Elena Eneva

About Elena Eneva

Elena Eneva has 20+ years of experience in AI, ML, and data science across R&D, technical, and business groups- Experienced in building and mentoring interdisciplinary R&D, product development, and consulting teams across academia and industry- Proven track record in collaboration with government agencies and nonprofits- Expert in leading, developing, and delivering complex analytics strategy and novel AI solutions for healthcare, Internet of Things (IoT), disaster response, and fraud detection- Experience creating, organizing, and managing project-based interdisciplinary training programs at universities on AI for social impact. Elena is particularly passionate about solving challenging problems with a social impact, and is currently serving Research Director at Stanford’s RegLab. In the summer of 2013 Elena co-founded the Data Science for Social Good (DSSG) program at the University of Chicago, a project-based fellowship for aspiring data scientists from around the world to work on high-impact projects for nonprofits and government agencies globally. She later returned to lead the program and now serves on its board of directors. Additionally, Elena helped establish and directed the DataLab program, a similar DSSG-style fellowship for top U.S-based undergraduates, held at Sewanee, the University of the South. A longtime Bay Area resident, Elena balances her love of “sciencing with data” with volunteering for local organizations, mentoring young people in tech, social dancing, and tending to her succulents.

Experience

1. Board of Directors

   Data Science For Social Good Foundation

   Aug 2023 — Present

   We create and sustain communities, programs, and solutions that enhance the use of responsible data science and AI for equitable social good.

Education

• The University of the South

  BA, Computer Science

  1996 — 2000

• Carnegie Mellon University

  MS, Data Mining & Machine Learning

  2000 — 2002

Skills

• Databases
• Natural Language Processing
• Machine Learning
• Text Mining
• Statistics
• Predictive Modeling
• Data Analysis
• Information Retrieval
• Algorithms
• Analytics
• Fraud Detection
• Predictive Analytics
• Perl
• Agile Methodologies
• Big Data
• Data Mining
• Data Visualization
• Computer Science
• Software Engineering