Note:My publications are indexed under two names "Venkata M. V. Gunturi" and "Viswanath Gunturi" in DBLP. Below is the complete list.
Check my Google Scholar account for information on citations and h-index.

** Papers were the lead authors were either my students or were closey mentored by me.

Monograph
  • Gunturi, V., Shekhar, S.: Spatio-Temporal Graph Data Analytics. ISBN: 978-3-319-67770-5, Springer (2017) Springer link
Journal
  • Ali, R., Gunturi, V., and et. al.: Discovering Non-compliant Window Co-occurrence Patterns: GeoInformatica, Springer 2017.
  • Gunturi, V. and et al.: Scalable Computational Techniques for Temporally Detailed Social Network. Machine Learning Journal special issue on Dynamic Networks and Knowledge Discovery, Springer, 2016.
  • Gunturi, V. and et. al.: A critical-time-point approach to all-start-time lagrangian shortest paths. IEEE transactions on Knowledge and Data Engineering (2015) IEEE Xplore link
  • Spatiotemporal Data Mining: A Computational Perspective, Internation Journal of Geo-Information 4(4): 2306 -- 2338 (2015)
  • Yang, KS., Evans, M., Gunturi, V. and et. al.: Lagrangian Approaches to Storage of Spatio-Temporal Network Datasets. IEEE Transactions on Knowledge and Data Engineering 26(9): 2222-2236 (2014)
  • Shekhar, S., Yang, KS., Gunturi, V. and et. al.: Experiences with evacuation route planning algorithms. International Journal of Geographical Information Science 26(12): 2253-2265, Taylor and Francis (2012)
Conferences
  • ** Kaur, R., Goyal, V., Gunturi, V.: Finding The Most Navigable Path in Road Networks: A Summary of Results. Accepted in 29th Intl. Conference on Database and Expert Systems Applications, DEXA 2018
  • ** Mehta, A., Malik, K., Gunturi, V. and et. al: Load Balancing in Network Voronoi Diagrams under Overload Penalties. Accepted in 29th Intl. Conference on Database and Expert Systems Applications, DEXA 2018
  • ** Mongia, A., Gunturi, V. and Naik, V: Detecting Activities at Metro Stations Using Smartphone Sensors. 10th International Conference on COMmunication Systems and NETworkS, 2018.
  • ** Vij, M., Gunturi, V. and Naik, V: Use of ECDF-based Features and Ensemble of Classifiers to Accurately Detect Mobility Activities of People using Accelerometers. 9th International Conference on COMmunication Systems and NETworkS, 2017.
  • ** Ali, R. Gunturi, V., and et. al.: Future Connected Vehicles: Challenges and Opportunities for Spatio-temporal Computing (Vision Paper). In proceedings of the 23rd ACM SIGSPATIAL, International Conference on Advances in Geographic Information Systems, ACM 2015.
  • ** Ali, R., Gunturi, V., and et. al.: Discovering Non-compliant Window Co-occurrence Patterns: A Summary of Results. In proceedings of the 14th Intl. Symposium on Spatial and Temporal Databases (SSTD 2015), Springer.
  • Ramnath, S and Jiang, Z and Wu, H and Gunturi, V.: A Spatio-temporally Opportunistic Approach to Best-start-time Lagrangian Shortest Paths. In proceedings of the 14th Intl. Symposium on Spatial and Temporal Databases (SSTD 2015), Springer.
  • Gunturi, V. , Shekhar, S.: Lagrangian Xgraphs: A Logical Data-Model for Spatio-Temporal Network Data: A Summary. In Advances in Conceptual Modeling. LNCS vol. 8823, pp.201—211. Springer 2014.
  • Yang, KS., Gunturi, V., Shekhar, S.: A Dartboard Network Cut Based Approach to Evacuation Route Planning: A Summary of Results. In proceedings of 7th International Conference on Geographic Information Science, LNCS, vol. 7478, pp. 325-339, Springer, Heidelberg (2012).
  • Gunturi, V. and et. al.: A critical-time-point approach to all-start-time lagrangian shortest paths: A summary of results. In proceedings of the 12th Intl. Symp. on Spatial and Temporal Databases (SSTD 2011), LNCS, vol. 6849, pp. 74–91. Springer, Heidelberg (2011).
  • Gunturi, V., Shekhar, S., Bhattacharya, A.: Minimum spanning tree on spatio-temporal networks. In proceedings of the 21st Intl. Conf. on Database and Expert Systems Applications (DEXA 2010). LNCS, vol. 6262, pp. 149–158. Springer, Heidelberg (2010)
Peer reviewed workshops and book chapters
  • ** Agarwal, P., Verma, R., Gunturi, V.: Discovering Spatial Regions of High Correlation. 11th Intl. Workshop on Spatial and Spatiotemporal Data Mining (SSTDM-16), ICDM workshops 2016.
  • Gunturi, V. and et al.: Big Spatio-temporal Network Data Analytics for Smart Cities: Research Needs. Springer book on Seeing Cities Through Big Data (Springer 2016), Springer Link
  • Brugere, I., Gunturi, V. , Shekhar, S.: Modeling and analysis of spatio-temporal social networks. Encyclopedia of Social Network Analysis and Mining, Springer (ISBN 978-1-4614-6169-2), 2014
  • Evans, M., Yang, KS., Gunturi, V. and et. al.: Spatio-Temporal Networks: Modeling, Storing, and Querying Temporally-Detailed Roadmaps. In Space-Time Integration in Geography and GIScience: Research Frontiers in the US and China (Ed. M. Kwan, D. Richardson, D. Wang and C. Zhou), Springer (2014)
  • Shekhar, S., Gunturi, V., Evans, M. Yang, KS.: Spatial big-data challenges intersecting mobility and cloud computing. In Proc. of the 11th ACM Intl. Workshop on Data Engineering for Wireless and Mobile Access (MobiDE '12) held in conjunction with ACM SIGMOD/PODS 2012, pp. 1—6. ACM New York (2012)
  • Shekhar, S., Evans, M., Gunturi, V. and et. al.: Benchmarking Spatial Big Data. In proceedings of the first workshop on Specifying Big Data Benchmarks, WBDB 2012, LNCS, vol. 8163, pp. 81-93, Springer, Heidelberg.
Invited Articles
  • * Ali, R., Gunturi, V., Shekhar, S.: Spatial big data for eco-routing services: computational challenges and accomplishments. SIGSPATIAL Special 6(2): 19-25 (2014)