About
Rohit here. Currently, working as Founding Member & Chief Commercial Officer at Qure.ai. Qure.ai focuses on AI for medical imaging and is currently being used in 50+ countries, 2000+ provider sites globally. Within Qure, I am currently responsible for business development and strategy for existing business verticals. My learnings are primarily around entering new segments for a B2B business and scalign them. I will try and consolidate my learnings on this blog. Ironaically, this is what I have been doing day-in day-out for since 2018.
I have also done a TEDX talk in the meantime talking about the journey of Qure and the problem we’re trying to solve. Also, in the intervenign years, I got a chance to mentor and coach 200+ students as a faculty at GreyAtom. In collaboration with GreyAtom, we put out a series of YouTube lectures on machine learning and AI which could help anyone get started with data science.
From 2019-2021, I worked with Google Developer Expert Group for machine learning to mentor/coach budding data scientists across the globe to learn data science. Have travelled to 20+ conferences as part of the role to meet and give talks about interesting aspects of explainability of machine learning.
As teaching machine learning very close to my heart, I also happened to co-author a book titled Big Data Analytics: Systems, Algorithms, Applications along with Prof. Prabhu and his student (it was a lot of effort writing even few chapters!)
A 2014 graduate from IIT Bombay, I had worked Nomura right after graduation. Before Qure, I had worked as Data Scientist for ListUp, a P2P buy-sell platform and as Freelance Data Scientist for New York based startup Data Science Labs and couple of other startups.
Early on in Qure I used to mostly on R&D areas in computer vision part of Deep Learning. In addition to vision, I also keenly follow developments in reinforcement learning (mostly related to trading strategies). Also, on weekends, I am mostly playing either playing tennis or at swimming pool. An avid Hindi music buff, I like to read on varied topics, and keep a tab on the newest breakthroughs. Hence, a varied lot of topics in the blog.
Patents
- Patent on Application of deep learning for medical imaging evaluation Link for the patent
Publications
- Research abstract with collaboration with Yale School of Cardiology on Advanced Analytics Improve Prognostication, Identify Distinct Subgroups of Heart Failure and Detect Heterogeneity in Response to Therapies in a Cohort of Heart Failure Patients accepted for oral presentation at
- American College of Cardiology Meeting ‘16, Washington DC, USA
- American Heart Association Annual Conference ‘16, New Orleans, USA
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Research abstract with collaboration with Yale School of Cardiology on Application of Machine Learning Methods for Prediction of Outcomes after Cardiac Transplantation: Insights from the UNOS Database accepted for oral presentation at American Heart Association Annual Conference ‘16, New Orleans, USA
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Research paper with collaboration with Yale School of Cardiology Variation in Practice Patterns and Outcomes Across UNOS Allocation Regions accepted for publication in Clinical Cardiology
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Research abstract on Automated detection and localisation of skull fractures from CT scans using deep learning accepted for scientific paper presentation at annual conference of European Society of Radiology (ECR) ‘18, Vienna, Austria
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Research abstract on Automatic detection of generalised cerebral atrophy using deep neural networks from head CT scans accepted for scientific paper presentation at annual conference of ECR’18, Vienna, Austria
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Research abstract on Automated detection of intra and extra-axial haemorrhages on CT brain images using deep neural networks accepted for scientific paper presentation at annual conference of ECR’18, Vienna, Austria
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Research abstract on Deep neural networks to identify and localize intracerebral hemorrhage and midline shift in CT scans of brain accepted for Scientific Poster and Alternate for Oral Presentations Status in annual Conference ‘17 by Radilogical Society of North America (RSNA)
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Co-authored part of Chapter on RegTech Investment & Compliance Spending in the upcoming The RegTECH Book by Wiley Publications, discussing Merits & Demerits of Shared Risk Engine along with the proposed architecture and scope for adavanced risk management using ML.
- Co-authored case study on Exploring Long-Term Relationships in Logistics Industry along with teaching note, published by McGraw Hill Education Pvt. Ltd. as part of the book Cases In Business Marketing