Naina Dandona is a Software Architect at Cadence. She brings over 20 years of experience in software architecture and development, specifically in the electronic design automation (EDA) space. Naina is at the forefront of innovation in the EDA Library creation domain. Her team is pioneering using artificial intelligence (AI) to revolutionize the process, reducing library creation time from days to minutes. They're achieving this through a Machine Learning-based recommendation system that automates a significant portion of the workload.

Can you tell us about your AI journey? 

I am a Software Architect at Cadence. I have around 20 years of experience in software architecture and development, specifically in the electronic design automation (EDA) space. I am leading a team that builds Library Solutions for EDA Library models. 

We have been working on various projects to boost the productivity of librarians in the EDA industry, including AI ML-based solutions to accelerate library creation time from days to minutes. 

What is your area of expertise in AI, and what made you choose it?

My main areas of expertise are Exploratory Data Analysis and Machine Learning Algorithms. My primary focus lies in AI-powered library solutions, emphasizing Exploratory Data Analysis integrated with Machine Learning. This strategy facilitates comprehensive analysis and visualization of library data, allowing us to identify key characteristics, uncover patterns, and establish effective relationships among variables.

How important do you think skilling and upskilling are in a country like India? 

AI is rapidly transforming various industries globally. For India to stay competitive and participate actively in the global economy, it's crucial to have a skilled workforce capable of leveraging and developing AI technologies. 

There is a substantial gap between the demand for AI skills and the available talent pool in India. Skilling and upskilling initiatives can help bridge this gap by preparing more individuals for AI research, development, implementation, and management roles.

Describe some challenges you have faced in reaching where you are now.  

I feel privileged to be part of Cadence, a company rooted in R&D where everyone is treated equally, regardless of gender, ethnicity, physical ability, etc. Cadence has always prioritized innovation to maintain leadership in the industry. 

Cadence is highly supportive of its employees, extending assistance during personal challenges, which has motivated me to stay resilient during challenging times both professionally and personally. 

I still remember the time when I had just returned from maternity leave, and laptops were not provided individually for work. My group enabled me to work a few days a week from home by providing the pool laptop. My colleagues were so cooperative in helping me get back to work so quickly. 

In what direction should companies in the AI sphere move to ensure more female participation and leadership? 

In general, implementing robust diversity, equity, and inclusion (DE&I) programs that specifically target gender diversity across the board is crucial. Creating a work environment that supports women, including flexible work arrangements, family-friendly policies, and zero-tolerance policies for discrimination and harassment, will ensure that women are able to bring their best selves to work every day. Promoting a culture of respect and inclusivity can enhance retention and career satisfaction among female employees.

Specific to AI, upskilling and re-skilling will help all employees, not just women, meet AI technology's challenges. While AI has been around for a while, its applications have recently exploded. They are changing so rapidly that anyone working with AI technologies must keep sharpening their skills.

In a country like India, where societal constraints bind women, how do you think that they should break the stereotypes? 

I want to acknowledge that women have already made great strides in breaking stereotypes. So many more women are in the workforce today because women in the previous generation broke stereotypes and paved the way for us in the next generation. I hope we do the same for today's young girls and women. 

There is, of course, much more work to be done in this area. From a company standpoint, providing tailored training and skill development programs specifically for women in STEM and AI to equip them with technical expertise and confidence will help keep women in the workforce after marriage and childbirth.

The most significant impetus for breaking stereotypes lies with our male allies. Companies need to educate stakeholders, especially men, about unconscious biases and stereotypes that affect women and implement policies to mitigate bias in hiring, promotions, and project assignments.

Of course, highlighting successful women who have broken stereotypes and establishing mentorship programs to inspire and support aspiring women are motivational for women at all stages of their careers.

What are your words of wisdom to young girls who wish to build careers in AI?

Dream big, embrace continuous learning (AI is constantly evolving; stay curious, keep learning and unlearning, and adapt to new technologies and ideas), Demonstrate resilience (Challenges are inevitable in any career; stay strong in adversity and see them as chances to learn and develop), Foster networking and collaboration, and above all believe in yourself.

Can you tell us something about the projects you are handling and your plans in the pipeline?

We work in the domain of EDA, focusing more on productivity boosters for Librarians where AI can augment the library creation task. We are working on a Machine Learning-based recommendation system that will automate a significant portion of the workload for Librarians.