Dr. Gongora-Svartzman is an Assistant Teaching Professor of Information Systems
At Carnegie Mellon University, Prof. Gongora-Svartzman is an Assistant Teaching Professor for Heinz College of Information Systems and Public Policy. She has taught classes such as Data Mining, Exploratory Data Analysis, and Visualization with Python, and Machine Learning Foundations with Python and has served as a faculty advisor for Information Systems Consulting Projects and Capstone Projects.
Before joining CMU, Prof. Gongora-Svartzman (Prof. GS) was an Adjunct Instructor for the Business Intelligence and Analytics Program, Business School at Stevens Institute of Technology. She was also an Adjunct Associate Faculty for the Applied Analytics Program, School of Professional Studies at Columbia University. During her time at Stevens, she was a researcher at the Visualization for Optimal Decision Making Lab (VizDec), a Research Scientist for the Systems Engineering Research Center (SERC), and a co-teacher for classes such as Data Visualization and Multi-Agent Socio-Technical Systems.
Prof. Gongora-Svartzman holds a Ph.D. in Engineering Management from the Stevens Institute of Technology, School of Systems and Enterprises. She also holds a double major as a B.Sc. in Computer Engineering and Electrical Engineering and an M.Sc. in Computer Science. Prof. Gongora-Svartzman's main research areas are 1) Urban Informatics, 2) Data Visualization for Decision Making, and 3) Resilience and Social Perception. Her research endeavors include disaster preparedness strategies through social media analysis, quality of smart city services, equity in social movements, and transportation services. Her work bridges the technical performance of services and disruptions with human perceptions and experiences.
Prof. Gongora-Svartzman is an active member of the Institute for Operations Research and the Management of Sciences (INFORMS), where she has organized sessions such as the "Diversity, Equity, and Inclusion in OR/MS/Analytics. Innovations in Research and Practice" and "Resilient Infrastructure and Community Networks," to highlight a couple. She has also served as chair of the Early Career Teachers Network (ECTN 2021 and 2022), Secretary for Women in OR/MS (2021), current VP of Communications for Women in OR/MS (2022) and has been a mentor for the Women in OR/MS Mentorship program for the past three years (2019-2021). Additionally, Prof. GS is a mentor for the Tartan Scholars Mentorship Program (CMU), a long-time Institute of Electrical and Electronics Engineers (IEEE) member, a proud Grace Hopper Scholar (2018), and a Scholar at Tapia Conference (2019). In her free time, she helps promote women in STEM, DEI in computing fields and mentors the occasional student-led data competition.
- 90-457 - Applied Data Analytics with Tableau
- 90-800 - Exploratory Data Analysis and Visualization with Python
- 90-803 - Machine Learning Foundations with Python
- 94-805 - Urban Analytics
- 94-819 - Data Analytics with Tableau
- 95-791 - Data Mining
- 95-854 - Machine Learning with Tableau