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About me
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Silver linings of the pandemic.
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This article is about the key areas I want to work on, eventually.
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This article is about the key areas I want to work on, eventually.
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Human mind, collectively and individually, has given birth to all of civilization. Every contribution of the mankind that we see, be it the tallest skyscraper, Mars landing spacecraft, or tiniest nanotechnologies, someone somewhere imagined it long before it came to existence. The scientific mind, often isolated in their office or small laboratories, worked hundreds and thousands of hours to solve each puzzle to make these imaginations a reality….
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For thousands of years, mankind has failed to unite behind a common cause. Religion, nationalism, capitalism, communism, socialism, Marxism: none of these could have united the mankind…
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Published in Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Best Paper Nomination), 2012
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Published in Proceedings of the 2nd ACM international workshop on Pervasive Wireless Healthcare, 2012
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Published in Proceedings of the 2013 Research in Adaptive and Convergent Systems (RACS 2013) (Best Paper), 2013
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Published in ACM SIGAPP Applied Computing Review, 2013
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Published in Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE, 2014
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Published in Computer Software and Applications Conference (COMPSAC), 2015 IEEE 39th Annual, 2015
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Published in Computing in cardiology, 2016
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Published in Journal of Global Oncology, 2017
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Published in AMIA 2017 Annual Symposium, 2017
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Published in American Thoracic Society (ATS) Conference, 2018
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Published in Physiological measurement, 2018
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Published in medRxiv, 2019
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Published in Critical Care Medicine, 2019
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Published in CHEST conference, 2019
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Published in Frontiers in Neurology, 2020
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Published in Under review, 2020
Published in Machine Learning for Healthcare, 2020 (pre-print), 2020
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Published in The 11th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB), 2020 (pre-print), 2020
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We describe a new model for collaborative access, exploration, and analyses of the Medical Information Mart for Intensive Care - III (MIMIC III) database for translational clinical research. The proposed model addresses the significant disconnect between data collection at the point of care and translational clinical research. It addresses problems of data integration, preprocessing, normalization, analyses (along with associated compute back-end), and visualization. The proposed platform is general, and can be easily adapted to other databases. The pre-packaged analyses toolkit is easily extensible, and allows for multi-language support. The platform can be easily federated, mirrored at other locations, and supports a RESTful API for service composition and scaling.
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Despite the promise of big data, little evidence has been generated for clinical practice with data driven systems. A new model for collaborative access, exploration, and analyses of integrated clinical data will be presented with a standard database, Medical Information Mart for Intensive Care - III (MIMIC III), for translational clinical research. The proposed model addresses the significant disconnect between data collection at the point of care and translational clinical research. It addresses problems of data integration, pre-processing, normalization, analyses (along with associated compute back-end), and visualization. The pre-packaged analyses toolkit is easily extensible, and allows for multi-language support. The platform can be easily federated, mirrored at other locations, and supports a RESTful API for service composition and scaling.
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We aim to develop critical and enabling cyberinfrastructure for integrated analyses of longitudinal and time-series data from the multitude of sensors in common commercial wearables, in conjunction with the corresponding patient pharmacological and electronic health records EHRs). Effective analyses of this rich source of data has the potential to significantly enhance long-term individual well-being, reduce cost of healthcare, improve our understanding of pathology, associated sensor markers and prognoses, characterize the efficacy of drugs and identify adverse effects and interactions, and to enable a broad class of new data-driven studies. Architecting the proposed system poses significant challenges stemming from the heterogeneity of sensor devices and associated quality of data, diversity of populations and underlying pathologies, disparate drug regimes and responses, and complexity of the underlying analytics problems.
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Undergraduate course, University of Asia Pacific, Department of Electrical Engineering, 2009
I taught Microprocessors and for junior students and also was the instructor for the lab testings for the course.
Undergraduate course, Marquette University, Department of Mathemtatics, Statistics, and Computer Science, 2010
I was a teaching assistant for Calculus I, II and III for eight semesters between 2010 and 2015 at Marquette University.
Undergraduate course, Marquette University, Department of Mathemtatics, Statistics, and Computer Science, 2011
I taught Data Structures to Sophomores. Topics included, data structures such as trees, heaps, hash functions, and search algorithms.
Mentoring, Purdue University, 2020