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 problems for complex data
- Anomaly detection in large complex graphs
- Fraud detection (opinion spam, credit card fraud, medical fraud, etc.)
- Analysis and algorithm design for heterogeneous graphs
- Vulnerability and resilience in large dynamic graphs
- Analysis of online social media
We are thankful to following funding agencies for their support to our research.
Ongoing projects of our group include:
In the past, our research was also funded by:
- 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)
I have had the opportunity to work with the following MS/PhD students and post docs:
- Dimitris Berberidis, Post-doc (Jul 2019 - )
- Yue Zhao, PhD student (advisor, F 2019 - )
- Lingxiao Zhao, PhD student (advisor, F 2018 - )
- Shubhranshu Shekhar, PhD student (advisor, F 2017 - )
- Hung Nguyen, Post-doc (Aug 2018 - Aug 2019)
- Xuejian Wang, PhD student (advisor, F 2018 - F 2019)
- Sachin Grover, PhD student (advisor, F 2018 - F 2019)
- Jing Mao, MS student, ECE (research advisor, Summer 2019)
- Tuan Le, Post-doc (F 2017 - F 2018)
- Meghanath Macha, PhD student (advisor, F 2016 - F 2018)
- Hemank Lamba, PhD student (advisor, F 2017 - S 2018)
- Emaad Ahmed Manzoor, PhD student (advisor, F 2016 - S 2018)
- Lingxiao Zhao, MS student, ECE (research advisor, F 2017 - S 2018)
- Xuan Wu, MS student, SCS (research advisor, S 2017 - S 2018)
- Abhinav Maurya, PhD student (Summer 2017)
- Runshan Fu, PhD student (S 2017)
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
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.