Leman Akoglu

Dean's Associate Professor of Information Systems

Data Analytics Techniques Algorithms (DATA) Lab

Our group is interested in
  • understanding, modeling, and leveraging data,
  • that is large-scale, streaming, multi-modal, and/or noisy,
  • toward solving real-world problems,
  • through effective and scalable computational methods,
  • with implications on policy and decision making.
We specifically focus on identifying trends and patterns and in turn rare, anomalous, fraudulent, and/or emerging events.

Our current projects include:
  • Formalizing anomaly mining problems for complex data
  • Anomaly detection in large multi-modal and relational data
  • Fraud detection (medical fraud, ad fraud, intrusion, opinion spam, credit card fraud, etc.)
  • Understanding and designing neural network models
  • Analysis and algorithm design for complex graphs
  • Vulnerability and resilience in large time-varying graphs


We are thankful to following funding agencies for their support to our research.

Ongoing projects of our group include:
  • NSF: Toward Fairer Outlier Detection
  • IARPA: Hidden ActivitY Signal and Trajectory Anomaly Characterization (HAYSTAC)
  • PwC (Risk and Regulatory Services Innovation Center)

In the past, our research was also funded by:
  • NSF CAREER 1452425 [Read abstract]
  • Adobe (University Marketing Research Grant)
  • NSF IIS 1408287 [Read abstract]
  • ONR SBIR grant (Contract No. N00014-14-P-1155)
  • Stony Brook University Office of Vice President for Research
  • Northrop Grumman Aerospace Systems (NGAS)
  • Facebook (faculty gift)
  • ARO Young Investigator Program (Contract No. W911NF-14-1-0029)
  • PNC (Financial Services Innovation Center)
  • DARPA TC Project (Contract No. FA8650-15-C-7561)


Student collaborators

I have had the opportunity to work with the following MS/PhD students and post docs:

at CMU: at Stony Brook:
  • Shebuti Rayana,  PhD student (Thesis advisor, 2013 - 2017)
  • Emaad Ahmed Manzoor,  PhD student (advisor, 2015 - 2016)
  • Aria Rezaei,  PhD student (advisor, 2015 - 2016)
  • Junting Ye,  PhD student (advisor, 2014 - 2016)
  • Hau Chan,  PhD student (co advisor, 2010 - 2015)
  • Bryan Perozzi,  PhD student (2011 - 2016)
  • Mirza Basim Baig,  PhD student (advisor, 2014 - 2015 )
  • Shuchu Han,  PhD student (2013 - 2014)
  • Santhosh K. M. Lakshminarayanan,  MSc advanced project (2015 - 2016)
  • Abhinav Mishra,  MSc advanced project (2015 - 2016)
  • Heeyoung Kwon,  MSc Thesis (2014 - 2015)
  • Vasudev Bhat,  MSc student (2013 - 2014)
  • Jagat Sastry Pudipeddi,  MS student (2012 - 2013)
  • Vivek Kulkarni,  MSc student (2012 - 2013)
  • Tiantian Gao,  MSc student (2012 - 2013)
  • Junhee Park,  BSc student (2012 - 2013)
See our group page for more information.
You can also subscribe to our email list for our reading seminar meetings here.

Prospective students

I am looking for PhD students!    Criteria: (self-) motivated, hardworking, curious, background in stats/computer science/math.
Those interested in joining DATA Lab and/or working with my research group:

  • If you are not yet at CMU:

    • Apply (by early January) to Heinz College's Ph.D. program in Information Systems and Management (ISM) here.
    • Information about Ph.D. in ISM can be found here.
    • You can earn a joint Ph.D. degree in Machine Learning and Public Policy after being admitted to the Heinz College as a Ph.D. student, by completing a short list of additional requirements. You can find details here (scroll down to PhD in Machine Learning and Public Policy), as well as here.
  • If you are at CMU: please directly email me with your CV and a brief statement about your research interests.

Note: I do NOT hire MS students unless they have taken some subset of the following courses at CMU and shown excellence (A, A+): Machine Learning (10601, 10701), Data Mining (36462), Probability and Mathematical Statistics (36700), Convex Optimization (10725), NLP (11611), etc.