Leman Akoglu
Dean's Associate Professor of Information Systems
Bio
Leman Akoglu, PhD
Leman Akoglu is the Heinz College Dean's Associate Professor of Information Systems at Carnegie Mellon University. She holds courtesy appointments in the Computer Science Department (CSD) and Machine Learning Department (MLD) of School of Computer Science (SCS). She has also received her Ph.D. from CSD/SCS of Carnegie Mellon University in 2012.
Dr. Akoglu’s research interests broadly span machine learning and data mining, and specifically graph mining, pattern discovery and anomaly detection, with applications to fraud and event detection in diverse real-world domains. At Heinz, Dr. Akoglu directs the Data Analytics Techniques Algorithms (DATA) Lab.
Dr. Akoglu is a recipient of the SDM/IBM Early Career Data Mining Research award (2020), National Science Foundation CAREER award (2015) and US Army Research Office Young Investigator award (2013). Her early work on graph anomalies has been recognized with the The Most Influential Paper (PAKDD 2020), which was awarded the Best Paper (PAKDD 2010). Dr. Akoglu's other research awards include the Best Research Paper (SIAM SDM 2019), Best Student Machine Learning Paper Runner-up (ECML PKDD 2018), Best Paper Runner-up (SIAM SDM 2016), Best Research Paper (SIAM SDM 2015), Best Paper (ADC 2014), and Best Knowledge Discovery Paper (ECML PKDD 2009). She holds 3 U.S. patents filed by IBM T. J. Watson Research Labs. Her research has been supported by the NSF, US ARO, DARPA, Adobe, Capital One Bank, Facebook, Northrop Grumman, PNC Bank, PwC, and Snap Inc.
Leman Akoglu is the Heinz College Dean's Associate Professor of Information Systems at Carnegie Mellon University. She holds courtesy appointments in the Computer Science Department (CSD) and Machine Learning Department (MLD) of School of Computer Science (SCS). She has also received her Ph.D. from CSD/SCS of Carnegie Mellon University in 2012.
Dr. Akoglu’s research interests broadly span machine learning and data mining, and specifically graph mining, pattern discovery and anomaly detection, with applications to fraud and event detection in diverse real-world domains. At Heinz, Dr. Akoglu directs the Data Analytics Techniques Algorithms (DATA) Lab.
Dr. Akoglu is a recipient of the SDM/IBM Early Career Data Mining Research award (2020), National Science Foundation CAREER award (2015) and US Army Research Office Young Investigator award (2013). Her early work on graph anomalies has been recognized with the The Most Influential Paper (PAKDD 2020), which was awarded the Best Paper (PAKDD 2010). Dr. Akoglu's other research awards include the Best Research Paper (SIAM SDM 2019), Best Student Machine Learning Paper Runner-up (ECML PKDD 2018), Best Paper Runner-up (SIAM SDM 2016), Best Research Paper (SIAM SDM 2015), Best Paper (ADC 2014), and Best Knowledge Discovery Paper (ECML PKDD 2009). She holds 3 U.S. patents filed by IBM T. J. Watson Research Labs. Her research has been supported by the NSF, US ARO, DARPA, Adobe, Capital One Bank, Facebook, Northrop Grumman, PNC Bank, PwC, and Snap Inc.