Ravi Janardan's research interests center around the design and analysis of efficient algorithms for representing, reasoning about, and manipulating large numbers of discrete geometric entities (e.g., points, line-segments, polygons, and polytopes) that have spatiotemporal attributes. Questions of interest concern intersection, containment, proximity, similarity, spread, shape, etc., and are motivated by applications in domains as diverse as computer-aided design and manufacture, bio-medical modeling and simulation, location-based services, and machine learning.

Research Division
Computing Foundations

Current Research
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Ph.D. Graduates
Jie Xue (2019); Rahul Saladi (2017); Yuan Li (2017); Akash Agrawal (2016); Yokesh Kumar (2012); Jieping Ye (2005); Ivaylo Ilinkin (2003); Jayanth Majhi (1998); Prosenjit Gupta (1995); Siu Wing Cheng (1992).

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Meet the Faculty - Ravi Janardan

Education

Ph.D. in Computer Science, Purdue University (1987)
M.S. in Computer Science, Purdue University (1985)
M.Tech in Computer Science, Indian Institute of Technology, Madras (1982)
B.Tech in Mechanical Engineering, Indian Institute of Technology, Madras (1980)

Professional Background

Ravi Janardan joined the Department of Computer Science & Engineering in 1987 as an assistant professor. He was promoted to full professor in 1998 and served as Associate Head of the Department from 2000-05. Janardan conducts research on the theoretical and applied aspects of geometric computing. His collaborative research on digital dentistry resulted in a University Innovations Award (2012). His excellence in teaching was recognized by an Outstanding Instructor Award (1989) and by the George W. Taylor/CSE Alumni Society Award for Distinguished Teaching (2015).

Visit Ravi Janardan's Experts@Minnesota profile page.

Teaching Subjects

• Algorithm and Data Structure Design
• Computational Geometry
• Discrete Structures

Honors and Awards

2015: George W. Taylor/CSE Alumni Society Award for Distinguished Teaching
1988: Science and Engineering Student Board - Best Professor Award

Selected Grants
II-New: Research Infrastructure for Big Spatial and Temp
Mokbel, M. F., Hecht, B. J., Janardan, R. & Shekhar, S.; National Science Foundation; 7/1/15 - 6/30/20.

Selected Publications

2022

Xue, J., Li, Y., Rahul, S., Janardan, R. (2022). New Bounds for Range Closest-Pair Problems. Discrete and Computational Geometry. 68 (1), [1-49].
DOI: 10.1007/s00454-022-00388-7

2020

Xue, J., Li, Y., Janardan, R. (2020). Approximate range closest-pair queries. Computational Geometry: Theory and Applications. [101654].
DOI: 10.1016/j.comgeo.2020.101654

Xue, J., Li, Y., Rahul, S., Janardan, R. (2020). Searching for the closest-pair in a query translate. Journal of Computational Geometry. 11 (2), [26-61].
 

Agrawal, A., Li, Y., Xue, J., Janardan, R. (2020). The most-likely skyline problem for stochastic points. Computational Geometry: Theory and Applications. [101609].
DOI: 10.1016/j.comgeo.2020.101609

2019

Xue, J., Li, Y., Janardan, R. (2019). On the expected diameter, width, and complexity of a stochastic convex hull. Computational Geometry: Theory and Applications. [16-31].
DOI: 10.1016/j.comgeo.2019.04.002

Li, Y., Eldawy, A., Xue, J., Knorozova, N., Mokbel, M.F., Janardan, R. (2019). Scalable computational geometry in MapReduce. VLDB Journal. 28 (4), [523-548].
Accepted author manuscriptDOI: 10.1007/s00778-018-0534-5

Xue, J., Li, Y., Rahul, S., Janardan, R. (2019). Searching for the closest-pair in a query translate. In Barequet, G., Wang, Y. (eds). 35th International Symposium on Computational Geometry, SoCG 2019. (Leibniz International Proceedings in Informatics, LIPIcs. 129. (1868-8969)). Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing.
DOI: 10.4230/LIPIcs.SoCG.2019.61

2018

Xue, J., Li, Y., Janardan, R. (2018). Approximate range closest-pair search. Paper presented at 30th Canadian Conference on Computational Geometry, CCCG 2018. [282-287].
 

Xue, J., Li, Y., Rahul, S., Janardan, R. (2018). New bounds for range closest-pair problems. In Toth, C.D., Speckmann, B. (eds). 34th International Symposium on Computational Geometry, SoCG 2018. (731-7314). (Leibniz International Proceedings in Informatics, LIPIcs. 99. (1868-8969)). Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing.
DOI: 10.4230/LIPIcs.SoCG.2018.73

Xue, J., Li, Y., Janardan, R. (2018). On the separability of stochastic geometric objects, with applications. Computational Geometry: Theory and Applications. [1-20].
DOI: 10.1016/j.comgeo.2018.06.001

2017

Li, Y., Xue, J., Agrawal, A., Janardan, R. (2017). On the arrangement of stochastic lines in R². Journal of Discrete Algorithms. [1-20].
DOI: 10.1016/j.jda.2017.04.003

Xue, J., Li, Y., Janardan, R. (2017). On the expected diameter, width, and complexity of a stochastic convex-hull. In Ellen, F., Kolokolova, A., Sack, J.R. (eds). Algorithms and Data Structures - 15th International Symposium, WADS 2017, Proceedings. (581-592). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 10389 LNCS. (0302-9743)). Springer Verlag.
DOI: 10.1007/978-3-319-62127-2_49

Agrawal, A., Li, Y., Xue, J., Janardan, R. (2017). The most-likely skyline problem for stochastic points. Paper presented at 29th Canadian Conference on Computational Geometry, CCCG 2017. [78-83].
 

2016

Xue, J., Li, Y., Janardan, R. (2016). On the separability of stochastic geometric objects, with applications. In Fekete, S., Lubiw, A. (eds). 32nd International Symposium on Computational Geometry, SoCG 2016. (62.1-62.16). (Leibniz International Proceedings in Informatics, LIPIcs. 51. (1868-8969)). Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing.
DOI: 10.4230/LIPIcs.SoCG.2016.62

2015

Agrawal, A., Rahul, S., Li, Y., Janardan, R. (2015). Range search on tuples of points. Journal of Discrete Algorithms. [1-12].
DOI: 10.1016/j.jda.2014.10.006

2014

Rahul, S., Janardan, R. (2014). A general technique for top-κ geometric intersection query problems. IEEE Transactions on Knowledge and Data Engineering. 26 (12), [6945935]. [2859-2871].
DOI: 10.1109/TKDE.2014.2316807

Gupta, P., Janardan, R., Kumar, Y., Smid, M. (2014). Data structures for range-aggregate extent queries. Computational Geometry: Theory and Applications. 47 (2 PART C), [329-347].
DOI: 10.1016/j.comgeo.2009.08.001

2013

Kumar, Y., Janardan, R., Larson, B.E. (2013). Automatic virtual alignment of dental arches in orthodontics. Computer-Aided Design and Applications. 10 (3), [371-398].
DOI: 10.3722/cadaps.2013.371-398

Eldawy, A., Li, Y., Mokbel, M.F., Janardan, R. (2013). CG-Hadoop: Computational geometry in MapReduce. In 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2013. (284-293). (GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems.).
DOI: 10.1145/2525314.2525349

2012

Rahul, S., Janardan, R. (2012). Algorithms for range-skyline queries. In 20th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2012. (526-529). (GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems.).
DOI: 10.1145/2424321.2424406