ADITYA SINHA

About

Computer vision and machine learning enthusiast who has also worked in the field of robotics. I am fascinated by innovation and technology solving real-life problems, intrigued by the scope of science in making life easier for humans Currently I am working as an Assistant Professor at Manipal University Jaipur. I have completed my PhD in the field of Image processing applications for plant disease detection, I have worked on government-funded projects(DST) in the field of Smart Agriculture Electronics specifically on Agri-bots in CSIR-CEERI, Pilani, India and machine vision-based solutions for proof of concept in a biotech-startup based on novel DNA sequencing techniques namely Geneseque AS-Norway.

Employment

• Manipal University - Jaipur Campus Assistant Professor
  2020 - Present
• Manipal University - Jaipur Campus PhD Research Scholar
  2016 - Present
• GeneSeque (Norway) Software Intern
  2012 - 2013
• Central Electronics Engineering Research Institute CSIR Project Associate
  2010 - 2011

Education

• Manipal University - Jaipur Campus Ph.D.
  2016 - 2021
• Manipal Institute of Technology Master of Tehnology
  2011 - 2013
• Swami Keshvanand Institute of Technology Management and Gramothan Bachelor of Engineering
  2005 - 2009

Projects & Funding

Projects & funding information is unavailable.

Publications (18)

• From image processing to artificial intelligence-driven tools: A comprehensive survey on the evolution of feature extraction methods in paintings
  Engineering Applications of Artificial Intelligence 2025 DOI: 10.1016/j.engappai.2025.111794
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• Detection and classification of pathogens causing various plant diseases using supervised machine learning approaches based on hybrid feature sets
  RECENT ADVANCES IN SCIENCES, ENGINEERING, INFORMATION TECHNOLOGY & MANAGEMENT 2023 DOI: 10.1063/5.0154162
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• Lesion isolation using color space thresholding and k-means on powdery mildew affected squash leaves
  RECENT ADVANCES IN SCIENCES, ENGINEERING, INFORMATION TECHNOLOGY & MANAGEMENT 2023 DOI: 10.1063/5.0154163
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• Novel approach for quantification for severity estimation of blight diseases on leaves of tomato plant
  Expert Systems 2023 DOI: 10.1111/exsy.13174
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• An Artificially Intelligent Framework for Plant Health Monitoring
  2023 DOI: 10.22541/au.168011827.75967619/v1
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• Demographic Customer Segmentation of banking users Based on k-prototype methodology
  2022 12th International Conference on Cloud Computing, Data Science Engineering (Confluence) 2022 DOI: 10.1109/Confluence52989.2022.9734169
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• SMS Spam Classification Using Machine Learning Techniques
  2022 12th International Conference on Cloud Computing, Data Science Engineering (Confluence) 2022 DOI: 10.1109/Confluence52989.2022.9734128
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• Protecting Superfood Olive Crop from Pests and Pathogen Using Image Processing Techniques: A Review
  Current Nutrition & Food Science 2021 DOI: 10.2174/1573401318666211227103001
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• A novel image classification technique for spot and blight diseases in plant leaves
  The Imaging Science Journal 2021 DOI: 10.1080/13682199.2020.1865652
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• Classification of Neofabrea and Peacock Leaf Spot Disease in Olive Plants using Image Processing Techniques
  TEQIP -III Sponsored First International Conference on Innovations and Challenges in Computing, Analytics and Security” (ICICCAS-2020 2020 DOI: 10.21467/abstracts.90
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