About:

Hello, welcome to my homepage. I am an Assistant Professor in the Department of Computer Science and Engineering at Indian Institute of Information Technology, Guwahati. I joined IIITG in January, 2022. Prior to that, I did my PhD from National Institute of Technology Arunachal Pradesh under the Visvesvaraya PhD Scheme for Electronics & IT, Ministry of Electronics & IT, India.

Research Interests:

Machine Learning, Pattern Recognition.

Teaching:

At IIITG, I am teaching the following course:

  • Fuzzy Sets, Logic and Systems

Publications:

Journals
  1. Barenya Bikash Hazarika, Deepak Gupta, Parashjyoti Borah, "An intuitionistic fuzzy kernel ridge regression classifier for binary classification,” Applied Soft Computing, vol. 112, pp. 107816-107830, 2021.
  2. Parashjyoti Borah, Deepak Gupta, "Robust twin bounded support vector machines for outliers and imbalanced data,” Applied Intelligence, vol. 51, pp. 5314–5343, 2021.
  3. Deepak Gupta, Parashjyoti Borah, Usha Mary Sharma, Mukesh Prasad, "Data-driven mechanism based on fuzzy Lagrangian twin parametric-margin support vector machine for biomedical data analysis,” Neural Computing and Applications, March, 2021.
  4. Parashjyoti Borah, Deepak Gupta, "Unconstrained convex minimization based implicit Lagrangian twin extreme learning machine for classification (ULTELMC),” Applied Intelligence, vol. 50, pp. 1327-1344, 2020.
  5. Parashjyoti Borah, Deepak Gupta, "Functional iterative approaches for solving support vector classification problems based on generalized Huber loss,” Neural computing and applications, vol. 32, pp. 9245-9265, 2019.
  6. Parashjyoti Borah, Deepak Gupta, "Unconstrained convex minimization based implicit Lagrangian twin random vector Functional-link networks for binary classification (ULTRVFLC),” Applied Soft Computing, vol. 81, pp. 105534-105548, 2019.
  7. Deepak Gupta, Bharat Richhariya, Parashjyoti Borah, "A fuzzy twin support vector machine based on information entropy for class imbalance learning,” Neural computing and applications, vol. 31, pp. 7153-7164, 2018.
Conferences
  1. Parashjyoti Borah, Deepak Gupta, Mukesh Prasad. "Improved 2-norm based fuzzy least squares twin support vector machine." In 2018 IEEE symposium series on computational intelligence (SSCI), pp. 412-419. IEEE, 2018.
  2. Parashjyoti Borah, Deepak Gupta. "A two-norm squared fuzzy-based least squares twin parametric-margin support vector machine." In Machine Intelligence and Signal Analysis, pp. 119-134. Springer, Singapore, 2019.
  3. Deepak Gupta, Parashjyoti Borah, Mukesh Prasad. "A fuzzy based Lagrangian twin parametric-margin support vector machine (FLTPMSVM)." In 2017 IEEE symposium series on computational intelligence (SSCI), pp. 1-7. IEEE, 2017.
  4. Parashjyoti Borah, Deepak Gupta. "On Lagrangian twin parametric-margin support vector machine." In International Conference on Next Generation Computing Technologies, pp. 474-487. Springer, Singapore, 2017.
  5. Rupam Kr Sharma, Hemanta Kumar Kalita, Parashjyoti Borah. "Analysis of machine learning techniques based intrusion detection systems." In Proceedings of 3rd International Conference on Advanced Computing, Networking and Informatics, pp. 485-493. Springer, New Delhi, 2016.

Dr. Parashjyoti Borah

Assistant Professor (CSE)

PhD (NIT Arunachal Pradesh)

Email:

parashjyoti.borah@iiitg.ac.in