Driven by a desire to forge his own path, Arun George Zachariah is building a professional life based on carefully considered experiences in both research and industry.
From academia, Zachariah has honed his deep analysis skills and intellectual curiosity, and he has flourished in the freedom it offers to explore solutions without inhibiting constraints. Industry has taught him more grounded yet equally essential skills, including how to scale ideas, collaborate across teams, and couple research with its real-world impact.
Today, Zachariah is a software engineering manager with Nvidia’s TAO Toolkit team; he’s also one of Computing’s Top 30 Early Career Professionals for 2024.
In the following Q&A, Zachariah describes:
- How, despite his love for programming, he chose an unexpected path for his undergraduate studies—and it later proved invaluable
- The ways in which moving between industry and academia has helped him to define career fulfilment in broader ways
- Why the technical obstacles he faced during his PhD research were easier to manage than the personal challenges, which provoked thought and growth at deeper levels—and had deeper payoffs
- The pivotal advice he offers as a mentor, which can also help individuals and teams thrive in our rapidly evolving world
- Which essential qualities he cites as being key to building a successful career
What initially sparked your interest in computer science and technology? How did your early education shape your career path?
My fascination with computers began at an early age when I was first introduced to programming through Logo. Seeing simple commands bring a turtle to life on the screen sparked a sense of curiosity that has never faded. As I progressed through school, I had the privilege of learning C and C++ from some truly inspiring teachers who made programming feel like both an intellectual challenge and an exciting puzzle to solve. These early experiences reinforced my passion for technology and problem-solving.
Despite my love for programming, I chose not to pursue a formal degree in computer science right away. Instead, I wanted to develop a deeper understanding of the fundamentals that power computing systems, which led me to study electrical and electronics engineering during my undergraduate years. This decision gave me a strong foundation in hardware, embedded systems, and computational theory, which later proved invaluable when I transitioned fully into the world of computer science.
Even though I was eager to pursue higher education in computer science, I wanted to first gain practical experience and understand how technology is applied in real-world scenarios. This approach allowed me to bridge the gap between theory and application, eventually leading me to research and advanced studies in computer science. Looking back, my early education not only shaped my technical foundation but also instilled in me a mindset of continuous learning and interdisciplinary thinking—something that continues to guide my career today.
What were some of the biggest challenges you faced during your PhD research—particularly with your dissertation on large-scale image and video retrieval? How did you overcome these challenges?
During my PhD, the research itself was an exciting and deeply rewarding journey. Like any researcher, I encountered roadblocks, dead ends, and unexpected challenges, but I always saw them as part of the process—an opportunity to refine my ideas and push the boundaries of what was possible. Overcoming these hurdles required persistence, creativity, and a willingness to embrace failure as a steppingstone to progress.
However, the biggest challenges I faced were not just technical, but personal. The PhD journey can be isolating at times, requiring immense dedication while the world around you seems to be moving at a different pace. It was a period of self-discovery, where I had to learn to stay grounded in my purpose, trust the process, and find motivation even when the path ahead felt uncertain. There were moments when I questioned my choices, but I reminded myself that growth often comes through discomfort, and that perseverance would eventually lead me to where I wanted to be.
What helped me navigate these challenges was building a strong support system, mentors who offered guidance, peers who shared the journey, and small victories that reinforced my belief in the work I was doing. I also learned the importance of seeing the bigger picture, understanding that struggles are temporary and that the skills, resilience, and mindset developed during difficult times are what truly shape a successful career.
Looking back, I see those challenges not as setbacks, but as formative experiences that made me more adaptable, empathetic, and determined. They shaped not only my approach to research but also how I mentor and support others on their own journeys. To those aspiring to pursue a PhD or a career in research, I would say this: Trust the process, stay curious, and remember that every challenge you overcome adds to the depth of your journey.
Having worked in industry and academia, how do the two environments compare? What unique skills or perspectives have you gained from each?
Working in both industry and academia has given me the opportunity to experience two distinct yet complementary environments, each offering unique challenges and growth opportunities.
I began my career as a systems engineer at Infosys, where I gained a strong foundation in developing scalable solutions, collaborating with cross-functional teams, and understanding how technology translates into real-world products. Industry taught me the importance of efficiency, teamwork, and delivering results within deadlines, often with a strong focus on business impact. Working in a fast-paced environment reinforced the value of structured problem-solving and adaptability, as decisions were driven by real-world constraints and customer needs.
Over time, I became more interested in exploring the deeper technical challenges behind the technologies I worked on. This curiosity led me to pursue a PhD, which shifted my perspective in many ways. Academia offered the freedom to explore open-ended research problems, develop new ideas, and contribute to fundamental advancements in my field. Unlike industry—where success is often measured by product delivery—research was about discovering new knowledge, experimenting with innovative solutions, and pushing the boundaries of what was possible. I learned to navigate ambiguity, think critically, and approach problems with a long-term vision.
During my PhD, I had the opportunity to collaborate and intern at multiple companies, each offering a unique perspective on how research translates into real-world applications. These experiences reinforced how cutting-edge ideas are shaped by practical constraints, business needs, and scalability challenges. Working in different environments allowed me to see firsthand how companies, both large and small, invest in innovation while navigating real-world complexities.
After completing my PhD, I transitioned back to industry and joined NVIDIA, where I now leverage both my research expertise and industry experience. The shift felt natural; my time in academia had equipped me with the ability to deeply analyze problems, work independently, and explore innovative solutions without immediate constraints. At the same time, my prior industry experience helped me understand how to scale ideas, collaborate across teams, and align research with real-world impact.
Having worked in both environments, I’ve come to appreciate the strengths of each. Academia fosters intellectual curiosity and the pursuit of knowledge, while industry provides the structure and resources to turn those ideas into impactful products. For me, moving between these worlds has been incredibly rewarding, as each experience has enriched the other. It has reinforced the idea that technical careers don’t have to follow a single path. Sometimes the most fulfilling journeys are the ones that bridge multiple domains, combining deep research with real-world application.
As a mentor in programs such as Global Mentorship Initiative and KaggleX BIPOC Mentorship Program, what advice do you give people looking to have an impact in the tech industry?
As a mentor, I have had the privilege of guiding students and professionals from diverse backgrounds as they navigate their careers in the tech industry. One of the key pieces of advice I share is the importance of continuous learning. Technology evolves rapidly, and staying relevant requires not just keeping up with trends but also developing a mindset of lifelong learning, whether through formal education, self-driven projects, or active participation in research communities.
Another crucial aspect is building a strong foundation in problem-solving and critical thinking. Mastering specific tools and technologies is valuable, but the ability to think analytically and adapt to new challenges is what truly sets professionals apart. I encourage mentees to go beyond surface-level knowledge, engage in hands-on projects, and explore how different domains intersect with technology.
Networking and collaboration also play a significant role in career growth. I emphasize the importance of engaging with the community, whether through contributing to open-source projects, participating in conferences, or joining mentorship programs. Meaningful connections can open doors to new opportunities, spark collaborations, and provide guidance at pivotal moments.
Lastly, I remind professionals that success in tech is not just about technical expertise but also about resilience and adaptability. Many aspiring professionals feel imposter syndrome or hesitate to take risks, but the most impactful careers are built by those who embrace challenges, learn from failures, and remain open to new experiences. The tech industry thrives on innovation, and those who are willing to step out of their comfort zones and keep pushing forward will undoubtedly leave their mark.
Through mentorship, I aim to instill confidence, encourage curiosity, and help professionals build a career that aligns with both their skills and passions. Seeing mentees grow and make meaningful contributions to the field is one of the most rewarding aspects of being involved in these mentorship programs.
How do you balance your responsibilities as a software engineering manager at NVIDIA with your ongoing research and contributions to academic conferences and journals?
Balancing these responsibilities requires a blend of strategic prioritization, collaboration, and a deep passion for both industry and academia. At NVIDIA, I am fortunate to be part of a culture that fosters an environment in which employees can do their life’s work; this allows me to align my research interests with industry-driven innovation.
In my role, I focus on leading teams to develop cutting-edge solutions while also creating space for exploration and learning. I encourage my team to think beyond immediate deliverables and engage with the broader research community—this not only drives innovation, but it also strengthens our technical foundation. By fostering a research-driven mindset, I ensure that the work we do in industry has a lasting impact, both in real-world applications and academic discourse.
Time management also plays a crucial role in balancing these commitments. I integrate research into my workflow by identifying synergies between ongoing projects and emerging challenges in academia. Additionally, I stay actively involved in conferences and journals by reviewing papers, collaborating with researchers, and mentoring others in their research pursuits. This allows me to contribute meaningfully without compromising my leadership responsibilities.
Ultimately, I see my dual engagement in industry and academia as complementary rather than competing priorities. Industry provides real-world challenges that drive meaningful research questions, while academic contributions help advance the field and bring fresh perspectives back into industry. By leveraging the strengths of both worlds, I can stay at the forefront of technological advancements while also mentoring and inspiring the next generation of researchers and engineers.
What are your long-term career goals, and how do you plan to continue contributing to the field of computer science and technology?
My long-term career goals are driven by a deep passion for computer science and a desire to contribute meaningfully to both industry and academia. I want to continue pushing the boundaries of technology, working on cutting-edge research that not only advances the field but also has real-world impact. Whether through innovation in industry or collaboration with academic institutions, I aim to be at the intersection of research and practical application, ensuring that groundbreaking ideas translate into tangible solutions.
Beyond technical contributions, I strongly believe in giving back to the research community. Throughout my career, I have benefited from the guidance of mentors and the support of a collaborative academic environment, and I want to create similar opportunities for the next generation of researchers and engineers. Actively participating in conferences, reviewing papers, and collaborating on research projects are ways I plan to stay engaged with the broader academic community.
Additionally, I am passionate about mentoring and teaching. I find great fulfillment in guiding students and early-career professionals, helping them navigate challenges, develop technical expertise, and cultivate a research mindset. Whether through formal teaching, mentorship programs, or industry collaborations, I want to inspire and support others in their journey, fostering an environment where innovation and learning thrive.
Looking ahead, I see my career as a continuous journey of exploration, impact, and mentorship. By staying actively involved in research, bridging the gap between academia and industry, and nurturing the next generation of computer scientists, I hope to make lasting contributions to the field of computer science and technology.
Bio: Arun George Zachariah
Arun George Zachariah is a software engineering manager with Nvidia’s TAO Toolkit team, where he oversees end-to-end planning and execution of TAO releases. His focus is on ensuring that his team of software developers and deep learning engineers meet the highest standards of reliability, security, transparency, and ethical practices – particularly regarding trustworthiness – as they develop and deploy AI technologies.
Zachariah received his PhD in computer science from the University of Missouri-Columbia in 2022 under Praveen Rao’s guidance. As part of the MU College of Engineering’s Scalable Data Science (SDS) Lab, Zachariah leveraged his AI and cluster computing expertise to contribute to solving challenging problems in the energy and healthcare domains, including sustainable housing design, genomic analysis, and cancer cell detection in histopathology images.
In summer 2021, he was an intern at Arm Inc, where he automated and optimized complex 5G system workloads on multicore Arm processors. Prior to starting his PhD, Zachariah worked as a technology analyst at Infosys Technologies, a global leader in software development.
Dig Deeper
To find out more about Zachariah’s work and research,
Each week over the next few months, Tech News will highlight different Top 30 honorees. For a full list, see Computing’s Top 30 Early Career Professionals for 2024.
In addition to Computing’s Top 30, IEEE Computer Society offers many other awards; to read
about the honors and the honorees—and perhaps nominate an impactful professional in your life—visit the IEEE CS Awards page.
