Dr Venkata Maruti Gunturi

Dr Venkata Maruti Gunturi

Lecturer in Computer Science

Faculty and Department

  • Faculty of Science and Engineering
  • School of Computer Science

Qualifications

  • BEng (Vellore Institute of Technology)
  • MSc (Indian Institute of Technology)
  • PhD / DPhil

Summary

Dr Gunturi has over 10 years of experience in the area of Geospatial data science. He is interested in research problems which lie at the intersection of computer science and sustainability. He has experience in working with problems in the area of urban transportation and smart cities. His works are published in highly prestigious journals such as IEEE TKDE, GeoInformatica (Springer), Machine Learning (Springer) and IJGIS. His research work has been supported by both government (DST, India) and industry (Microsoft India).

Data Analysis and Visualization (Level 6)

Recent outputs

View more outputs

Journal Article

NEAT Activity Detection using Smartwatch

Dewan, A., Gunturi, V., & Naik, V. (2024). NEAT Activity Detection using Smartwatch. International Journal of Ad Hoc and Ubiquitous Computing, 45(1), 36-51. https://doi.org/10.1504/IJAHUC.2024.136141

Finding the most navigable path in road networks

Kaur, R., Goyal, V., & Gunturi, V. M. (2021). Finding the most navigable path in road networks. GeoInformatica, 25(1), 207-240. https://doi.org/10.1007/s10707-020-00428-5

Discovering non-compliant window co-occurrence patterns

Ali, R. Y., Gunturi, V. M., Kotz, A. J., Eftelioglu, E., Shekhar, S., & Northrop, W. F. (2017). Discovering non-compliant window co-occurrence patterns. GeoInformatica, 21(4), 829-866. https://doi.org/10.1007/s10707-016-0289-3

Scalable computational techniques for centrality metrics on temporally detailed social network

Gunturi, V. M., Shekhar, S., Joseph, K., & Carley, K. M. (2017). Scalable computational techniques for centrality metrics on temporally detailed social network. Machine Learning, 106(8), 1133-1169. https://doi.org/10.1007/s10994-016-5583-7

Spatiotemporal data mining: A computational perspective

Shekhar, S., Jiang, Z., Ali, R. Y., Eftelioglu, E., Tang, X., Gunturi, V. M., & Zhou, X. (2015). Spatiotemporal data mining: A computational perspective. ISPRS International Journal of Geo-Information, 4(4), 2306-2338. https://doi.org/10.3390/ijgi4042306

Research interests

Geospatial Data Science, Spatio-temporal Data Mining, Spatio-temporal Database, Urban Transportation, Sustainability, Graph Algorithms.

Postgraduate supervision

GeoSpatial Data Science, Artificial Intelligence, Urban Transporation

Top