With over 17 years of Industry Experience in the field of Data Science, Dr. Sheela has addressed business problems in domains like Industry 4.0, Health Care, Smart city, etc., and provided innovative Machine Learning solutions. Built a team of Data Scientists, Big Data Architects, Visualization and Project Management for enabling end-to-end solution. Prior to joining Kyndryl, Dr. Sheela worked as an Expert – Data Science, Bosch; Senior Research Scientist and Scientist at the Research Centers of Infosys and General Motors respectively. 

Can you take us through your AI journey?  

My tryst with AI started in my engineering days with an interest in operations research and statistics that grew significantly and strengthened over time. Subsequently, during my Masters and PhD in the USA (The University of Texas and Arlington), I delved deeper into data science, machine learning, and text mining.  

This academic foundation provided a strong springboard for my entry into the industry. Over the past 17+ years, my expertise has revolved predominantly around Machine Learning, a field in which I've thrived. I have focused on providing specialized solutions for manufacturing challenges, where I can offer invaluable insights into adopting automation.   

AI is a field that never ceases to evolve, and I relish the opportunity to stay at the forefront. I find immense satisfaction in understanding the technical aspects and the broader industrial applications.  

Can you discuss your role in the collaboration between Kyndryl and IIT Tirupati for advancing AI-enabled 3D printing in the Manufacturing Sector? What are the real-world applications for this?  

The collaboration between Kyndryl and IIT Tirupati is a highly synergistic venture. I was familiar with the innovative work at IIT Tirupati before joining Kyndryl, and after joining, I saw a strong alignment in our goals for innovation. When I proposed this collaboration, the organization was very supportive, and I've been the technical lead for the project. Over the past year, we've worked closely with the faculty at IIT Tirupati, leveraging their well-equipped infrastructure, particularly in additive manufacturing using robotic arms.  

What sets this project apart is our unique approach, using welding as a method for 3D printing. This represents a novel and more cost-effective method compared to traditional laser-based techniques.  

Currently, welding-based 3D printing is primarily in the academic sector, where research is being conducted to build prototype models in manufacturing and healthcare domains. Our contribution lies in the AI aspect. We've developed algorithms that can identify defects in real-time, not just on the surface but also within the weld. This significant advancement allows us to detect potential flaws below the surface without dismantling or traditional scanning methods.  

In practical terms, this technology has a wide range of applications. For instance, in healthcare, we can create customized prototypes for patients who require specific implants or replacements. Additionally, this technology can be used in manufacturing to test components before full-scale production, ensuring they meet the necessary standards.  

Overall, this collaboration represents a significant step forward in applying AI-enabled 3D printing in the manufacturing sector, focusing on efficiency, cost-effectiveness, and quality assurance.  

Can you tell us how Kyndryl is helping enterprises adopt AI and automation? How does Kyndryl ensure the safe and responsible use of AI?  

Kyndryl seamlessly incorporates AI and automation into solutions across diverse domains, ensuring that innovation is integral to our offerings. Our focus is not only on intelligence but also on speed and accuracy. This integrated approach ensures that our solutions incorporate cutting-edge technology and deliver results swiftly and reliably. We refine our solutions with each new customer engagement, striving to provide increasingly effective outcomes. This iterative learning process allows us to enhance the value we bring to our customers continuously.  

In August '23, Kyndryl launched an AI-readiness program to provide customers with end-to-end services to help them responsibly explore and adopt GenAI solutions.   

In customer service engagements, especially in ticket resolution, we employ AI to expedite the categorization process, balancing automation with necessary manual tasks. This allows us to progressively break down complex issues into manageable segments, leveraging AI as a vital tool. We also offer customers Kyndryl Bridge, our open integration services platform powered by AI, to accelerate automation, drive efficiency, and enhance security and resiliency. 

With the advent of Generative AI, there is a rising uncertainty about the future of women in AI. What do you want to say to the women who worry about their future in emerging tech?  

Technology is gender-neutral and has an overall positive impact, as people recognize the importance of intelligence and adaptability over routine tasks. The world is embracing multiple facets of technology, such as machine learning and computer vision, to solve diverse business challenges.   

I feel that the support for women in the Indian tech industry has improved over the years. Academically also, there is a strong presence of women in technology-related programs, and more women are pursuing advanced degrees like PhDs compared to earlier times.   

More generally, Generative AI, like ChatGPT and AI, has vast potential, especially when integrated into an organization's data strategy.   

A robust and agile data strategy is vital for effectively leveraging AI insights at scale. Continuous feeding of new data is necessary for its sustained learning and relevance. To scale AI, a robust data strategy forms the foundation. AI holds immense promise, but proper scaling and integration into an organization's ecosystem are critical. Connecting it to applications and data sources maximizes its potential and impact.  

Several researchers today remark AI as a catalyst for the digital divide. In such a context, do you believe that AI might widen gender disparity, posing a challenge for women in AI?  

AI is a powerful tool, so applying it responsibly and monitoring its use is important. This will help to regulate the usage, so it is beneficial and can be used for good in the world, like supporting the creation of a more equitable and inclusive society.  

AI will positively impact society, regardless of factors like gender, race, etc., like the adoption of the internet or the invention of the printing press. We must ensure the elimination of bias while building AI models. Ultimately, AI is just a tool, and humans can achieve far better results with the right tools than without. 

In this rapidly changing world, how can one stay updated? Do you have any tips for young women aspiring for a successful career in AI, ML, Data science, etc.?   

There is no shortcut to sustainable growth, whether in achieving your desired fitness levels, mastering a skill, or gaining expertise in any other field. To stay updated, one must be proactive in their learning and development.   

Accessibility to information has increased significantly, and tracking and learning about the latest news developments, discussions and innovations in the field can be quite helpful. As they say, tiny drops can make an ocean. Similarly, devoting realistically possible time for an individual towards learning and keeping track of the latest developments and industry opinions in this constantly evolving field can help build significant knowledge and awareness. I still spend more than a couple of hours reading and consuming information daily.  

Some tips for young women aspiring for a successful career in AI, ML, and data science:  

• Build a strong foundation in math and computer science: AI, ML, and data science are all technical fields, so it is important to have a good foundation in math and computer science.  
• Get involved in extracurricular activities: Many extracurricular activities can help you develop your AI, ML, and data science skills. For example, you can participate in hackathons or work on independent AI projects.  
• Don't be afraid to ask for help: If you are struggling to learn a new skill or concept, don't ask for help from a mentor, classmate, or colleague. There are also many online forums and communities where you can ask questions and get help from other professionals in a similar field. 

Does sustainable AI influence sectors such as energy and healthcare?  

For us, sustainability is in every solution. When we design a solution, we ensure that sustainability flows within the solution and is not an exclusive extra. Yes, sustainable AI can influence sectors such as energy and healthcare in several ways.  

AI can optimize energy use in buildings, factories, and other facilities. For example, AI can control heating and cooling systems, turn off lights and appliances when not in use, and predict energy demand so that power grids can be operated more efficiently.  

AI can help improve the performance of renewable energy technologies, such as solar panels and wind turbines. For example, AI can optimize the placement of renewable energy infrastructure.   

AI can improve the efficiency of healthcare delivery in several ways. For example, AI can support diagnosing diseases. It can also help reduce healthcare costs by automating tasks currently performed by humans, such as scheduling appointments and reviewing medical records.  

Can you analyze the impact of generative AI in your field of expertise?  

Generative AI is revolutionizing the world and significantly impacts the field of AI. It has enabled researchers to speed up their process of learning concepts, old or new, so they can spend more time conducting experiments and testing new solutions that can drive innovation. In conclusion, generative AI has boosted efficiency and productivity, enabling researchers and innovators to spend more time on work that can drive business impact. However, it is important to note that the power of AI tools lies in the hands of the user. It is up to us to utilize these capabilities responsibly and solve practical problems.