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Assistant Professor & Warden (Men’s Hostel)

uttam@iiitb.ac.in

Education : Ph.D. (IISc Bangalore)

Dr. Uttam Kumar is an Assistant Professor at IIIT Bangalore. He is a Senior Member IEEE (Institute of Electrical and Electronics Engineers, NY, USA) and Senior Member ACM (Association for Computing Machinery, NY, USA), and is the Former Infosys Foundation Career Development Chair Professor. He is the Convenor of Spatial Computing Laboratory at IIIT Bangalore.

Dr. Uttam holds a Bachelor’s Degree in Computer Science from Visvesvaraya Technological University Belgaum, Diploma in Advanced Computing from CDAC Pune, Master’s Degree in Geoinformation Science from University of Twente, The Netherlands and Ph.D. in Algorithms for Geospatial Data Analysis from Indian Institute of Science (IISc), Bangalore. He earned professional certifications in Data Science (Computational Data Analytics) and Machine Learning from Massachusetts Institute of Technology (MIT); in Big Data from Stanford University; in Spatial Computing from University of Minnesota; and in Geospatial Intelligence & Revolution from Pennsylvania State University, USA.

He worked as a Project Assistant and as a Research Associate at IISc, Bangalore, and was a Visiting Scientist at GISE Lab, Department of Computer Science & Engineering, IIT Bombay. He moved to NASA (National Aeronautics and Space Administration) Ames Research Center, Moffett Field, Mountain View, California, USA as a NASA Postdoctoral Fellow and subsequently served as a Visiting Scientist at NASA Ames/USRA for almost 4 years.

He has published 34 research papers in national/international journals, 20 book chapters, 91 papers in conference proceedings and 8 technical reports. He has delivered 102 invited guest lectures by different institutions and organizations in India and abroad. He is the reviewer of 29 national and international scientific journals, reviewer for several conferences, and has served as session chair and judge in several conferences and competitions. He is a member of AGU, IEI (India), OSGeo, ISRS, ACS and IAENG.

He has received several awards including Indian National Geospatial Award 2021; Sahyadri Shikshaka Award 2020, CES, IISc Bangalore; The Institute of Engineers India (IEI) Young Engineers Award 2016; NASA Group Achievement Award by NASA, Washington, D.C.; Publons Peer Review Awards 2017; Certified Sentinel of Science Award 2016 in the Earth and Planetary Sciences; Best Paper Award 2023 in Annual Conference on Infrastructure and Built Environment: Towards Sustainable and Resilient Societies, IIT Kharagpur; Best Paper Award 2022 in Applications of ML and Data Science in Inter-disciplinary areas, IIM Visakhapatnam; Best Paper Award 2015 in International Conference on Machine Learning and Data Analysis, UC Berkley; Best Paper Award 2015 in International Conference on Remote Sensing and Applications, Los Angeles; Best Paper Award 2014 by Boletín Geológico y Minero, Spain; Young GeoSpatial Scientist Award 2011, New Delhi; Best Paper Award 2011 by Indian Society of Remote Sensing, Bhopal; and Best Paper Award 2011 by IIT Kharagpur, India.

                                

Please visit our Spatial Computing Laboratory  Web page at IIIT Bangalore for more details.

Data science / Data mining, Applied machine learning, Remote sensing and GIS, Digital image processing, Spatial computing, Database systems, Large scale geospatial data analysis and Free and open source software

Journal

  • Uttam Kumar; Ganguly, S.; Nemani, R.R.; Raja, K.S.; Milesi, C.; Sinha, R.; Michaelis, A.; Votava, P.; Hashimoto, H.; Li, S.; Wang, W.; Kalia, S.; Gayaka, S., (2017), Exploring Subpixel Learning Algorithms for Estimating Global Land Cover Fractions from Satellite Data Using High Performance Computing. Remote Sensing, vol. 9, no. 11, pp. 1105.
  • Uttam Kumar, Anindita Dasgupta, Mukhopadhyay, C., and Ramachandra T. V., (2017), Examining the Effect of Ancillary and Derived Geographical Data on Improvement of Per-Pixel Classification Accuracy of Different Landscapes. Journal of the Indian Society of Remote Sensing, vol. 46, no. 3. pp. 407-422.
  • Saikat Basu et al., (2015), A Semi-automated Probabilistic Framework for Tree Cover Delineation from 1-m NAIP Imagery Using a High Performance Computing Architecture. IEEE Transaction on Geoscience and Remote Sensing, vol. 53, no. 10, pp. 5690-5708.
  • Uttam Kumar, Mukhopadhyay, C., and Ramachandra T. V., (2014), Cellular Automata Calibration Model to Capture Urban Growth. Boletín Geológico y Minero, vol. 125, no. 3, pp. 285-299.
  • Uttam Kumar, Kumar Raja S., Mukhopadhyay, C., and Ramachandra T. V., (2013), Assimilation of Endmember Variability in Spectral Mixture Analysis for Urban Land Cover Extraction. Advances in Space Research, vol. 52, no. 11, pp. 2015-2033.
  • Uttam Kumar, Kumar Raja S., Mukhopadhyay, C., and Ramachandra T. V., (2012), A Neural Network Based Hybrid Mixture Model to Extract Information from Non-linear Mixed Pixels. Information, vol.3, no. 3, pp. 420-441.
  • Ramachandra T. V., Uttam Kumar, and N. V. Joshi, (2012), Landscape Dynamics in Western Himalaya – Mandhala Watershed, Himachal Praesh, India. Asian Journal of Geoinformatics, vol. 12, no. 1.
  • Uttam Kumar, Kumar Raja S., Mukhopadhyay, C., and Ramachandra T. V., (2011), Hybrid Bayesian Classifier for Improved Classification Accuracy. IEEE Geoscience and Remote Sensing Letters, vol. 8, no. 3, pp. 473-476.
  • Uttam Kumar, Norman Kerle, Milap Punia, and Ramachandra T. V., (2011), Mining Land Cover Information using Multilayer Perceptron and Decision Tree from MODIS data. Journal of the Indian Society of Remote Sensing, vol. 38, no. 4, pp. 592-603.
  • Uttam Kumar, Anindita Dasgupta, Mukhopadhyay, C., N. V. Joshi, and Ramachandra T. V., (2011), Comparison of 10 Multi-Sensor Image Fusion Paradigms for IKONOS images. International Journal of Research and Reviews in Computer Science, Academy Publisher, United Kingdom, vol. 2, no. 1, pp. 40-47.
  • Ramachandra T. V. and Uttam Kumar, (2011), Characterisation of Landscape with Forest Fragmentation Dynamics. Journal of Geographic Information System, vol. 3, no. 3, pp. 234-246.
  • Ramachandra T. V., and Uttam Kumar, (2009), Land Surface Temperature with Land Cover Dynamics: Multi-Resolution, Spatio-Temporal Data Analysis of Greater Bangalore. International Journal of Geoinformatics, vol. 5, no. 3, pp. 43-53.
  • Uttam Kumar, Mukhopadhyay, C., and Ramachandra T. V., (2009), Spatial Data Mining and Modeling for Visualisation of Rapid Urbanisation. SCIT Journal, vol. IX, pp. 1-9.
  • Uttam Kumar and Ramachandra T. V., (2008), Endmembers Discrimination in MODIS Using Spectral Angle Mapper and Maximum Likelihood algorithms. International Journal of Applied Remote Sensing, vol. 2, no. 1, pp. 1-14.
  • Ramachandra T. V. and Uttam Kumar, (2008), Wetlands of Greater Bangalore1, India: Automatic Delineation through Pattern Classifiers. The Greendisk Environmental Journal, (International Electronic Journal), vol. 1, no. 26, pp.1-22.

Book Chapters

  • Uttam Kumar, Cristina Milesi, S. Kumar Raja, Ramakrishna R. Nemani, Sangram Ganguly, Weile Wang, Saikat Basu, (2017), Unmixing Algorithms: A Review of Techniques for Spectral Detection and Classification of Land Cover from Mixed Pixels on NASA Earth Exchange, Chapter 8. In: Large-Scale Machine Learning in the Earth Sciences (Eds. Ashok N. Srivastava, Ramakrishna Nemani, Karsten Steinhaeuser). Chapman and Hall/CRC Press, Taylor & Francis Group, 43 pp.
  • Uttam Kumar, Mukhopadhyay, C., and Ramachandra T. V., (2015), Multi Resolution Spatial Data Mining for Assessing Land use Patterns, Chapter 4, In: Data Mining and Warehousing (Eds. Elayidom M Sudheep). CENGAGE Learning, India. ISBN 10: 8131525864 / ISBN 13: 9788131525869
  • Ramachandra T. V., Uttam Kumar and Bharath H. Aithal, (2012), Ecosystem Approach for Mitigation of Urban Flood Risks. Chapter 7, In: Ecosystem Approach to Disaster Risk Reduction (Eds. Anil K. Gupta and Sreeja, S. Nair). Published by National Institute of Disaster Management (NIDM), Ministry of Home Affairs, Govt. of India, IIPA Campus, New Delhi - 110002, India, pp. 103-119.
  • Ramachandra T. V., and Uttam Kumar, (2009), Geoinformatics for Urbanisation and Urban Sprawl pattern analysis. Chapter 19, In: Geoinformatics for Natural Resource Management (Eds. Joshi et al.). Nova Science Publishers, NY, pp. 235-272.
  • Uttam Kumar, Norman Kerle, and Ramachandra T. V., (2008), Constrained linear spectral unmixing technique for regional land cover mapping using MODIS data. In: Innovations and advanced techniques in systems, computing sciences and software engineering (Eds. Khaled Elleithy). Springer, Berlin, pp. 87-95.

Conference Proceedings

  • Uttam Kumar, Sangram Ganguly, Cristina Milesi, and Ramakrishna R. Nemani (2015), Fully Constrained Linear Subpixel Classification Algorithms: A Comparative Analysis Based on Heuristic. In Proceedings of the International Conference on Machine Learning and Data Analysis, World Congress on Engineering and Computer Science 2015, Lecture Notes in Engineering and Computer Science, vol. II, pp. 764-769, University of California, Berkley, USA, 21-23 October, 2015, ISBN: 978-988-14047-2-5, ISSN: 2078-0958.
  • Uttam Kumar, Cristina Milesi, Sangram Ganguly, S. Kumar Raja, and Ramakrishna R. Nemani, (2015), Simplex Projection for Land Cover Information Mining from Landsat-5 TM Data. In Proceedings of the 16th IEEE International Conference on Information Reuse and Integration, San Francisco, USA, August, 13-15, 2015, pp. 244-251, IEEE Computer Society. DOI 10.1109/IRI.2015.48
  • Uttam Kumar, Cristina Milesi, S. Kumar Raja, Sangram Ganguly and Ramakrishna R. Nemani, (2015), Unconstrained Linear Spectral Mixture Models for Spatial Information Extraction: A Comparative Study. In Proceedings of the 4th IEEE International Workshop on Data Integration and Mining (DIM), IEEE Conference on Information Reuse and Integration, San Francisco, USA, August, 13-15, 2015, pp. 574 – 581, IEEE Computer Society. DOI 10.1109/IRI.2015.91
  • Uttam Kumar, Cristina Milesi, S. K. Raja, Ramakrishna R. Nemani, Sangram Ganguly, and Weile Wang, (2015), Land cover fraction estimation with global endmembers using collaborative SUnSAL. In Proceedings of the SPIE Optics + Photonics, Remote Sensing and Modeling of Ecosystems for Sustainability XII, Wei Gao; Ni-Bin Chang, Editors, vol. 9610 (SPIE, Bellingham, WA 2015), 96100B, 9 - 13 August 2015, San Diego, CA, USA.
  • Uttam Kumar, Cristina Milesi, Ramakrishna R. Nemani and Saikat Basu, (2015), Multi-Sensor Multi-Resolution Image Fusion for Improved Vegetation and Urban Area Classification. In Proceedings of the 2015 International Workshop on Image and Data Fusion, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-7/W4, 2015, 21 – 23 July 2015, Kona, Hawaii, USA, pp. 51 – 58. doi:10.5194/isprsarchives-XL-7-W4-51-2015
  • Uttam Kumar, Cristina Milesi, Ramakrishna R. Nemani, S. Kumar Raja, Sangram Ganguly and Weile Wang, (2015), Sparse Unmixing via Variable Splitting and Augmented Lagrangian or Vegetation and Urban Area Classification Using Landsat Data. In Proceedings of the 2015 International Workshop on Image and Data Fusion, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-7/W4, 2015, 21 – 23 July 2015, Kona, Hawaii, USA, pp. 59 – 65. doi:10.5194/isprsarchives-XL-7-W4-59-2015
  • Uttam Kumar, Anindita Dasgupta, Mukhopadhyay, C., and Ramachandra T. V., (2012), Advanced Machine Learning Algorithms based Free and Open Source Packages for Landsat ETM+ Data Classification, In Proceedings of the First National Conference on Free and Open Source Software for Geospatial (FOSS4G India 2012), IIIT Hyderabad, October 25-27, 2012, Abstract Page No. - 26.
  • Anindita Dasgupta, Uttam Kumar, Mukhopadhyay, C., and Ramachandra T. V., (2012), GRASS with R: An Introductory Tutorial to Open Source GIS & Statistical Computing Software for Geospatial Analysis, In Proceedings of the First National Conference on Free and Open Source Software for Geospatial (FOSS4G India 2012), IIIT Hyderabad, October 25-27, 2012, Abstract Page No. - 17.
  • Uttam Kumar, Anindita Dasgupta, Mukhopadhyay, C., and Ramachandra T. V., (2012), Sequential Maximum A Posterior (SMAP) Algorithm for Classification of Urban Area using Multi-resolution Spatial Data with Derived Geographical Layers, In Proceedings of the India Conference on Geo-spatial Technologies & Applications, Indian Institute of Technology, Bombay, April 12-13, 2012.
  • Uttam Kumar, Anindita Dasgupta, Mukhopadhyay, C., and Ramachandra T. V., (2012), Geographical Indicators for Sustainable Management of Urban Sprawl, Samanway 2012, Faculty Hall, Indian Institute of Science, Bangalore, India, 3-4 March, 2012.
  • Uttam Kumar, S. Kumar Raja, Mukhopadhyay, C., and Ramachandra T. V., (2011), A Multi-layer Perceptron based Non-linear Mixture Model to estimate class abundance from mixed pixels, IEEE Students’ Technology Symposium, Indian Institute of Technology, Kharagpur, India, 14-16 January, 2011, pp. 148-153.
  • Uttam Kumar, Anindita Dasgupta, Mukhopadhyay, C., and Ramachandra T. V., (2011), Random Forest Algorithm with derived Geographical Layers for Improved Classification of Remote Sensing Data, IEEE INDICON 2011, Hyderabad, India, 17-18 December, 2011, Abstract page no. 37.
  • Uttam Kumar, Mukhopadhyay, C., and Ramachandra T. V., (2009), Cellular automata and Genetic Algorithms based urban growth visualization for appropriate land use policies, In Proceedings of the Fourth Annual International Conference on Public Policy and Management, Centre for Public Policy, Indian Institute of Management (IIMB), Bangalore, India, 9-12 August, 2009.
  • Uttam Kumar, Mukhopadhyay, C., and Ramachandra T. V., (2009), Fusion of Multisensor Data: Review and Comparative Analysis, In Proceedings of the 2009 WRI Global Congress on Intelligent Systems, 19-21 May 2009, Xiamen, China, vol. 2, pp. 418 – 422, IEEE Computer Society, Conference Publishing Services, Los Alamitos, California.
  • Uttam Kumar, Mukhopadhyay, C., Kumar Raja S., and Ramachandra T. V., (2008), Soft classification based Sub-pixel allocation model, In Proceedings of the International Conference on Operations Research for a growing nation in conjunction with the 41st Annual Convention of Operational Research Society of India, Tirupati, AP, India, 15-17 December, 2008.
  • Ramachandra T. V. and Uttam Kumar, (2004), Geographic Resources Decision Support System for Landuse/Landcover dynamics analysis. In Proceedings of the FOSS/GRASS Users Conference, Bangkok, Thailand, 12-14 September, 2004.

Selected Invited / Guest lectures

  • Indian School of Business (ISB), Hyderabad.
  • National Institute of Technology Surathkal (NITK).
  • Indian Institute of Space Science and Technology (IIST), Thiruvananthapuram.
  • Department of Civil Engineering, IIT Guwahati.
  • 12th NatFoE, Indian National Academy of Engineering (INAE), IIT Guwahati.
  • North East Space Application Centre (NESAC), ISRO, Umiam, Meghalaya.
  • The Bangalore Science Forum, National College, Basavanagudi, Bangalore.
  • Stanford University, CA, USA.
  • NASA South/Southeast Research Initiative (SARI) Agricultural Workshop, New Delhi.
  • Karnataka Science and Technology Academy, Bangalore.
  • S.D.M. College of Engineering and Technology, Dharwad, Karnataka, India.
  • Centre for Mathematical Modelling and Computer Simulation, National Aerospace Laboratory, Bangalore.
  • R V College of Engineering, Bangalore.
  • IIT Kanpur, India.
  • Sri Jayachamarajendra College of Engineering, Mysore, India.
  • Department of Electrical Engineering, Indian Institute of Science, Bangalore.
  • Karunya University, Coimbatore, Tamil Nadu, India.
  • NASA International Regional Science Meeting on LCLUC in South Asia, Coimbatore, India.
  • Cochin University of Science and Technology, Kerala, India.
  • International Institute of Information Technology, Bangalore.
  • Indian Institute of Management, Indore, India.
  • System Science and Informatics Unit, Indian Statistical Institute, Bangalore.
  • Computer Science and Engineering, IIT Bombay.
  • CiSTUP, Indian Institute of Science, Bangalore.
  • Centre for Space Science and Technology in Asia and the Pacific, IIRS, Dehradun, India.
  • National Remote Sensing Centre, ISRO, Hyderabad.
  • S. J. Mehta School of Management, IIT Bombay.
  • Center for Continuing Education, Indian Institute of Science, Bangalore.
  • Mahindra Satyam Technology Center, Hyderabad.
  • School of Urban Design, Wuhan University, Wuhan, China.
  • Indian Institute of Remote Sensing, Dehradun, India.
  • Centre for Artificial Intelligence and Robotics, DRDO, Bangalore.
  • PES Institute of Technology, Bangalore.
  • JNU, New Delhi.
  • National Institute of Design (NID), Ahmedabad, India.

Journal Reviewer

1.) IEEE Transactions on Geoscience and Remote Sensing; 2.) IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing; 3.) IEEE Geoscience and Remote Sensing Letters; 4.) Scientific Reports, Nature; 5.) Photogrammetric Engineering and Remote Sensing, American Society of Photogrammetric and Remote Sensing; 6.) International Journal of Remote Sensing, Taylor and Francis; 7.) Remote Sensing Letters, Taylor and Francis; 8.) International Journal of Digital Earth; 9.) Geocarto International; 10.) International Journal of Applied Earth Observation and Geoinformation, Elsevier; 11.) Applied Geography, Elsevier; 12.) Journal of Environmental Management, Elsevier; 13.) Remote Sensing, MDPI – Open Access Publishing; 14.) ISPRS International Journal of Geo-Information, MDPI – Open Access Publishing; 15.) Information, MDPI – Open Access Publishing; 16.) Egyptian Informatics Journal, Elsevier; 17.) Journal of Renewable and Sustainable Energy, American Institute of Physics; 18.) Smart and Sustainable Built Environment Journal, Emerald Group Publishing; 19.) Sadhana - Academy Proceedings in Engineering Science, Indian Academy of Sciences; 20.) Current Science, Indian Academy of Sciences; 21.) Land, MDPI – Open Access Publishing; 22.) Sensors, MDPI – Open Access Publishing; 23.) Applied Science, MDPI – Open Access Publishing 24.) Remote Sensing in Earth Systems Science, Springer; 25.) PLOS ONE

 

 

 

 

  • DS 707: Data Analytics
  • GEN 511: Machine Learning
  • CS301: Database Systems
  • AI 703: Geographic Information Systems
  • AI 821: Spatial Computing