Chandan Gautam

Data Scientist

Continual Learning, Zero-Shot Learning
One-Class Classification, Outlier/Novelty Detection
Kernel Learning, Non-iterative Approaches in Learning, like Kernel Ridge Regression (KRR), Least Squares-based Methods, Random Vector Functional Link (RVFL), Extreme Learning Machines (ELM), etc.

PhD, Indian Institute of Technology Indore, Jan 2015-May 2020.

Advisor: Dr. Aruna Tiwari
THESIS: Kernel-based Learning in the Absence of Counterexamples: One-class Classification [ pdf]
M.Tech, University of Hyderabad, 2012-2014.
Advisor: Dr. V. Ravi
THESIS: Hybrid Intelligence Systems For Data Imputation [ pdf]

Data Scientist, I2R (Institute for Infocomm Research), A*STAR, Jan 2022-Present
Postdoctoral Fellow, ARTPARK (AI & Robotics Technology Park), July 2021-Dec 2021
Postdoctoral Fellow, Indian Institute of Science, Bangalore, Feb 2020-June 2021
Teaching Assistant,Indian Institute of Technology Indore, Jan 2015-Apr 2017
Research Intern, Center of Excellence in CRM and Analytics Lab, Institute for Development and Research in Banking Technology, Hyderabad. June 2013-June 2014

March 2021: Paper Accepted in Neural Computing and Applications
Sep 2020: Paper Accepted in Cognitive Computation
Jan 2019: Received Travel Grant by CoDS-COMAD 2019 to attend the ACM India Joint International Conference on Data Science & Management of Data (6th ACM IKDD CoDS and 24th COMAD).
Dec 2015: Received Travel Grant by Department of Science and Technology, Govt. of India, for attending conference.
January 2015: Received Visvesvaraya Scheme fellowship supported by the Department of Electronics and Information Technology (DEITY), Government of India for doctoral research.

S. P. Kumar, C. Gautam, S. Suresh. Meta-Cognition-Based Simple And Effective Approach To Object Detection, 46th International Conference on Acoustics, Speech, & Signal Processing (ICASSP-2021), Toronto, June, 2021. [Accepted]

C. Gautam, A. Tiwari. Localized Multiple Kernel Support Vector Data Description, International Conference on Data Mining Workshops (IEEE ICDM Workshop-2018), Singapore, pp. 1514-1521, November, 2018. [ICDMW2018]

C. Gautam, A. Tiwari, and A. Iosifidis. Minimum Variance-Embedded Multilayer Kernel Ridge Regression for One-class Classification, IEEE Symposium Series on Computational Intelligence (IEEE SSCI-2018), Bengaluru, India, pp. 389-396, November, 2018. (Flagship annual international conference sponsored by the IEEE Computational Intelligence Society). [SSCI2018]

C. Gautam, A. Tiwari, S. Ravindran. Construction of Multi-class Classifiers by Extreme Learning Machine Based One-Class Classifiers, International Joint Conference on Neural Networks (IJCNN-2016), Vancouver, July, 2016 (IEEE). (Flagship conference of the IEEE Computational Intelligence Society and the International Neural Network Society). [IJCNN2016]

C. Gautam, A. Tiwari, P. K. Mishra, S. Suresh, A. Iosifidis, M. Tanveer. Graph-Embedded Multi-layer Kernel Ridge Regression for One-class Classification, Cognitive Computation, vol. 13, pp. 552–569, 2021 (Springer). (IF: 5.418). [CogCom2021]

P. K. Mishra, C. Gautam, A. Tiwari. Minimum Variance-Embedded Autoassociative Kernel Extreme Learning Machine for One-class Classification, Neural Computing and Applications, vol. 33, pp. 12973–12987, 2021 (Springer). (IF: 5.606). [NCA2021]

C. Gautam, P. K. Mishra, A. Tiwari, B. Richhariya, H. M. Pandey, S. Wang, M. Tanveer. Minimum Variance-Embedded Deep Kernel Regularized Least Squares Method for One-class Classification and Its Applications to Biomedical Data, Neural Network, vol. 123, pp. 191-216, 2020 (ELSEVIER). (IF: 5.785). [NN2020]

C. Gautam, A. Tiwari, M. Tanveer. AEKOC+: Kernel Ridge Regression-based Auto-Encoder for One-class Classification using Privileged Information, Cognitive Computation, pp. 1-14, 2020 (Springer). (IF: 4.287). [CogCom2020]

C. Gautam, A. Tiwari, M. Tanveer. KOC+: Kernel Ridge Regression based One-class Classification using Privileged Information, Information Sciences, vol. 504, pp. 324-333, 2019 (ELSEVIER). (IF: 5.524). [INS2019]

C. Gautam, A. Tiwari, S. Suresh, and K. Ahuja. Adaptive Online Learning with Regularized Kernel for One-class Classification, IEEE Transactions on Systems, Man, and Cybernetics: Systems, pp. 1-16, 2019 (IEEE). (IF: 7.351). [TSMC2019]

C. Gautam, R. Balajia, K. Sudharsan, A. Tiwari, and K. Ahuja. Localized Multiple Kernel Learning for Anomaly Detection: One-class Classification, Knowledge-Based Systems, vol. 165, pp. 241-252, 2018 (ELSEVIER). (IF: 5.101). [KBS2019]

C. Gautam, A. Tiwari, and Q. Leng. On The Construction of Extreme Learning Machine for Online and Offline One Class Classifier - An Expanded Toolbox, (Selected in the conference for submitting to this Journal), Neurocomputing, vol. 261, pp. 126-143, 2017 (ELSEVIER). (IF: 4.072). [Neucom2017]

C. Gautam and V. Ravi. Counter Propagation Auto Associative Neural Network based Data Imputation, Information Sciences, vol. 325, pp. 288-299, 2015 (ELSEVIER). (IF: 5.524). [Ins2015]

C. Gautam and V. Ravi. Data Imputation via Evolutionary Computation, Clustering and a Neural Network, Neurocomputing, vol. 153, pp. 134-142, 2015 (ELSEVIER). (IF: 4.072). [Neucom2015]

Review Editor of Frontiers in Applied Mathematics and Statistics
Reviewer of various SCI indexed journals viz., IEEE TNNLS, ACM Transactions on Multimedia Computing Communications and Applications, IEEE Trans. on Cybernetics, Information Fusion, Information Sciences, Neurocomputing, Artificial Intelligence in Medicine, Multidimensional Systems and Signal Processing, and IEEE System Journal.
Provided secretarial and technical assistance in various events viz., CMOCI symposium, MISP conference, GIAN course, various workshops (CMOCI, CSIR-CEERI, and Nature Inspired Optimization Techniques \& their Applications)
Invited to attend ACM-Microsoft-Infosys Academic Research Summit, IISC Bangalore

chandangautam31@gmail.com

gautamc@i2r.a-star.edu.sg

chandang@iisc.ac.in