B. Tech, Indian Institute of Technology, Kanpur, India, 1993PhD, Indian Institute of Science, Bangalore, India, 1999
Research interests include: Randomized Algorithms, Combinatorial Optimization, Distributed Computing, Network Science, Machine Learning, AI
Anil Vullikanti is a Professor in the Dept of Computer Science and the Biocomplexity Institute. His research interests are broadly in the areas of randomized algorithms, combinatorial optimization, distributed computing, dynamical systems and network science, machine learning, and AI, and their applications to epidemiology, public health and modeling, analysis and protection of critical infrastructures.
He was a postdoctoral associate at the Max Plank Institute for Computer Science, and then at the Los Alamos National Lab. From 2003-2005, he was a technical staff member at the Los Alamos National Lab. From 2005-2018, he was at Virginia Tech. His papers have been nominated for best paper awards at Supercomputing 2016 and AAAI 2013.
College of Engineering Faculty Fellow Award, Virginia Tech2017
Excellence in Research Award, Biocomplexity Institute of Virginia Tech2017
DOE Early Career Award 2010
NSF CAREER Award2009
"Modeling disease outbreaks in realistic urban social networks," Nature, 429, pp. 180-184 (2004). Stephen Eubank, Hasan Guclu, V.S. Anil Kumar, Madhav Marathe, Aravind Srinivasan, Zoltan Toroczkai and Nan Wang.
"Algorithmic Aspects of Capacity in Wireless Networks," Proc. ACM SIGMETRICS, pp. 133-144, 33(1), 2005 V.S. Anil Kumar, M. V. Marathe, S. Parthasarathy and A. Srinivasan.
"An Efficient and Scalable Algorithmic Method for Generating Large-Scale Random Graphs," Proc. of the International Conference for High Performance Computing, Networking, Storage and Analysis (S Maksudul Alam, Maleq Khan, Anil Vullikanti and Madhav Marathe.
"A unified approach to scheduling on Unrelated Parallel Machines," Journal of the Association of Computing Machinery (JACM), 56(5), article 28, 2009 V.S. Anil Kumar, Madhav V. Marathe, Srinivasan Parthasarathy and Aravind Srinivasan.
"Near-Optimal and Practical Algorithms for Graph Scan Statistics," Proc. SIAM Data Mining (SDM), pp. 624–632, 2017. doi: 10.1137/1.9781611974973.70 Jose Cadena, Feng Chen and Anil Vullikanti.