Phone:

+91-79-6632 4937

Email:

manish@iima.ac.in

Website:

faculty.iima.ac.in/~manish

Manish Aggarwal

Information Systems

Educational Qualifications

  • M.Tech(CSE/Maths) IIT Delhi
  • Ph.D. (CSE/IT) IIT Delhi

Academic Affiliation

Research Fellowships

  • Visiting doctoral student: Department of Computer Science and Mathematics, Univ. of Marburg, Germany (DAAD Fellowship)
  • Post-doc: Department of Information and Computer Science, Univ. of Trento, Italy (EU Fellowship)
  • Visiting university academician: Department of Informatics, University of Oldenburg, Germany

Professional Affiliation

A decade of research and managerial experience in renowned global corporations.

 

Teaching

 

Area of Research :

  • Information systems
  • Decision sciences
  • Soft computing
  • Fuzzy systems
  • Knowledge representation under uncertainty
  • Machine learning
  • Multi-objective optimization
  • Artificial intelligence

Current Research :

  • Multi criteria decision making (MCDM)
  • Preference learning
  • Evolutionary multi-objective optimization
  • Fuzzy decision analysis
  • Fuzzy sets and systems
  • Rough set theory
  • Information Fusion
  • Plausible and analogical reasoning

Publications/Articles/Cases:

Journal Articles

  • M. Aggarwal, On learning of Choice Models with Interactive Attributes, IEEE Transactions on Knowledge and Data Engineering, to appear.
  • M. Aggarwal, Probabilistic Variable Precision Fuzzy Rough Sets, IEEE Transactions on Fuzzy Systems, IEEE, Impact Factor (IF): 8.74, 2016.
  • M. Aggarwal, M. Hanmandlu, Representing Uncertainty with Information Sets, IEEE Transactions on Fuzzy Systems (IEEE, IF: 8.74), 2016.
  • M. Aggarwal, Linguistic Discriminative Aggregation in Multi-Criteria Decision Making, International Journal of Intelligent Systems (Wiley, IF: 1.88), 2016.
  • M. Aggarwal, On the Learning of Weights through Preferences, Information Sciences (Elsevier, IF: 4.22), pp. 90-102, 2015.
  • M. Aggarwal, Generalized Compensative Weighted Averaging Operators, Computers and Industrial Engineering (Elsevier, IF: 2.41), pp. 81-90, 2015.
  • M. Aggarwal, Compensative Weighted Averaging Operators, Applied Soft Computing (Elsevier, IF: 3.22), Vol. 28, pp. 368-378, 2015.
  • M. Aggarwal, New Family of Induced OWA Aggregation Operators, International Journal of Intelligent Systems (Wiley, IF: 1.88), Vol. 30, pp. 170 – 205, 2015.
  • M. Aggarwal, Probabilistic Fuzzy Rough Sets, Journal of Intelligent and Fuzzy Systems (IOS Press, IF: 1.81), Vol. 29, no. 5, pp. 1901-1912, 2015.
  • M. Aggarwal, T. Palpanas, Linguistic Rough Sets, International Journal of Machine Learning and Cybernetics (Springer), Oct. 2014.
  • M. Aggarwal, A. F. Tehrani, E. Hullermeier, Preference-based Learning of Ideal Solutions in TOPSIS-like Decision Models, Journal of Multi-Criteria Decision Analysis (Wiley), Vol. 22, Issue 3-4, pp. 715-183, 2014.
  • M. Aggarwal, K. K. Biswas, M. Hanmandlu, Generalized intuitionistic fuzzy soft sets with applications in decision-making, Applied Soft Computing (Elsevier, IF: 3.22), Vol. 13, Issue 8, pp. 3552 – 3566, 2013. 
    Top 25 Hottest (most downloaded) Elsevier article in 2013.
  • M. Aggarwal, M. Hanmandlu, K. K. Biswas, A Probabilistic and Decision Attitude Aggregation Operator for Intuitionistic Fuzzy Environment, International Journal of Intelligent Systems (Wiley, IF: 1.88), Vol. 28, Issue 8, pp. 806 – 839, 2013.


Book Chapter

  • M.Aggarwal, K. K. Biswas, M. Hanmandlu, Handling Fuzzy Models in the Probabilistic domain, in: Computational Intelligence, Studies in Computational Intelligence (SCI), Madani et al. (Eds.), Springer, Berlin, pp. 137 - 151, 2013.


Peer-Reviewed Proceedings

  • M. Aggarwal, M. Hanmandlu, K. K. Biswas, The Properties and Information Measures for Information Sets, IEEE International Conference on Fuzzy Systems (FUZZ-IEEE, 2014), Accepted, 6-11 July 2014, Beijing, China.
  • M. Aggarwal, M. Hanmandlu, K. K. Biswas, New Linguistic Aggregation Operators for Decision Making, IEEE International Conference on Fuzzy Systems (FUZZ-IEEE, 2014), Accepted, 6-11 July 2014, Beijing, China.
  • M. Aggarwal, K. K. Biswas, M. Hanmandlu, Intuitionistic fuzzy soft preference relations and application in decision making, IEEE International Conference on Fuzzy Systems (FUZZ-IEEE, 2013) , pp. 1 - 8, 7 - 10 July 2013, Hyderabad, India.
  • M. Aggarwal, K. K. Biswas, M. Hanmandlu, Choquet integral vs. TOPSIS: An intuitionistic fuzzy approach, IEEE International Conference on Fuzzy Systems (FUZZ-IEEE, 2013), pp. 1 - 8, 7 - 10 July 2013, Hyderabad, India.
  • M. Aggarwal, K. K. Biswas, M. Hanmandlu, Probabilistic Intuitionistic Fuzzy Models, 5th International Conference on Automation, Robotics and Applications (ICARA, 2011), pp. 214 - 219, Dec. 6 - 8, Wellington, New Zealand, 2011.
  • M. Aggarwal, K. K. Biswas, M. Hanmandlu, Fuzzy Model Building using Probabilistic Rules, International Conference on Fuzzy Computation Theory and Applications, IJCCI (FCTA, 2011), Scitepress, pp. 361 - 369, Paris, France, 24 - 26 Oct. 2011. Nominated for best student paper.
  • M. Aggarwal, K. K. Biswas, M. Hanmandlu, Relations in Generalized Intuitionistic Fuzzy Soft Sets, IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (CIMSA, 2011), Sep 19 - 22, Ottawa, Canada, 2011.
  • M. Aggarwal, M. Hanmandlu, K. K. Biswas, Generalized intuitionistic fuzzy soft set and its application in practical medical diagnosis problem, IEEE International Conference on Fuzzy Systems (FUZZ-IEEE, 2011), pp. 2972 - 2978, Taipei, Taiwan, 27 - 30 June 2011.

Consulting

 

Awards & Honors

Year Awards & Honors
   

 

Thoughts

 

Staging Enabled