine Learning with Ray
- Mar 16, 2020 Pearson Live Training: Debugging Data Science (part 2): Tuning Models, Engineering Features, and Improving Performance (slides and code)
- Mar 9, 2020 Pearson Live Training: Debugging Data Science (part 1): Evaluating Machine Learning in Practice (slides and code)
- Jan 22, 2020 Pearson Live Training: Debugging Data Science (part 2): Tuning Models, Engineering Features, and Improving Performance (slides and code)
- Jan 8, 2020 Pearson Live Training: Debugging Data Science (part 1): Evaluating Machine Learning in Practice (slides and code)
- Oct 17, 2019 Pearson Live Training: Causal Inference in Data Science (slides and code)
- Sept 26, 2019 Pearson Live Training: Debugging Data Science (slides and code)
- June 26, 2019 Pearson Live Training: Debugging Data Science (slides and code)
- May 9, 2018 Human-Computer Interaction Institute: Machine Learning for HCI (slides)
- March 15, 2018 CASOS @ Carnegie Mellon University: Uncovering Factions in Parliamentary Voting with Probabilistic Latent Variable Models
- Feb 28, 2017 Carnegie Mellon University: Videoplace—an artificial reality
- May 22, 2016 Moogfest: Sonifying Data (slides and code)
- April 24, 2016 Gray Area Festival: Data Sonification with p5.js (slides and code)
- April 13, 2016 Data Science Pop-up Austin: Surfing Silver, Dynamic Bayesian Forecasting for Fun and Profit (slides)
- Nov 15, 2015 ODSC: Hands-on with D3.js: Civic Impact (video)
- Nov 10-12, 2015 IBM Datapalooza: Visualizing Petabytes of Data with Spark and D3.js
- Nov 10-12, 2015 IBM Datapalooza: Better Search at Scale, Leveraging Spark for Contextual NLP
- Nov 10-12, 2015 IBM Datapalooza: Machine Learning Ensembles on Spark
- Oct 14, 2015 Rich Data Summit: Better Search at Scale: Leveraging Spark for Contextual NLP
- Oct 7, 2015 Data Science Pop-up Seattle: Building Data Science Applications w/ Spark (in Python!)
- Sept 28, 2015 DataWeek: Interactive Data Visualization with D3.js
- Sept 22, 2015 Eventbrite Tech Talk: Better Search at Scale with Spark (video)
- July 24, 2015 PyData Seattle: Scalable Data Pipelines w/ Luigi (video)
- June 10, 2015 Data Science Pop-up Chicago (Panel): Do you need context or is data enough? (video)
- June 2, 2015 Hirepalooza (moderator): Intern to CTO
- June 1, 2015 Hirepalooza (panel): The Art of Recruiting Senior Tech Talent
- May 24, 2015 Gray Area Festival: Civic Impact through Data Visualization (slides | code)
- May 23, 2015 Gray Area Festival (panel): Civic Data
- Feb 18, 2015 Strata: Building Interactive Data Visualizations (video | slides | code)
- Nov 23, 2014 PyData NYC: On Building a Data Science Curriculum (slides)
- Oct 20, 2014 IOTAconf: Distributed Machine Learning: Architectures to Leverage Streams of Data (video)
- July 21, 2014 GraphLab: Modern Education in a Postmodern world (slides)
- May 4, 2014 PyData SV: Data Engineering 101, Building your First Data Product (slides)
- April 1, 2014 SF Data Science Meetup (moderator): Data Science for Social Good (video)
- Oct 2, 2013 DataWeek: Why I Teach (Data Science) (video)
- Sept 30, 2013 DataWeek: Intro to Data Science and Machine Learning (slides | code)
- Aug 16, 2013 SF Machine Learning Meetup: Data Science Dos and Don’ts (video)
- May 13, 2013 Ignite SF: Meta-Learning, What Quantum Theory has to Teach us about Education (video)
Advising
- 2015-present UC Berkeley Extension: Data Science Advisory Board
- 2015-2016 DataKind SF Bay Area: Data Ambassador
- 2015-2016 Gray Area Foundation for the Arts: Cultural Incubator Advisor
- 2013-2016 SF Data Science Meetup: Co-founder and Co-organizer
Research
- ML-RSA Workshop @ NeurIPS 2020: Challenging common interpretability assumptions in feature attribution explanations.
- Factions: Near Real Time Assessment of Emergent Complex Systems of Confederates
- Crowd Terms: Identifying Terms & Conditions Important to Consumers Using Crowdsourcing and Pairwise Comparisons
Software
- Liminoid: A toolkit for building local-first analytics applications on the web
Press
- Oct 29, 2015 Software Engineering Daily: Galvanize Data Science with Jonathan Dinu and Ryan Orban
- Nov 3, 2014 Venture Beat: Why LinkedIn’s data science reorg actually makes a lot of sense
- April 1, 2014 Venture Beat: Data scientists need their own GitHub. Here are four of the best options
- Aug 15, 2013 ITworld: Data visualization, Beneficial but perilous
The Museum (or graveyard...)
