Dr. Hajar Homayouni’s research focuses on anomaly detection in different domains using machine learning algorithms.
She recently published a paper using machine learning to detect unusual patterns in COVID-19 patient data. Many of the COVID-19 data anomalies were from healthcare workers incorrectly entering data, but some were the result of patients having additional diseases that doctors were not already aware of.
She is also collaborating on a project to examine the effects of COVID-19 on energy consumption in residential and commercial sectors. The potential of interdisciplinary projects within the College of Sciences and across the university was one of the main reasons she decided to join San Diego State.
“Computers are ever-evolving,” Homayouni said. She loves that being a professor allows her to always be up-to-date with what’s happening in the world of computing.
This semester she is teaching a course on data science where students apply their skills to datasets of personal interest. Next semester, Dr. Homayouni hopes to continue mentoring master’s students and undergraduates interested in machine learning.
In addition to research, Dr. Homayouni enjoys hiking and is passionate about increasing the representation of women and other minorities in Computer Science through opportunities like attending the Grace Hopper and Richard Tapia conferences.