Position Type
- Present

Ashwin Lall joined the Denison faculty in 2010. Prior to this, he was a postdoctoral researcher at Georgia Tech, a Ph.D. student and Sproull fellow at the University of Rochester, and a math/computer science double major at Colgate University. Dr. Lall has taught several introductory courses, such as CS110, CS109, FYS102, as well as advanced topics such as Theory of Computation and Design/Analysis of Algorithms. Dr. Lall created a Game Design elective for the CS major in 2012. In 2013, he designed a new version of the introductory computer science course with an emphasis on applications in the social sciences. Dr. Lall was named a Bayley-Bowen faculty fellow in 2013.

B.A., Colgate University; M.S., Ph.D., University of Rochester


My research spans many different areas in computer science related to large data sets. Projects we could work on would involve answering questions about large network traffic, commercial product, or social network data sets.

My research focuses on the design and analysis of algorithms for very large data sets. Much of my work has to do with applications in computer networks, though I have also done work in the areas of databases, social networks, distributed computing, and natural language processing (AI). I am interested in doing summer research with students on analysis of networking data, query optimization, or social networks. Interested students should drop by my office to discuss possible projects.



Selected publications:

  • Towards Optimal Error-Estimating Codes through the Lens of Fisher Information Analysis, Nan Hua, Ashwin Lall, Baochun Li, and Jun Xu. In Proceedings of SIGMETRICS, London, UK, 2012.
  • Dense Subgraphs on Dynamic Networks, Atish Das Sarma, Ashwin Lall, Danupon Nanongkai, Amitabh Trehan. In Proceedings of DISC, Salvador, Brazil, 2012.
  • Regret-Minimizing Representative Databases, Danupon Nanongkai, Atish Das Sarma, Ashwin Lall, Richard J. Lipton, and Jim Xu. In Proceedings of the 36th International Conference on Very Large Databases, Singapore, 2010.
  • Streaming Pointwise Mutual Information, Benjamin Van Durme and Ashwin Lall. In Proceedings of the Neural Information Processing Systems Conference, Vancouver, Canada, 2009.
  • Data Streaming Algorithms for Estimating Entropy of Network Traffic, Ashwin Lall, Vyas Sekar, Mitsunori Ogihara, Jun Xu, and Hui Zhang. In Proceedings of ACM SIGMETRICS 2006/IFIP Performance, Saint Malo, France, 2006.


Student Collaborations

Selected student research projects:

  • Yuting Chen, Edward Takahashi. Sketch-guided sampling for measuring network traffic statistics. In proceedings of MCURCSM 2012.
  • Edward Takahashi, Yuting Chen. Divergence in network traffic. In proceedings of MCURCSM 2012.