Q5: How do you approach managing complex data sets and do you think real-time data visualization can significantly improve the process?
Shailesh Chauhan:
I believe that managing complex data sets requires a structured approach to ensure both efficiency and accuracy in obtaining actionable insights. I have always been deeply interested in data visualization and its powerful implications for problem solving, but my interest in data visualization took concrete form with Kepler.gl, an open source geospatial tool that I developed at Uber for real-time visualization of complex data sets. .
Kepler.gl has enabled urban planners, policy makers and data scientists to identify patterns and trends that might otherwise have been overlooked, bringing data to life. This tool has enabled data-informed decision-making in sectors such as urban planning, logistics, UX improvement and route optimization. I presented this work at the Strata conference in London, and it has since been used to better understand transport and urban infrastructure.
I believe that if solutions like Kepler.gl were widely implemented, they could redefine industry standards. By offering accessible and actionable insights from complex spatial data, these tools could set new benchmarks in data accessibility, visualization and strategic decision-making, creating a framework for meaningful change across various sectors.
Q6: Given your deep technical expertise and experience at various companies, what key insights or thought leadership would you impart to aspiring AI professionals looking to shape the future of this field?
Shailesh Chauhan:
Besides regular technical work, mentoring is an integral part of my job. I believe it’s not just about teaching technical skills, but also fostering a mindset that encourages continuous learning and innovation. I often share my knowledge with my peers and junior colleagues, and I make it a point to mentor emerging professionals and startups, offering them advice on product strategy, career development, and how to navigate the rapidly evolving landscape of AI and data science.
I also speak to wider audiences through speaking engagements, such as the AWS On Air and ThoughtSpot webinars, where I discuss key topics such as natural language processing (NLP) and relational search. It’s rewarding to share my experiences and help others recognize the potential of machine learning to solve real-world problems.
The future of AI and data is incredibly bright. As technology advances, AI will be increasingly integrated into daily life, enabling businesses to make smarter and faster decisions. The rapid evolution of AI brings new challenges and endless possibilities.
My advice to newcomers to the field is to stay curious, embrace continuous learning, and focus on solving practical problems. AI has the potential to transform industries and solve significant challenges, and the next generation of leaders will play a critical role in driving this change.
