Mohd Dilshad Ansari

About

Dr. Mohd Dilshad Ansari is currently working as Associate Professor in the department of Computer Science & Engineering at SRM University Delhi-NCR, India. He received his Ph.D & M.Tech from Jaypee University of Information Technology, Waknaghat, Solan, HP, India in 2018 and 2011 respectively. He obtained his B.Tech in Information Technology From UPTU, Lucknow in 2009. He has published more than 85 papers in International Journals and conferences. He is the Member of various technical/ professional societies such as IEEE, UACEE and IACSIT. He is Associate /Guest Editor of Scopus/SCIE Index Journal and Appointed as Editorial/Reviewer Board as well as Technical Programme Committee member in various reputed Journals/Conferences. His research interest includes Digital & Fuzzy Image Processing, IoT, and Cloud Computing.

Employment

• SRM University Associate Professor
  2023 - Present
• Guru Nanak Institutions Associate Professor
  2022 - 2023
• CMR College of Engineering and Technology Associate Professor
  2022 - 2022
• CMR College of Engineering and Technology Assistant Professor
  2018 - 2022
• Jaypee University of Information Technology Teaching Assistant
  2012 - 2018
• Invertis University Assistant Professor
  2011 - 2012

Education

• Jaypee University of Information Technology Ph.D
  2012 - 2018

Projects & Funding

Projects & funding information is unavailable.

Publications (96)

• Neuroroute-GNNRL: A Hybrid Graph Neural and Reinforcement Learning Framework For Dynamic Node Classification and Speed
  International Journal on Smart Sensing and Intelligent Systems 2026 DOI: 10.2478/ijssis-2026-0017
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• A Framework for Predicting Diabetes Using Machine Learning Techniques
  Cognitive Science and Technology 2026 DOI: 10.1007/978-981-95-0140-3_18
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• Diabetes Prediction in Healthcare with Ensemble Learning
  Lecture Notes in Networks and Systems 2026 DOI: 10.1007/978-981-95-5085-2_6
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• Exposing the Illusion: A Comprehensive Study on Fake Review Detection on Amazon
  Cognitive Science and Technology 2026 DOI: 10.1007/978-981-95-0140-3_10
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• On Machine Learning Techniques to Improve Medical Assessment and Prediction for Diabetes Mellitus
  Cognitive Science and Technology 2026 DOI: 10.1007/978-981-95-0140-3_4
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• Quantum classical convolutional neural network using ResNet-18 and feature optimization for multiclass skin lesion classification
  Discover Artificial Intelligence 2026 DOI: 10.1007/s44163-026-01384-z
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• COSITE 2025 Commentary
  2025 3rd International Conference on Computer System, Information Technology, and Electrical Engineering (COSITE) 2025 DOI: 10.1109/cosite68330.2025.11414370
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• Advancing Cancer Diagnosis: Multi-View Transformer-Guided Federated Learning for Privacy-Preserving and Personalized Multi-Institutional Collaboration
  2025 IEEE 7th International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA) 2025 DOI: 10.1109/icccmla66092.2025.11581155
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• On Multi-Agent AI Framework for Real-Time Swine Disease Identification Using Retrieval-Augmented Diagnostic Systems
  2025 IEEE 7th International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA) 2025 DOI: 10.1109/icccmla66092.2025.11580864
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• Advanced supervised machine learning methods for precise diabetes mellitus prediction using feature selection
  Frontiers in Medicine 2025 DOI: 10.3389/fmed.2025.1620268
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