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Global Chief AI Officer | Leading AI Organization | Modern Healthcare 40 under 40
At GE HealthCare, my leadership in AI has been recognized as top-tier, translating into strategic advancements in medical technology. Our team's focus on integrating artificial intelligence into device development and operations has significantly improved patient care and operational efficiency. Transitioning from Amazon, where I spearheaded generative AI and machine learning initiatives, I now harness these competencies to innovate within the healthcare sector. Our commitment at GE HealthCare is to leverage cutting-edge AI to deliver the most effective digital solutions for patient outcomes.
Georgia Institute of Technology
Master Computational Science & Engineering, Machine Learning
January 1, 2014 – January 1, 2015
Indian Institute of Technology, Ropar
Ropar B.Tech, Computer Science and Engineering
January 1, 2008 – January 1, 2012
GE HealthCare
Chief AI Officer
April 1, 2023 – Present
Seattle, Washington, United States
Amazon
Head of Applied Science - Generative AI
September 1, 2022 – April 1, 2023
Amazon
Science Manager
January 1, 2019 – August 1, 2022
Amazon
Senior ML Scientist and Lead Scientist at Amazon Comprehend Medical
October 1, 2018 – January 1, 2019
Amazon
NLP Scientist (Deep Learning & AI)
April 1, 2017 – October 1, 2018
Yik Yak, Inc.
Senior Machine Intelligence(Deep Learning & AI) Engineer
June 1, 2016 – April 1, 2017
Atlanta
Yik Yak, Inc.
Machine Intelligence(Deep Learning & AI) Engineer
February 1, 2016 – June 1, 2016
Atlanta
Deep Learning Summer School, Univ of Montreal
Graduate Student
August 1, 2015 – August 1, 2015
Montreal, Canada Area
Microsoft
Data Scientist - Machine Learning - Data & Fundamentals
May 1, 2015 – August 1, 2015
Greater Seattle Area
Georgia Institute of Technology
Graduate Teaching Assistant - Machine Learning
January 1, 2015 – May 1, 2015
Georgia Institute of Technology
Graduate Research Assistant - NLP (Under Dr. Jacob Eisenstein)
August 1, 2014 – February 1, 2016
Georgia Institute of Technology
Graduate Student
August 1, 2014 – December 1, 2015
Edifecs
Software Engineer - IC2
April 1, 2014 – August 1, 2014
Edifecs
Associate Software Developer
June 1, 2012 – March 1, 2014
Microsoft
Software Development Intern at Microsoft Corporation
May 1, 2011 – July 1, 2011
Hyderabad Area, India
Cultural Fit Analysis
The candidate has a strong background in large, established tech companies (Amazon, Microsoft) and healthcare (GE HealthCare, Edifecs), indicating a preference for structured environments and impactful projects. Their leadership roles suggest a drive for innovation and strategic influence. The transition from core software engineering to deep learning and AI demonstrates a continuous learning mindset. The breadth of experience across different domains (e.g., e-commerce, healthcare, social media) suggests adaptability, but the primary focus has been on large-scale enterprise and product-driven AI, which may align well with organizations seeking mature AI leadership. The lack of explicit project details outside of work descriptions makes it difficult to assess diversity of personal initiatives or open-source contributions, which could indicate a more corporate-focused cultural alignment.
Soft Skills & Operational Fit
The candidate's career progression from individual contributor to Chief AI Officer demonstrates strong leadership, strategic thinking, and the ability to manage complex technical organizations. Their experience at Amazon and GE HealthCare suggests adaptability to fast-paced, high-impact environments and a focus on delivering real-world AI solutions. The descriptions highlight collaboration with product and engineering partners, indicating good cross-functional communication and operational fit.