Dr. Sanyam Shukla
Associate Professor
Google Scholar: https://scholar.google.co.in/citations?user=HMAzliEAAAAJ
Scopus: https://www.scopus.com/authid/detail.uri?authorId=56668302700
ORCID: https://orcid.org/0000-0001-6652-9132
Vidwan: https://vidwan.inflibnet.ac.in/profile/61720
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U.G |
Statistical Methods for Data Interpretation and Analysis |
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Soft computing |
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Machine Learning |
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Optimization Techniques |
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Statistical Methods |
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P.G |
Statistical Method |
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Machine Learning |
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Advanced Machine Learning |
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Organization |
Start Date |
End Date |
Designation |
Nature of Work |
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MANIT, Bhopal |
21/12/2023 | Till Date | Assoicate Professor AGP 9500 |
Teaching and research |
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MANIT, Bhopal |
28/12/2018 |
20/12/2023 |
Assistant Professor AGP 8000 |
Teaching and research |
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MANIT, Bhopal |
04/06/2011 |
27/12/2018 |
Assistant Professor AGP 7000 |
Teaching and research |
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MANIT, Bhopal |
01/01/2006 |
03/06/2011 |
Assistant Professor AGP 6000 |
Teaching and research |
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MANIT, Bhopal |
22/08/2005 |
31/12/2005 |
Lecturer |
Teaching and research |
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SVITS, Indore |
25/06/2003 |
02/08/2005 |
Lecturer |
Teaching |
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Name of the Student |
Topic |
Year of Award |
Co-Supervisor (if any) |
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Bhagat Singh Raghuwanshi |
Variants of Extreme Learning Machine for class |
2020 |
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Roshani Choudhary |
Novel approaches for design of ELM based classifiers to handle class imbalance learning |
2022 |
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Saurabh Shrivastava |
Novel optimization based solutions for supervised learning |
2025 |
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Manali Chandnani |
Traffic Sign Recognition in harsh environment |
Ongoing 2022 batch |
Dr. Rajesh Wadhvani |
|
Juhi |
Optimization of machine learning algorithms using data complexity measures. |
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Supervisor: Dr. Rajesh Wadhvani Co-Supervisor: Dr. Sanyam Shukla |
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Title |
Sponsoring Agency |
Duration |
Amount |
Co-PI (if any) |
| Long Short Term Memory Neural Network based model for solar irradiance forecasting | M. P. Council of Science and Technology | 24 | 4.6 lakhs |
PI: Dr Rajesh Wadhvani Co-PI: Dr. Sanyam Shukla |
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Title |
Sponsoring Agency |
Duration |
Amount |
Co-Investigator (if any) |
|
Authors |
Title |
Journal |
VOL. NO., PAGE NO |
YEAR |
SCI/ Scopus |
IMPACT FACTOR |
| Manali Chandnani, Sanyam Shukla & Rajesh Wadhvani |
Handling heteroscedasticity in kernelized extreme learning machine based regression and deep learning models for traffic sign detection using box cox and Yeo Johnson transformations |
Volume 19, article number 978, | 2025 | SCIE | 1 | |
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Sowkarthika B, Manasi Gyanchandani, Rajesh Wadhvani & Sanyam Shukla |
Data complexity measures for classification of a multi-concept dataset | Multimedia Tools and Applications | Volume 84, pages 571–602 | 2024 | Scopus | 1 |
| Manali Chandnani, Sanyam Shukla, Rajesh Wadhvani | Multistage traffic sign recognition under harsh environment | Multimedia Tools and Applications | Volume 83 Issue 34 Pages 80425-80457 | 2024 | Scopus | 1 |
| Saurabh Shrivastava, Sanyam Shukla, Nilay Khare | Support vector machine with eagle loss function | Expert Systems with Applications |
Volume 238 Pages 122168 |
2024 | SCIE | 7.5 |
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Raghuwanshi B.S., Shukla S. |
SMOTE based class-specific extreme learning machine for imbalanced learning |
Knowledge-Based Systems |
-,187 |
2020 |
SCIE |
8.8 |
|
Raghuwanshi B.S., Shukla S. |
Class-specific kernelized extreme learning machine for binary class imbalance learning |
Applied Soft Computing Journal |
1026-1038,73 |
2018 |
SCIE |
8.7 |
|
Jain S., Singhal M., Shukla S. |
Comments on 'Traffic Sign Recognition Using Kernel Extreme Learning Machines with Deep Perceptual Features' |
IEEE Transactions on Intelligent Transportation Systems |
3759-3761,20 |
2019 |
SCIE |
8.5 |
|
Sowkarthika B., Gyanchandani M., Wadhvani R., Shukla S. |
Data complexity-based dynamic ensembling of SVMs in classification |
Expert Systems with Applications |
-,216 |
2023 |
SCIE |
8.5 |
|
Raghuwanshi B.S., Shukla S. |
Minimum class variance class-specific extreme learning machine for imbalanced classification |
Expert Systems with Applications |
-,178 |
2021 |
SCIE |
8.5 |
|
Choudhary R., Shukla S. |
A clustering based ensemble of weighted kernelized extreme learning machine for class imbalance learning |
Expert Systems with Applications |
-,164 |
2021 |
SCIE |
8.5 |
|
Chandak T., Shukla S., Wadhvani R. |
An analysis of “A feature reduced intrusion detection system using ANN classifier” by Akashdeep et al. expert systems with applications (2017) |
Expert Systems with Applications |
79-83,130 |
2019 |
SCIE |
8.5 |
|
Raghuwanshi B.S., Shukla S. |
Generalized class-specific kernelized extreme learning machine for multiclass imbalanced learning |
Expert Systems with Applications |
244-255,121 |
2019 |
SCIE |
8.5 |
|
Jain S., Shukla S., Wadhvani R. |
Dynamic selection of normalization techniques using data complexity measures |
Expert Systems with Applications |
252-262,106 |
2018 |
SCIE |
8.5 |
|
Shrivastava S.,Shukla S.,Khare N. |
A stable variant of linex loss SVM |
Information Sciences |
in press,in press |
2023 |
SCIE |
8.1 |
| Raghuwanshi B.S., Shukla S. | Minimum variance-embedded kernelized extension of extreme learning machine for imbalance learning | Pattern Recognition | -,119 | 2021 | SCIE | 8 |
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Raghuwanshi B.S., Shukla S. |
UnderBagging based reduced Kernelized weighted extreme learning machine for class imbalance learning |
Engineering Applications of Artificial Intelligence |
252-270,74 |
2018 |
SCIE |
8 |
|
Shukla S., Raghuwanshi B.S. |
Online sequential class-specific extreme learning machine for binary imbalanced learning |
Neural Networks |
235-248,119 |
2019 |
SCIE |
7.8 |
|
Raghuwanshi B.S., Shukla S. |
Class-specific extreme learning machine for handling binary class imbalance problem |
Neural Networks |
206-217,105 |
2018 |
SCIE |
7.8 |
|
Raghuwanshi B.S., Shukla S. |
Class imbalance learning using UnderBagging based kernelized extreme learning machine |
Neurocomputing |
172-187,329 |
2019 |
SCIE |
6 |
|
Raghuwanshi B.S., Shukla S. |
Class-specific cost-sensitive boosting weighted ELM for class imbalance learning |
Memetic Computing |
263-283,11 |
2019 |
SCIE |
4.7 |
|
Raghuwanshi B.S., Mangal A., Shukla S. |
Universum based kernelized weighted extreme learning machine for imbalanced datasets |
International Journal of Machine Learning and Cybernetics |
3387-3408,13 |
2022 |
SCIE |
4.5 |
|
Raghuwanshi B.S., Shukla S. |
Classifying imbalanced data using SMOTE based class-specific kernelized ELM |
International Journal of Machine Learning and Cybernetics |
1255-1280,12 |
2021 |
SCIE |
4.5 |
|
Raghuwanshi B.S., Shukla S. |
Classifying imbalanced data using ensemble of reduced kernelized weighted extreme learning machine |
International Journal of Machine Learning and Cybernetics |
3071-3097,10 |
2019 |
SCIE |
4.5 |
|
Saxena S., Shukla S., Gyanchandani M. |
Breast cancer histopathology image classification using kernelized weighted extreme learning machine |
International Journal of Imaging Systems and Technology |
168-179,31 |
2021 |
SCIE |
3.3 |
|
Saxena S., Shukla S., Gyanchandani M. |
Pre-trained convolutional neural networks as feature extractors for diagnosis of breast cancer using histopathology |
International Journal of Imaging Systems and Technology |
577-591,30 |
2020 |
SCIE |
3.3 |
|
Raghuwanshi B.S., Shukla S. |
Classifying imbalanced data using BalanceCascade-based kernelized extreme learning machine |
Pattern Analysis and Applications |
1157-1182,23 |
2020 |
SCIE |
3.1 |
|
Patil D., Wadhvani R., Shukla S., Gupta M. |
Adaptive wind data normalization to improve the performance of forecasting models |
Wind Engineering |
1606-1617,46 |
2022 |
SCOPUS |
1.4 |
|
Brahma B., Wadhvani R., Shukla S. |
Attention mechanism for developing wind speed and solar irradiance forecasting models |
Wind Engineering |
1422-1432,45 |
2021 |
SCOPUS |
1.4 |
|
Wadhvani R., Shukla S. |
Analysis of parametric and non-parametric regression techniques to model the wind turbine power curve |
Wind Engineering |
225-232,43 |
2019 |
SCOPUS |
1.4 |
|
Raghuwanshi B.S., Shukla S. |
Classifying multiclass imbalanced data using generalized class-specific extreme learning machine |
Progress in Artificial Intelligence |
259-281,10 |
2021 |
SCOPUS |
3.2 |
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Title |
Year |
Agency |
Co-Investigator(if any) |
Published/Granted |
