Dr Dipankar Sengupta
Qualifications:
July 2010 - March 2014: Ph.D., Jaypee University of Information Technology (JUIT), India [Thesis: Translational and High-End Computing of Clinical data in India]
July 2003 - June 2007: Bachelor of Technology (Bioinformatics), Jaypee University of Information Technology (JUIT), India
Professional Experience:
Aug. 2023 onwards: Senior Lecturer in Health Data Analytics, School of Life Sciences, University of Westminster, United Kingdom
Sep. 2021 - July 2023 onwards: Lecturer in Health Data Analytics, School of Life Sciences, University of Westminster, United Kingdom
Apr. 2020 – Sep. 2021: Teaching Associate (Bioinformatics and Computational Biology), PGJCCR, Queen’s University Belfast, United Kingdom
Jan. 2018 - Mar. 2020: Postdoctoral Research Fellow, PGJCCR, Queen’s University Belfast, United Kingdom
Aug. 2014 - Dec. 2017: Postdoctoral Researcher and Teaching Assistant, Artificial Intelligence Lab, Vrije Universiteit Brussels (VUB), Belgium
Apr. 2014 -July 2014: Assistant Professor, Jaypee University of Information Technology (JUIT), India
May 2010 -Mar. 2014: Associate Lecturer, Jaypee University of Information Technology (JUIT), India
Sep. 2007 - Apr. 2010: Associate Consultant (Technology), Publicis Sapient, India
With an undergraduate and postgraduate background in Bioinformatics, I have ~3 years of industrial and ~8 years of post-doctoral research experience in business intelligence, data science, machine learning, relational databases, and software development as applied to clinical and life sciences, with 28 peer-reviewed abstracts, book chapters, and papers in journals/conference proceedings, including 14 as first or senior author. My work has spanned both academic and industrial sectors.
My research aspires to unveil the precision medicine intricacies like patient stratification, tools for diagnosis/prognosis (temporal computing), and challenges like availability of labeled data, etc. using data science, machine learning, and other computational approaches.
I also have an interest in addressing challenges in precision nutrition, urban health, sustainable development, etc. via technological solutions like machine learning.
