Director of AI Oversees the Deployment of AI Innovation

Name: Srikanth Thudumu

PhD: Artificial Intelligence, Swinburne University of Technology, 2021

What is your current job?

I am the Director of AI for the Institute of Applied Artificial Intelligence and Robotics (IAAIR) in Memphis, Tennessee.

I have several responsibilities within my role, including:

• Define the institute’s AI roadmap, priorities, and innovation agenda to address real-world challenges across industries.

• Oversee the design, development, and deployment of cutting-edge AI systems, ensuring scalability, robustness, and ethical alignment.

• Collaborate with industry, government, and academia to secure funding, co-develop solutions, and expand the institute’s impact.

• Establish frameworks for explainable, secure, and socially responsible AI, aligned with global standards and regulations.

What is your favorite thing about your job?

My favourite part of the job is engaging in deep conversations with industry experts—listening to their challenges, uncovering hidden gaps, and truly understanding the complexities they face. There’s something incredibly rewarding about connecting those real-world pain points with cutting-edge research. When I refer to a paper or concept I’ve been studying and explain how it directly applies to their problem, it often sparks this moment of clarity and excitement in their eyes. That spark—bridging theory and practice—is what drives me.

What is the most important skill you developed or experience you had during your PhD that now helps you in your current position?

The most important skill I developed during my PhD was critical thinking—learning how to approach complex problems from first principles, challenge assumptions, and rigorously validate solutions. This mindset has become foundational in my industry work, where off-the-shelf models rarely solve real-world problems without adaptation.

Whether I’m designing AI systems for defence, agriculture, or industrial settings, critical thinking allows me to navigate ambiguity, assess trade-offs, and make high-stakes technical decisions with confidence. It’s what enables me to go beyond theoretical research and deliver AI solutions that are not only innovative but also robust, ethical, and aligned with business and societal goals.

How did you build the skills necessary for your current role?

I built the skills necessary for my current role through a mix of hands-on research, interdisciplinary collaborations, and real-world problem solving. During my PhD and postdoc, I actively worked with industry partners like BAE Systems and the Australian Department of Defence, which taught me how to frame research in terms of impact and applicability. One of the most valuable skills I developed was the ability to translate complex research into practical solutions, putting everything in an industry context so that stakeholders could clearly see how AI could solve real problems.

Beyond academic training, working on applied projects, participating in industry-led workshops, and mentoring junior researchers also helped me bridge the gap between theory and deployment. These experiences shaped my ability to lead AI initiatives that are both scientifically sound and operationally relevant.

How did you find this position? What were the career steps you took to get to where you are now?

I found my current position quite unexpectedly. I was giving a talk on AI at the University of Melbourne, and in the audience was the person who would later become our Executive Director. He was impressed by my work and vision, and soon after, he offered me the opportunity to lead the institute. He also sponsored my move to the United States through an Extraordinary Ability (O-1) visa, which allowed me to take on this role and help shape the future of applied AI at the institute.

PhD graduate ➡️ Postdoc ➡️ Research Fellow ➡️ Sr Research Fellow ➡️ Director of AI

If someone is interested in a similar role, what would you recommend they start doing now to prepare?

The most important thing to build is constantly asking yourself: how can my research help solve real-world problems? Whether you're working on theoretical models or experimental systems, always try to frame your work in the context of real-world impact. This mindset not only sharpens your problem-solving skills but also makes your work more relevant to industry.

Engage with people outside academia—talk to practitioners, attend applied workshops, and seek collaborations where your research can be tested against actual challenges.

Why did you decide to not pursue a career in academia?

I didn’t see it as stepping away from academia, but more as extending its value into the real world. While I enjoyed academic research, I was naturally drawn to the challenge of applying that knowledge to solve real, tangible problems—whether in industry, government, or communities.

The decision came pretty easily for me. I realized I felt most energized when I could translate research into practical solutions and build systems that deliver real impact. Leading an applied AI institute lets me stay close to research while making sure it leads to meaningful, real-world outcomes.

What advice do you have for someone getting their PhD and looking to pursue a career outside of academia?

1. Think beyond citations—ask how your research can be used to solve real problems. That mindset shift is critical in industry.

2. Your ability to explain complex ideas clearly to business leaders, engineers, or policymakers will open more doors than technical jargon ever will.

3. Build industry exposure early. Intern, collaborate, or consult with industry partners during your PhD if possible. These experiences teach you how research is applied and valued outside academic circles.

4. Get comfortable turning ideas into usable tools, systems, or insights. Understanding the lifecycle from research to deployment is a huge advantage.

Most importantly, don’t view leaving academia as “leaving something behind”—see it as taking your skills where they can make a broader impact.

Are there any components of your identity you would like to share, including how they have impacted your journey?

My journey began with studying software engineering in India, followed by working in Singapore, and eventually transitioning into research in Australia. Starting my research career in Australia gave me a strong foundation in applied AI and exposed me to collaborative, interdisciplinary work. Being an international researcher has shaped how I think—it taught me to adapt across environments, communicate across disciplines, and approach problems with a global mindset.

Now working in the United States, I carry that experience with me as I lead AI initiatives that are both technically rigorous and socially meaningful. It’s also motivated me to mentor others from diverse backgrounds, especially those navigating unconventional paths into research and leadership.

And for those interested, what was your main area of research?

During my PhD, I focused on developing advanced techniques for anomaly detection in high-dimensional big data, identifying rare and meaningful patterns in complex, large-scale datasets. In my first postdoc, I was involved in a narrative visualization project, working on data integration and fusion in collaboration with BAE Systems. In my second postdoc, I worked on the development of a context-aware search engine for the Australian Department of Defence.