Nakul Padalkar is an associate professor of the practice at BU\u2019s Metropolitan College. With a PhD in management information systems from Texas Tech University and a decade of industry and academic experience, Dr. Padalkar is an expert in the intersection of technology, economics, and society. Prior to joining Metropolitan College, Padalkar was an assistant professor of data science and analytics at Georgetown University, where his teaching focused on education for technologies such as blockchain, computer vision, machine learning, and artificial intelligence, as well as the issues surrounding them. His ongoing research on blockchain evaluates its application for traceability and transparency of battery supply chains, specifically for illicit financial flows. His research on machine learning extends to the ethical applications of the large language models for deep fake detections for the institutional press, causal inference of the deep vision models, and the reproducibility and replicability (ethical AI) of the machine learning models. Through his work, he seeks to apply disruptive technologies to solve industry, societal, and governance problems.<\/p>\n
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Desai, A., Abdelhamid, M., and Padalkar, N. R. \u201cWhat is reproducibility in artificial intelligence and machine learning research?\u201d (2024). arXiv preprint arXiv:2407.10239<\/p>\n
Padalkar, N. R., and Yashwinder Ghura, T. S. \u201cDEFIYIELD: Exploitation of open blockchain platforms.\u201d In Americas\u2019 Conference on Information Systems (2023): 1\u20138.<\/p>\n
Padalkar, N. R., and De Lima, V. \u201cRecommendation systems with causal inference-based regularization.\u201d In Americas\u2019 Conference on Information Systems (2023): 1\u20135.<\/p>\n
Padalkar, N. R., and Jin, Y. \u201cMicrogrid cooperatives in emerging countries\u2014Impact of decentralization in rural India.\u201d In Americas\u2019 Conference on Information Systems (2021): 1\u201317.<\/p>\n
Padalkar, N. R. \u201c’Stonks to the moon’: Evidence from Reddit posts and corresponding market manipulation.\u201d In Americas\u2019 Conference on Information Systems 2021): 1\u20135.<\/p>\n
Padalkar, N. R., Sheikh-Zadeh, A., and Song, J. \u201cBusiness value of smart contract: Case of inventory information discrepancies.\u201d In Americas\u2019 Conference on Information Systems (2020): 1\u201310.<\/p>\n
Padalkar, N. R., Sheikh-Zadeh, A., and Song, J. \u201cImpact of blockchain on information discrepancies in inventory operations.\u201d In INFORMS 2020 Virtual Conference (2020).<\/p>\n
Padalkar, N. R., Sheikh-Zadeh, A., and Song, J. \u201cValue creation in smart contract enabled supply chain.\u201d In BIG XII+ MIS Symposium (2019): 1\u201310.<\/p>\n
Padalkar, N. R., and Blatchley, C. \u201cComparison of color matching functions and cone fundamentals.\u201d In Nebraska Academy of Sciences (2010).<\/p>\n
Padalkar, N. R., and Rodriguez, J. \u201cPrinting process optimization and control using Taguchi\u2019s robust design.\u201d In Technical Association of Graphic Arts Proceedings (2008).<\/p>\n
Padalkar, N. R., Oswal, R., and Virdhe, A. \u201cProcess variability optimization and control.\u201d In IARIGAI, International Research Conference (2007).<\/p>\n
Padalkar, N. R., Oswal, R., and Virdhe, A. \u201cProcess variability optimization and control: Application of Taguchi\u2019s robust design to printing processes.\u201d In Institute of Engineers Proceedings (2006).<\/p>\n
Working Papers<\/strong> Nakul Padalkar, Daniel Cisek, and Jacob McIntosh. \u201cHuman Bias Spillover in Computer Vision.\u201d In In Preparation (2022): 1\u201311.<\/p>\n Nakul R. Padalkar. \u201cEvaluation of Blockchain Technology for Cycle Counting in supply chains with Information Discrepancies.\u201d In Working Paper (2020): 1\u201345. Welcome to MET, Dr. Padalkar! Which program at MET will you be lecturing in? What is your area of expertise?<\/strong> My work involves studying disruptive technologies and their social implications. Some of my current research includes blockchain and distributed ledger technologies, which entails exploring traceability and geo-indication, addressing technology and illicit financial flows, and evaluating distributed energy markets in emerging countries.<\/p>\n I also study machine learning and computer vision, with particular focus on social and environmental applications, such as wildlife conservation, effectively detecting large-scale fake images generated by the language-vision models, and investigating computational biases and causality in deep learning models.<\/p>\n My recent publications include work on blockchain and illicit financial flows published at the International Monetary Fund\u2019s 11th Statistical Conference<\/a> and a study on the \u2018Reproducibility of Artificial Intelligence and Machine Learning Research\u2019<\/a>.<\/p>\n How does the subject you work in apply in practice? What is its application?<\/strong> What courses are you teaching at MET?<\/strong> How does your past experience help to inform your teaching?<\/strong> Please highlight a project within one of your courses that most interests your students.<\/strong> What \u201creal-life\u201d exercises do you bring to class?<\/strong> Is there anything else you would like to add?<\/strong> <\/div>\n<\/div>\n<\/p>\n","protected":false},"author":2836,"template":"","_links":{"self":[{"href":"https:\/\/www.bu.edu\/met\/wp-json\/wp\/v2\/profile\/88592"}],"collection":[{"href":"https:\/\/www.bu.edu\/met\/wp-json\/wp\/v2\/profile"}],"about":[{"href":"https:\/\/www.bu.edu\/met\/wp-json\/wp\/v2\/types\/profile"}],"author":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/met\/wp-json\/wp\/v2\/users\/2836"}],"version-history":[{"count":8,"href":"https:\/\/www.bu.edu\/met\/wp-json\/wp\/v2\/profile\/88592\/revisions"}],"predecessor-version":[{"id":97739,"href":"https:\/\/www.bu.edu\/met\/wp-json\/wp\/v2\/profile\/88592\/revisions\/97739"}],"wp:attachment":[{"href":"https:\/\/www.bu.edu\/met\/wp-json\/wp\/v2\/media?parent=88592"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
\nNakul Padalkar, Samuel Pastoriza, and Monroe Farris. \u201cNeural Network based recommendations: A Design Science Approach.\u201d In In Preparation (2022): 1\u20138.<\/p>\n
\n<\/div>\n<\/div>\nFaculty Q&A<\/h2>
New Associate Professor and Disruptive Technologies Expert Finds Ways to Blend Machine Learning, Blockchain Tech with Conservation Efforts<\/h3>\n
\nI am housed in Metropolitan College\u2019s Applied Business Analytics program under the Department of Administrative Sciences.<\/p>\n
\nDisruptive technologies have the potential to be harmful to social and economic well-being. My research focuses on the smaller aspects of these technologies to evaluate possible pathways to curb the ill effects of their large-scale use. For example, illicit financial flows are detrimental to a developing country\u2019s economic well-being, and technologies like blockchain can help create effective tracking mechanisms. My current research in illicit financial flows explores the reverse logistics (recycling of used batteries) of lead acid batteries in Asia and the utilization of distributed ledger technologies.<\/p>\n
\nI teach Business Analytics Foundations (MET AD 571)<\/a>, Web Analytics for Business (MET AD 688)<\/a>, and Quantitative and Qualitative Decision Making (MET AD 715)<\/a>.<\/p>\n
\nMy extensive research and collaboration with industrial partners in blockchain, machine learning, and computer vision provide me with real-world insights that I bring into the classroom. These experiences enable me to teach students the theoretical aspects and the practical applications of disruptive technologies. I have consistently used my experience in currency printing to discuss the mechanisms of cryptocurrencies and their relevance to financial systems.<\/p>\n
\nOne of the most engaging projects is the application of computer vision in wildlife conservation. Students work on real-world data, such as analyzing camera trap images to detect and classify species, which directly applies machine learning concepts to solve environmental challenges.<\/p>\n
\nI incorporate real-life exercises that involve analyzing real datasets, developing machine learning models, and applying blockchain technology to solve practical problems like product traceability or wildlife conservation. These exercises help students understand the tangible impact of their work.<\/p>\n
\nI spend my free time hiking around nearby national forests and capturing images. Coincidentally, I have made a habit of using those pictures in my computer vision class to teach students about image processing and applications of computer vision.\n<\/div>\n