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About

placeholder Rohit here. Having fun in general through life, mostly.

Previously was Founding Member at Qure.ai doing all the fun things from 0-1 (building the algos as AI researcher till 2018) and then 1-100 (commercialise tech as CCO till 2024, doing 0-1 across multiple market verticals). Qure.ai focuses on AI for medical imaging and is currently being used in 80+ countries, 2000+ provider sites globally ~as of 2024. The two phases couldn’t have been more similar and yet so different. Getting to do zero to one every day - couldn’t have thanked my stars for being able to live that life! Looking to do again :)

I have also done a bunch of ‘fun’ things in the process till now

  • Got to learn sales, started by selling frugally (spamming, you say?) and then be able to build a full fledged first principles based sales process to launch from 0 to $XX M+ ARR in 2-3 years; across 5 market vertials (learning to lead commercial teams along the way - they work very differently from AI reasearch teams, haha!)

  • TEDX talk in the problem we’re trying to solve the meantime talking about the journey of Qure

  • 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.

  • Worked with Google Developer Expert Group for machine learning to mentor/coach budding data scientists across the globe (mostly Tensoerflow though :P)

  • 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!)

  • Got a chance to be Guest Lecturer at multiple places - like UpGrad, University of Mumbai etc. (I love teaching students)

  • Built a RL-based trading ‘agent’ in 2019 for trading on India stock markets with my buddies Sushant and Jayant - (the backtesting results looked much better than real-lfe results). Still, it ran good till pandemics of 2020 ruined it !

Fun Facts

  • I didn’t know how to code a single line in any language at the begining of 2016, forget anything about deep learning or even machine learning or data structures and algorithms. Story for another day :)

  • Now, I am pickleball bronze medalist for City of Sydney’s Annual Pickleball Champinoship (newest addition to fun things in life)

Patents

  1. Patent on Application of deep learning for medical imaging evaluation Link for the patent

Publications

It is an old listing - I can’t keep updating it - Google Scholars does a better job - check the link here

  1. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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)

  8. 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.

  9. 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