Leman Akoglu

Dean's Associate Professor of Information Systems

2118C Hamburg Hall


About me

I am the Heinz College Dean's (Tenured!) Associate Professor at Carnegie Mellon University's Heinz College of Information Systems and Public Policy. I also hold courtesy appointments at the Machine Learning Department (MLD) and the Computer Science Department (CSD) of School of Computer Science (SCS).

At Heinz, I direct the Data Analytics Techniques Algorithms (DATA) Lab.
My research interests are broadly in data mining, graph mining, machine learning, and knowledge discovery, with specific focus on anOmaLiEs---identifying and characterizing 'what stands out' in large-scale, time-varying, multi-modal data sources through scalable computational methods. Prospective students with similar interests, please see here.


A short bio can be found here.

Postdoc position

The post doc position in my group has now been filled and applications are closed.
We have an open postdoctoral position on spatiotemporal data modeling and anomaly detection. See details and how-to-apply at THIS LINK.


Research interests

  • Outlier Mining, Out-of-Distribution Detection
  • Fraud Detection, Event and Change Detection, Adversarial Example Detection
  • Graph Neural Networks, Expressiveness, Graph Generation
  • Graph-based/Relational Anomaly Detection
  • Self-Supervised Learning
  • Applied Machine Learning

Selected Honors and Awards

  • IJCAI 2021 Early-Career Spotlight (among 15 all over the world)
  • SDM/IBM Early Career Data Mining Research Award, April 2021
  • The Most Influential Paper Award, PAKDD 2020
  • Heinz College Dean's Professor for Feb 2019-2022
  • Best Research Paper Award, SIAM SDM 2019
  • Best Student Machine Learning Paper Runner-up Award, ECML PKDD 2018
  • NSF CAREER Award, 2015-2020
  • Best Research Paper Runner-up Award, SIAM SDM 2016
  • Best Research Paper Award, SIAM SDM 2015
  • Army Research Office Young Investigator Award, 2013
  • Best Paper Award, PAKDD 2010
  • Best Knowledge Discovery Paper Award, ECML PKDD 2009