Dr Md Mostafa Kamal Sarker, the Head of AI at Technovative Solutions Ltd (TVS), recently spoke to students and early-career professionals in an exclusive webinar hosted by the SUST Data Science Club.
Dr Sarker, one of the alumni of Shahjalal University of Science and Technology (SUST), has built a career at the intersection of academic research and applied artificial intelligence, particularly in the healthcare sector.
The session covered his professional trajectory, key insights for those entering the field, and reflections on the evolving AI landscape.
Dr Sarker began his academic career in Physics at SUST, where his interest in data and computing first emerged. His subsequent path, from early research in machine learning to leadership roles in biomedical AI, has been shaped by many formative experiences.
We recently had the opportunity to interview Dr Sarker, asking him about his experience and thoughts from the event. Let’s take a closer look at Dr Mostafa Kamal Sarker’s journey into AI:
During the session, you discussed your journey from SUST to your current roles at the University of Oxford and Technovative Solutions. Could you briefly highlight what you believe were the most defining moments in that journey?
Dr Sarker: I shared my progression from undergraduate studies at SUST to my roles at Oxford and TVS. One defining realisation was that you can't jump directly into AI. You need a deep foundation in mathematics and programming. In your bachelor’s, start with the basics.
After that, during your master’s, focus on domain-specific implementation, algorithmic understanding, and more advanced programming. A PhD helps you overcome domain challenges and build expertise in applied research.
I also advised students to engage in open-source challenges like Kaggle or the MICCAI Challenge to sharpen their skills. Reading scientific papers and learning to write and publish your research enriches your portfolio significantly. Additionally, choosing a target domain early allows for more focused and impactful work.
Finally, my transition from Oxford to TVS was largely driven by the exciting AI challenges TVS is addressing and its strong vision for next-generation AI solution development.
Q: What were some of the most engaging or memorable questions or interactions you had with attendees during the webinar?
Dr Sarker: One of the most frequently asked questions was what to study to pursue a career in AI. My advice was to start with the basics: mathematics, programming, and practical problem-solving. Students often asked which courses or areas to focus on. I emphasised choosing a domain of interest and mastering it.
AI is much broader than it was when we started, and trying to learn everything is neither practical nor efficient. Choose a domain and explore further, while other domains can remain as supporting knowledge.
Q: For students and early-career professionals aspiring to work in AI and data science, what are the most critical skills or areas of focus you would recommend?
Dr Sarker: In addition to strong technical foundations, you must develop problem-solving capabilities. You need to move beyond just using AI tools; you need to engineer them. That means understanding how algorithms work, being able to code from scratch, and knowing how to evaluate and improve models.
Learning to think critically and constructively is just as important as technical knowledge. AI should be approached as a tool to augment human capabilities, not replace them.
Q: In your view, what emerging trends in AI and machine learning should young professionals start paying closer attention to?
Dr Sarker: One major trend is the rise of Agentic AI. Traditionally, AI models were built to solve a single task. Now, we’re moving toward multi-tasking agents: AI systems capable of performing a variety of tasks using a single model, making decisions based on multiple parameters.
For example, think of a healthcare application. Previously, a model might only detect fever. Now, we aim to create agents that can analyse a wide set of diagnostic data, just like a human doctor. This approach increases effectiveness and applicability across domains. Agentic AI represents a fundamental shift and is the future of intelligent systems.
Q: You mentioned the importance of bridging academic knowledge with industry practices. Could you elaborate on how students can better prepare for this transition?
Dr Sarker: Absolutely. In general, academia focuses on theoretical development, such as publishing papers, teaching, and mentoring.
On the other hand, industry is about implementation and delivering usable solutions. To transition effectively, students should engage in translational work, transforming academic research into applicable technologies. For instance, if you publish a paper on a novel algorithm, also think about how it can be used in a real-world application. That kind of bridge-building is crucial for making an impact in industry and for expanding the practical value of your research.
Q: As someone who has maintained strong ties with SUST, how do you feel about engaging with current students and contributing to events like this?
Dr Sarker: I have a strong sense of pride in staying connected to SUST. It’s inspiring to see the growth and enthusiasm of the current students. Events like AI hackathons are fantastic platforms for engagement. TVS often participates, not only to support these initiatives but also to recruit emerging AI talent.
Additionally, university clubs such as the Career Club and Science Club are doing commendable work in drawing attention from organisations like TVS. It’s a mutually beneficial relationship and something I deeply value.
Q: Is there any message or advice you would like to leave for our readers who may have missed the event?
Dr Sarker: My message to anyone who may have missed the event is simple: start from scratch and don’t take shortcuts.
Remember, true AI engineering is not just about prompting tools like ChatGPT—it’s about understanding how those tools work underneath.
Learn the fundamentals of programming, math, and algorithms. Choose a domain, and build solutions that solve real problems. Remember, AI is a tool to support humans, not a replacement. Ethical and responsible AI is crucial, especially as we advance toward Industry 5.0.
Finally, I’d like to share a quote from one of my professors at Oxford: "AI is like nuclear energy. You can either use it to build sustainable solutions or to create destructive power. The choice is ours."
About Dr. Md. Mostafa Kamal Sarker
Dr. Md. Mostafa Kamal Sarker, PhD, is currently the Head of AI at Technovative Solutions Ltd. He is also a Visiting Fellow at the University of Oxford.
Dr. Sarker is a renowned AI research scientist whose work is transforming healthcare through advanced machine learning and biomedical technologies. His research spans clinical AI, computer vision, health informatics, and digital healthcare. With nearly 40 peer-reviewed publications, he is recognised for both his technical expertise and his leadership in the global AI community.
