IIT Indore
My research interests are around the Softcomputing frameworks which are able to perform learning by handling real life ambiguous situations. Specifically with artificial neural networks, fuzzy clustering, genetic programming and their applications to bioinformatics, medical diagnosis The growing births of new intelligent system architectures are often due to the multi strategy learning and adaptation of advanced soft computing techniques in various fields such as pattern recognition, and data mining, particularly to address the issues of Big Data for classification, clustering and feature selection. Big data computing needs advanced technologies or methods to solve the issues of computational time to extract valuable information, in a realistic and practical time frame, without compromising the models quality. Therefore, the need for developing intelligent scalable algorithms has been felt, which will be able to perform classification, clustering and feature selection in optimal sense after adjusting their parameters in an adaptive way to accomplish faster solutions to address Big Data. Currently collaborating with Soyabean Research centre, Indore and CDAC, Bioinformatics group Pune.

Specifically dealing with problems for solving classification, Clustering, Prediction for handling large unstructured data having overlaps between data belonging to various classes, adaptation capability, unbalanced classes. My group is working with Fuzzy based supervised and unsupervised Learning Algorithms with an application to Big Data Classification. Also, working with Genetic Programming based learning algorithm in pattern recognition domain. A neuro-fuzzy model has been designed to work out the cluster validation to address the problem of validity of fuzzy partition. This can lead to better modeling of learning algorithms with efficient construction of a classifier for big data handling. Currently, work has been initiated in the area of Quantum based neural learning algorithms. All these algorithms are mainly focusing on applications like Biometric recognition, EEG signal classification, Protein sequence classification, Sentiment analysis.


Member Professional Bodies:
(i) Life member of Computer Society of India.
(ii) Member of IEEE Computational Intelligence Society.
(iii) Life member of Soft Computing research Society, India. See more

Reviewer for Conferences / Journals:
(i) Reviewed a paper of IEEE Transaction of Knowledge and Data Engineering detailed as (August 2012) TKDE-2012-06-0405, "A Hybrid Method of Nonlinear Data-Driven Feature Transformations to Derive Decision Boundaries in Complex Pattern Classification"
(ii) Member of Program and Review Committee of IITM 2013(Second International Conference on Intelligent Interactive Technologies and Multimedia), IIIT Allahabad, India.
(iii) Sub reviewer of 10th International Symposium on Neural Networks (ISNN 2013) Dalian, China.
(iv) In many international conferences, worked as program committee member and reviewed papers.


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Dr. Aruna Tiwari
Associate Professor
Computer Science and Engineering

artiwari[at]iiti.ac.in
Faculty Profile
Computer Science and Engineering