Ignacio Segovia-Dominguez

Ignacio Segovia-Dominguez is an Assistant Professor in the School of Mathematical and Data Sciences at West Virginia University. Previous appointments include a visiting scientist position at NASA Jet Propulsion Laboratory (Caltech), a postdoctoral research associate role at the University of Texas at Dallas, and a postdoctoral fellowship at the Center for Research in Mathematics (CIMAT).

He received his master's and doctoral degrees in computer science from the Center for Research in Mathematics (CIMAT) in Guanajuato, Mexico. He is committed to supporting the academic and professional growth of all students in STEM, informed by his own experience as a first-generation college graduate. 

For more about Ignacio’s profile, visit www.IgnacioSD.com.

Research

His research develops mathematically grounded methods for learning from complex and structured data, spanning statistical pattern recognition, spatio-temporal graph modeling, structural signature extraction, and numerical optimization. He applies these methods across health and natural systems, security and conflict analytics, and dynamic complex network modeling, with an emerging line of work in quantum computing and quantum machine learning. His broader research agenda is to build shared methodology across fields that don’t typically borrow from one another, from public health to conflict forecasting. 

For a full list of methods and applications, visit Research Interests.

Teaching

I combine inquiry-based and problem-based learning, structuring courses around open, challenging questions that let students test their reasoning, build literature and critical-analysis skills, and practice communicating findings within a team. 

In courses such as Current Topics in Data Science and Statistical Machine Learning II, I guide students through open-ended problems, providing feedback and mentorship as they navigate uncertainty, while recognizing that students engage with material differently based on their individual backgrounds and experiences. I am also modernizing course content around the statistical foundations of machine learning and data science, and introducing quantum computing material and drone technology, to prepare students in West Virginia for research and careers in emerging fields.

For further teaching experience, visit Selected Teaching Experience.

Mentoring

Mentoring is central to how I build a research program that spans fields not typically in conversation with one another. My lab includes both undergraduate and graduate students working across machine learning, structural signature extraction, and spatio-temporal modeling, with an emerging line of work in quantum computing, applied to problems in health, natural, and security-related systems, often through co-supervision with colleagues across physics, engineering, and political science.

Drawing on my own experience as a first-generation student, I place particular emphasis on providing the structure and consistent feedback students need to grow into independent researchers. Since joining WVU, my mentees have gone on to positions including the Institute for Defense Analyses (IDA), MITRE, and ManTech, as well as PhD programs at the University of Pittsburgh and Carnegie Mellon University.

For details on current and past lab members, visit Members.

Selected Publications

A selected list of publications, drawn from ORCID, appears below. For a full record and additional updates, visit www.IgnacioSD.com[IS1]  and Google Scholar[IS2] .