Dr. Mohd Shoaib Khan
Assistant Professor
Dr. Mohd Shoaib Khan is an Assistant Professor at the Department of Data Sciences and Analytics, School of Social Sciences, Ramaiah University of Applied Sciences. He holds a Bachelor’s degree from Kisan P.G. College, Dr. Rammanohar Lohiya Avadh University, and completed his master’s from Aligarh Muslim University in 2014. Notably, he qualified for CSIR-JRF with an impressive AIR-66 rank. His academic journey culminated with the successful completion of his Ph.D. degree from South Asian University, New Delhi.
With a passion for advancing the field of machine learning, Dr. Khan’s research interests primarily revolve around supervised and unsupervised learning algorithms. Specifically, he delves into the development and improvement of classifiers that can effectively distinguish data using distance measures within metric space. While these algorithms are widely used, they do possess certain limitations, affecting their reliability at the quantitative level. To address these challenges, Dr. Khan is actively engaged in pioneering new algorithms that leverage the qualitative information present in data, such as connected components, holes, voids, and more. This innovative approach falls under the realm of Topological Data Analysis, which holds promising potential for enhancing the accuracy and robustness of machine learning applications.
With his expertise and dedication to pushing the boundaries of machine learning, Dr. Mohd Shoaib Khan continues to make valuable contributions to the scientific community and further propel the field into new frontiers.
Qualifications
B.Sc.
Kisan PG College, Dr. Rammanorar Lohiya Avadh University (Mathematics)
M.Sc.
Aligarh Muslim University (Mathematics)
PhD
South Asian University (Applied Mathematics)
Experience
Total Years of Experience: 1 Year 6 Months
Academic Experience: KL University (1 year) + South Asian University (Teaching Assistant 6 months)
Training Experience
- Topological Data Analysis
- Classification and Clustering problems of Machine Learning
- Fuzzy Theory
- Applied Mathematics
- Topological Data Analysis
- Integral and Measures
- Fuzzy Theory
- Classification and Clustering problems of Machine Learning
- Computer Vision
International Conference Papers
- Khan, M.S., Tiwari, A. and Lohani, Q.D., 2023. Vietoris – Rips Complex induced by Intuitionistic Fuzzy Distance Measure. In 2023 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).
- Tiwari, A. Khan, M.S., and Lohani, Q.D., 2023. Circular Intuitionistic Fuzzy GRA for Hospital location Problem. In 2023 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).
- Khan, M.S., Tiwari, A. and Lohani, Q.D., 2021, July. Necessary and sufficient condition for the existence of Atanassov’s Intuitionistic Fuzzy based additive definite integral. In 2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (pp. 1 – 6). IEEE.
- Khan, M.S., Tiwari, A. and Lohani, Q.D., 2021, July. Necessary and sufficient condition for the existence of Atanassov’s Intuitionistic Fuzzy based additive definite integral. In 2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (pp. 1 – 6). IEEE.
- Khan, M.S., Lohani, Q.D. and Ashraf, Z., 2019, June. Existence of Atanassov’s Intuitionistic Fuzzy Definite Integrals. In 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (pp. 1 – 6). IEEE.
- Khan, Mohd Shoaib$^*$, and QM Danish Lohani. “A similarity measure for atanassov intuitionistic fuzzy sets and its application to clustering.” 2016 International Workshop on Computational Intelligence (IWCI). IEEE, 2016.
International Journal Papers
- Khan, M.S. and Lohani, Q.D., 2022. Topological analysis of intuitionistic fuzzy distance measures with applications in classification and clustering. Engineering Applications of Artificial Intelligence, 116, p.105415.
- KHAN, M.S., KAUSHAL, M. and LOHANI, Q.D., 2022. CES ARO PARANORMED SEQUENCE SPACE BASED INTUITIONISTIC FUZZY DISTANCE MEASURE. Journal of Inequalities & Special Functions, 13(1).
- Ashraf, Z., Khan, M.S., Tiwari, A. and Danish Lohani, Q.M., 2021. Difference sequence-based distance measure for intuitionistic fuzzy sets and its application in decision making process. Soft Computing, 25(14), pp.9139 – 9161.
- Ashraf, Z., Khan, M.S. and Lohani, Q.D., 2019. New bounded variation based similarity measures between Atanassov intuitionistic fuzzy sets for clustering and pattern recognition. Applied Soft Computing, 85, p.105529.
- KHAN, M.S., UDDIN, I. and LOHANI, Q.D., 2019. EXISTENCE OF THE SOLUTION OF COUNTABLY INFINITE SYSTEM OF DIFFERENTIAL EQUATIONS IN SEQUENCE SPACES m p (𝜙) AND n p (𝜙) WITH THE HELP OF MEASURE OF NON-COMPACTNESS. Journal of applied mathematics & informatics, 37(5), pp.329 – 339.
- Khan, M.S. and Lohani, Q.M., 2017. A novel sequence space related to $\mathcal {L} _ {p} $ defined by Orlicz function with application in pattern recognition. Journal of inequalities and applications, 2017(1), pp.1 – 14.
- Khan, M.S., Alamri, B.A., Mursaleen, M. and Lohani, Q.M., 2017. Sequence spaces M (ϕ) $ M (\phi) $ and N (ϕ) $ N (\phi) $ with application in clustering. Journal of inequalities and applications, 2017(1), pp.1 – 12.
- Khan, M.S., Lohani, Q.D. and Mursaleen, M., 2017. A novel intuitionistic fuzzy similarity measure based on double sequence by using modulus function with application in pattern recognition. Cogent Mathematics, 4(1), p.1385374.
Books / Chapter Published
- Ashraf, Z., Hasan, M.G. and Khan, M.S., 2021. Solving interval type‑2 fuzzy reliability-redundancy allocation systems with efficient PSO algorithm. In Advancements in Fuzzy Reliability Theory (pp. 135 – 165). IGI Global.
- Kaushal, M., Shoaib Khan, M. and Lohani, Q.D., 2020. An Approach to Aggregate Intuitionistic Fuzzy Information with the Help of Linear Operator. In Proceedings of International Joint Conference on Computational Intelligence: IJCCI 2018 (pp. 735 – 746). Springer Singapore.
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Algebraic Topology Research Network
Member
European Society for Fuzzy Logic and Technology
Member