Executive Committee
Leadership
Code Lead
Dr. Brian Spiering
Brian is passionate about teaching programming (primarily Python), Deep Learning, and Natural Language Processing (NLP). He is currently a computer science professor at the University of San Francisco. He was previously a Data Science Instructor at Galvanize. Brian is active in the San Francisco tech community through volunteering and mentoring.
Dr. Brian Spiering
Brian is passionate about teaching programming (primarily Python), Deep Learning, and Natural Language Processing (NLP). He is currently a computer science professor at the University of San Francisco. He was previously a Data Science Instructor at Galvanize. Brian is active in the San Francisco tech community through volunteering and mentoring.
Advisors

Jonathan Wang
Jonathan graduated from UC Berkeley in 2014 and started his career in economic consulting. He now works at Uber in Data Science on the Public Policy team. Through his experiences working as a pro-bono management consultant through The Berkeley Group, he developed a passion for collaborating with social sector organizations to affect greater change. This inspired the founding of Delta Analytics which bridged Jonathan's interests in data and social impact. Outside of his work with Delta Analytics, he enjoys reading, music, and fences foil.

Cecilia Cheng
Cecilia co-founded and continues to advise on the operational aspects of Delta Analytics. She has a background in economic consulting and in law. In her spare time, she travels, sings, and passively takes credit for cooking from a mix. Cecilia is a graduate of UC Berkeley and Yale Law School.

Sara Hooker
Sara has previously worked as a research scientist at Google Brain. Her research is focused on training deep neural networks that fulfill multiple criteria -- interpretable, robust, compact. She spent her childhood in Africa, growing up in South Africa, Swaziland, Mozambique, and Lesotho. In 2014, she founded Delta Analytics, a non-profit dedicated to bringing technical capacity to help non-profits across the world use machine for good.