Sanjay Agal
Also known as: Sanjay Agal
Parul University, DR. V. R. GODHANIA COLLEGE OF ENGINEERING & TECHNOLOGY, Pacific University, Faculty of Engineering & Technology , Mewar University, Aravali Institute of Technical Studies
About
I am Dr. Sanjay Agal, a dedicated educator and passionate researcher currently serving as a Professor and Head of Department Artificial Intelligence and Data Science at Parul University in Vadodara, India. With a rich background as the former Principal of Dr. VR Godhania College of Engineering & Technology in Porbandar, my journey in academia has been marked by excellence and innovation. Endorsed by Gujarat Technological University (GTU) for the role of Principal in 2023, I take pride in my contributions to the field, which include the authorship of six books, numerous international publications, and holding several patents. Committed to inspiring the next generation of innovators, I am driven by a relentless pursuit of knowledge and a vision to shape the future of engineering education.
Employment
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Parul University Professor & Head of Department2024 - Present
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DR. V. R. GODHANIA COLLEGE OF ENGINEERING & TECHNOLOGY Principal2017 - 2023
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Aravali Institute of Technical Studies HOD & Associate Professor2016 - 2017
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Pacific College of Engieernig Associate Professor & HOD2009 - 2016
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Niit Udaipur Faculty2008 - 2009
Education
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Pacific University Phd2014 - 2016
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Faculty of Engineering & Technology , Mewar University Master of Technology2010 - 2012
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Engineering College Kota Bachelor of Engineering2005 - 2008
Projects & Funding
Projects & funding information is unavailable.
Publications (54)
- PipeTwin Save
- EduSynX Save
- SynEdu-HEDL: A Synthetic Dataset for Early Warning Prediction of Student Success Save
- PipeBench : End to End ML Pipeline Benchmarking Save
- OpenMultiModalLiverCirrhosisDataset Save
- SynthCity Save
- SyntInfra-India: A Large-Scale Synthetic Dataset for AI-Driven University Infrastructure Analytics in Indian Higher Education Save
- LMS-FAIR-India Save
- SynLAD-HE Save
- EduSuccessX: A Public Synthetic Dataset for Explainable Student Success Prediction in Higher Education Save