Leman Akoglu

Leman Akoglu is the Heinz College Dean's Tenured Associate Professor at Carnegie Mellon University's Heinz College of Information Systems and Public Policy. She holds courtesy appointments in the Machine Learning Department (MLD) and the Computer Science Department (CSD) within the School of Computer Science (SCS). Her research focuses on anomaly detection, graph mining, machine learning, and data mining, particularly in identifying anomalies in large, dynamic datasets. She is currently on academic leave as a full-time Amazon Scholar until Spring 2026.

Education: Ph.D. in Computer Science from Carnegie Mellon University (2012), B.S. in Computer Science from Bilkent University (2003-2007).

Research Interests: Data Mining, Graph Mining, Machine Learning, Anomaly Detection, Self-Supervised Learning, Outlier Detection, Fraud Detection, and Healthcare Analytics. She leads the DATA Lab at Heinz College, exploring scalable computational methods for anomaly detection across domains like healthcare, finance, and cybersecurity.

Recent Work Highlights: Contributions include trajectory anomaly detection, self-supervised time series analysis, and fair outlier detection. Her work appears in top conferences like KDD, SIAM SDM, AAAI, and NeurIPS. She has received prestigious awards such as the SDM/IBM Early Career Award and NSF CAREER Award.

Teaching: Courses include Machine Learning for Problem Solving and Big Data and Large Scale Computing at CMU. She emphasizes practical machine learning processes, feature design, and scalable methods.