Dr. Monika Agarwal

About

I completed B. Tech from JECRC, Jaipur in year 2009 and M. Tech from NIT, Jaipur in year 2014. I completed Ph.D. from G.D. Goenka University, Gurugram in year 2021. I qualified the GATE exam in year 2012. My primary research interest areas are Image processing, Machine Learning and Deep Learning. I mainly focused on design and development of various efficient contrast enhancement techniques for medical MRI images quality improving. I developed an efficient model for accurate detection and classification of brain tumour. I am self-starter, fast learner with curiosity to learn new things, expert in building and leading teams, highly motivated & enthusiastic to initiate changes in organization, easily adjustable to unfamiliar environments I am also expertise in relationship management, team management, administrative activities, persuasion, program management, inter-personal skills, problem solving and analytical skills

Employment

• Dayananda Sagar University Assistant Professor
  2022 - Present

Education

• G. D. Goenka University PhD
  2016 - 2021

Projects & Funding

Projects & funding information is unavailable.

Publications (13)

• Enhancing Sentiment Analysis with Retrieval-Augmented Generation and Domain-Specific Fine-Tuning
  2026 DOI: 10.1007/978-3-032-18480-1_47
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• Evaluation and Potential Future Advancements in Enhancing Image Resolution with ESRGAN
  2026 DOI: 10.1007/978-981-96-8998-9_27
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• From Text to Treatment: Predicting Mental Health Needs Through Language Analysis and Machine Learning
  2025 DOI: 10.1007/978-981-96-4539-8_18
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• Lucy AI: Women’s Health Chatbot with Diabetic Retinopathy Classification Using Retinal Fundus Images
  2025 DOI: 10.1007/978-981-96-2179-8_20
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• A Hybrid Approach for Deep Fake Detection Using Deep Learning Algorithm
  2024 DOI: 10.1007/978-981-97-6714-4_11
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• Contrast Enhancement of Medical Images Using Otsu’s Double Threshold
  2024 DOI: 10.1007/978-981-97-2079-8_16
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• Potential Exoplanet Detection Using Feature Selection, Multilayer Perceptron, and Supervised Machine Learning
  2024 DOI: 10.1007/978-981-97-2079-8_29
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• Sequential Model for Digital Image Contrast Enhancement
  Recent Advances in Computer Science and Communications 2021 DOI: 10.2174/2666255813999200717231942
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• Optimized contrast enhancement for tumor detection
  International Journal of Imaging Systems and Technology 2020 DOI: 10.1002/ima.22408
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• Contrast Enhancement Using Optimum Threshold Selection
  International Journal of Software Innovation 2020 DOI: 10.4018/IJSI.2020070107
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