Thank you for the kind welcome. I am truly honored and very pleased to be in the midst of this august gathering—both on the stage and in front of me. More importantly, I am delighted to be in front of the young minds present today. I am also thankful to Professor Choudhury, who made my coming here possible through the invitation and the follow‑up communication. Thank you, ma’am.
I have a couple of thoughts I would like to share, simply because of my years of professional experience may offer some perspective. One thing that strikes me is the title of this conference. The fact that it is held every two years and continues to grow indicates the energy and enthusiasm of the organizers. I am sure the conference has seen many leaps in the quality of presentations and in the novelty of the work showcased. While I have only had the opportunity to look at the titles—not the full papers—I can easily imagine that the presentations must have been valuable.
Coming back to the title, it is very apt to say that “International Conference on Nascent Technologies” One thing that stands out about this conference name is its perennial relevance. It will never become outdated. As technology changes, the content of the conference may evolve, but the name will always remain appropriate. In contrast, a name tied to a specific domain—say “knowledge‑based systems”—might become less relevant over the decades. In that sense, this title is beautifully chosen. I congratulate the organizing committee and the advisory committee for selecting such a timeless name.
Let me take the liberty of sharing a few thoughts.
First, I want to talk about the way we write papers and technical documents. This is common advice I give to my own team of young researchers. When you step into a domain because you have read someone else’s work, it is important to acknowledge that earlier contribution. Giving credit to previous work is not optional. Literature surveys are a part of academic writing, but beyond that, proper citation is essential.
The second point I emphasize with my team is that if you want someone to really read and benefit from your manuscript, you must guide them on what they can do after reading it. A reader should not reach a dead end. They should not walk away thinking, “I know what the authors did, and I know the conclusion, but what next?” You must articulate possible extensions of your work, open questions, or new directions that arise from your study. Think of these as seeds in your paper. Without planting these seeds, there is no way for the literature to grow from what you have contributed. Citation metrics on Google Scholar may be indirectly hinting at this idea.
My third point relates to an analogy: imagine a wagon carrying goods on a railway track. Today, irrespective of the domain we work in, much of our activity touches machine learning and artificial intelligence. AI is embedded in our digital and even physical environments. For example, we hear about AI‑based washing machines. I am not entirely sure what AI they actually use—it may just be a marketing gimmick—but the point is that AI has become ubiquitous.
Now, many of us in India may not have access to the ideal infrastructure. It can feel like batting against Wasim Akram or Kapil Dev with one hand tied behind your back. The world is not always fair, and we have to work within our constraints.
In the analogy, the wagon represents the modeling mechanism—the AI model. The goods it carries represent your domain knowledge or data. The rails represent your computing infrastructure, your internet connectivity, and your processing capabilities. If you have a strong wagon (a good model), you can carry more goods (data). If your rails are smooth (good GPUs and infrastructure), everything moves effortlessly. But getting all three perfectly aligned is rare, and it requires significant investment.
In India, we often have plenty of data—large volumes of it—but our wagons may not always be large enough, and our rails may not always be world‑class. This means domain understanding becomes crucial. You might have to “massage” the data so it fits into the wagon and can move along the rails you have. If you have powerful GPUs, your approach may be different. But the key idea is this: as students, faculty members, and researchers, we must identify what we can control and use that to innovate. Complaining about what we lack—poor rails or small wagons—won’t help. Focus on what you can influence.
From the awards I saw distributed today, it is clear that this conference has been an excellent venue for all of you. One remarkable feature of this event is its inherently multidisciplinary nature. I noticed topics ranging from smart manufacturing and automation to embedded systems, networking, and security. Such multidisciplinary forums enable interaction between people from different departments or sectors. This broadens perspectives and enhances the way we think. I encourage all of you to interact with peers from other areas, because that is one of the best ways for all of us to grow together.
With these comments, I thank the organizers once again for inviting me. I truly enjoyed spending time among you. I wish you all the very best and a happy new year.
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