Lakhan Dev Sharma

About

Lakhan Dev Sharma (Listed in Stanford Top 2% Scientists, SMIEEE) received the PhD degree from Dr B. R. Ambedkar National Institute of Technology Jalandhar, India, in 2018 and an M.Tech. degree from Atal Bihari Vajpayee-Indian Institute of Information Technology and Management, Gwalior, India, in 2012. He has been serving as a Sr. Associate Professor with the School of Electronics Engineering, VIT-AP University, Amaravati, India since 2020. He has teaching experience at various technical institutes and university levels. His research interests include biomedical signal and image processing, machine learning, and deep learning. He is a reviewer of many SCI/SCIE journals at IEEE, Elsevier, and Springer. He is an editorial board member of BMC Medical Informatics and Decision Making, Frontiers in Signal Processing (Biomedical Signal Processing) and Frontiers in Physiology (Computational Physiology and Medicine). He served as organising chair for ICADCML-2024.

Employment

• VIT-AP Campus Sr Assistant Professor
  2020 - Present
• MLV Textile and Engineering College Assistant Professor
  2018 - 2020
• Lovely Professional University Assistant Professor
  2013 - 2014
• Parul Group of Institutes Assistant Professor
  2012 - 2012

Education

• Dr. B R Ambedkar National Institute of Technolgy, Jalandhar PhD
  2014 - 2018
• ABV-Indian Institute of InformationTechnology and Management, Gwalior M. Tech.
  2010 - 2012
• NRI Institute of Technology and Management B. E.
  2003 - 2007

Projects & Funding

Projects & funding information is unavailable.

Publications (77)

• Automated human emotion recognition from EEG signals using chaotic local binary pattern and ensemble learning
  International Journal of Machine Learning and Cybernetics 2026 DOI: 10.1007/s13042-025-02822-7
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• EOG-free EEG using successive variational mode decomposition and fuzzy c-means clustering
  Biomedical Signal Processing and Control 2026 DOI: 10.1016/j.bspc.2025.109434
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• Detection of cognitive load using EEG signal and lifting wavelet transform with specific lead selection
  Biomedical Physics & Engineering Express 2025 DOI: 10.1088/2057-1976/ade15a
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• Deep Fusion of VGG19 and ConvMixer With Superlet Transform for Cognitive Load Detection
  IEEE Transactions on Consumer Electronics 2025 DOI: 10.1109/TCE.2025.3618009
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• Advancements in AI for cardiac arrhythmia detection: A comprehensive overview
  Computer Science Review 2025 DOI: 10.1016/j.cosrev.2024.100719
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• Cross-Subject Emotion Recognition From Multichannel EEG Signals Using Multivariate Decomposition and Ensemble Learning
  IEEE Transactions on Cognitive and Developmental Systems 2025 DOI: 10.1109/TCDS.2024.3417534
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• Segmentation and Classification of Pulmonary Diseases Using Artificial Neural Networks and Otsu-Region-Based Method from Chest Radiographs
  2025 DOI: 10.1007/978-981-96-6406-1_26
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• Expunging Baseline Wander from ECG Signals by Empirical Wavelet Transform Based Dyadic Boundary Points
  Circuits, Systems, and Signal Processing 2025 DOI: 10.1007/s00034-025-03245-z
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• Softflatten-Net: A Deep Convolutional Neural Network Design for Monkeypox Classification From Digital Skin Lesions Images
  IEEE Sensors Journal 2024 DOI: 10.1109/JSEN.2024.3445286
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• Classification of lung disorders in chest multi-modal images using hyper-Parameter tuning and modified ResNet50
  Multimedia Tools and Applications 2024 DOI: 10.1007/s11042-024-20097-y
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