Dr. Vhaduri is an assistant professor in the Department of Computer and Information Technology at Purdue University. He received Ph.D. in Computer Science and Engineering at the University of Notre Dame. 

Research Areas: Machine Learning & Deep Learning, Mobile & Wearable Computing, Biometric Authentication, Healthcare Informatics, Internet of Things (IoT)

Affiliations: The Center for Education and Research in Information Assurance and Security (CERIAS), The Institute of Electrical and Electronics Engineers (IEEE), IEEE Computer Society, IEEE Signal Processing Society, IEEE Engineering in Medicine and Biology Society, IEEE Geoscience and Remote Sensing Society.

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                                      Message for Prospective Students 

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Dr. Vhaduri is actively looking for smart graduate students (both master's and Ph.D.) and undergraduate students, who are motivated to make a difference in their lives through impactful and innovative sustainable secure socio-technical research contributions. If you are interested in working with him, please shoot an email with "Research Interest" in your subject line (svhaduri@purdue.edu). While emailing, please describe your background (preferably with a CV for graduate students) and potential projects from THIS LIST that you are interested in.

Additional note for graduate students: If you want to work with me and make me your MS Thesis or Ph.D. Dissertation advisor, you need to checkmark my name as your primary advisor while applying for admission. 
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Dr. Vhaduri works in interdisciplinary collaborative teams consisting of researchers from a range of disciplines from academic and industrial research institutions in the US and Europe, including IBM Research. His research focuses on artificial intelligence (applied machine learning, deep learning, data mining, and data analytics) and mobile & wearable computing with a goal to innovate impactful and sustainable secure technological solutions towards empowering people in order to improve their quality of life using their own mobile devices, such as smartphones and wearables, interconnected via the Internet-of-Things (IoT). To achieve this goal his research integrates three major application areas: (1) HEALTHCARE INFORMATICS, (2) BIOMETRIC AUTHENTICATION, and (3) PLACE DISCOVERY. Dr. Vhaduri's work involves analysis of large-scale human study datasets collected through the mobile crowdsensing (MCS) paradigm. 

List of Publications

Teaching: Machine Learning for Smart Sensing (F'21)