Dinesh

About

Dinesh Kumar Vishwakarma received the Ph.D. degree in the field of Computer Vision and Machine Learning from Delhi Technological University, New Delhi, India, in 2016. He is currently a Professor and Head, the Department of Information Technology, Delhi Technological University. His current research interests include Computer Vision, Deep/Machine Learning, Sentiment Analysis, Fake News Detection, Multimedia Data Analytics, and Crowd Behaviour Analysis. He received research excellence awards from the Delhi Technological University in the years 2017, 2018, 2019, 2020, 2021 and 2022. He is Associate Editor of IEEE Transactions on Circuits Systems for Video Technology. He has been featured among top 2% scientist of the world by Stanford University in the year 2021, and 2022. He is a reviewer of various journals/transactions of the ACM, IEEE, Elsevier, and Springer. He is a senior member of IEEE, Member of Association for Computing Machinery, and a lifetime member of ISTE.

Employment

• Delhi Technological University Department of Information Technology Professor
  2021 - Present
• Delhi Technological University Associate Professor
  2018 - Present
• Delhi Technological University Assistant Professor
  2010 - 2018
• Amity University Assistant rofessor
  2006 - 2010

Education

• Delhi Technological University PhD ( Computer Vision)
  2011 - 2016
• Motilal Nehru National Institute of Technology Master of Technology
  2003 - 2005
• Dr Ram Manohar Lohia Avadh University Bachelor of Technology
  1998 - 2002

Projects & Funding

Projects & funding information is unavailable.

Publications (273)

• Enhancing quantum classification with custom feature maps in variational quantum classifiers
  Applied Soft Computing 2026 DOI: 10.1016/j.asoc.2026.116164
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• MHS-STMA: Multimodal Hate Speech Detection via Scalable Transformer-Based Multilevel Attention Framework
  ACM Transactions on Asian and Low-Resource Language Information Processing 2026 DOI: 10.1145/3820759
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• Multimodal hateful meme detection using knowledge distillation and hierarchical vision transformer framework
  Engineering Applications of Artificial Intelligence 2026 DOI: 10.1016/j.engappai.2025.113510
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• A Comparative Analysis of Machine Learning Algorithms for Vision-Based Fall Detection Using ORB Features
  2026 DOI: 10.1007/978-3-032-10783-1_21
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• DECA-DiaXEL: An Explainable Ensemble Learning Framework for Early Diabetes Detection in ICU Settings
  2026 DOI: 10.1007/978-3-032-16830-6_28
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• Extracting cross-modal semantic incongruity with attention for multimodal sarcasm detection
  Applied Intelligence 2025 DOI: 10.1007/s10489-025-06717-6
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• Federated workload-aware quantized framework for secure learning in data-sensitive applications
  Future Generation Computer Systems 2025 DOI: 10.1016/j.future.2025.107772
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• Sentiment Classification with Large Language Models: A Study on Generalization and Performance
  International Conference on Inventive Computing and Informatics, Icici 2025 DOI: 10.1109/ICICI65870.2025.11069494
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• A human activity recognition framework in videos using segmented human subject focus
  The Visual Computer 2024 DOI: 10.1007/s00371-023-03256-4
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• A comprehensive review on Federated Learning for Data-Sensitive Application: Open issues & challenges
  Engineering Applications of Artificial Intelligence 2024 DOI: 10.1016/j.engappai.2024.108128
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