With over two decades of deep engineering experience across global technology leaders such as HCL, Agilent Technologies, Marvell Technology, Freescale Semiconductor, and Juniper Networks, Sudhanshu Mittal brings a rare, ground-up perspective on how embedded systems have evolved from low-level engineering to powering today’s intelligent, connected world.
Currently serving as Head & Director – Technical Solutions at MeitY Nasscom Centre of Excellence, Mittal has worked at the intersection of hardware and software—building everything from firmware and drivers to complex, real-world systems across industries such as networking, healthcare, and IoT.
His journey mirrors the evolution of embedded technology itself—from assembly-level programming and standalone devices to today’s era of edge AI, software-defined systems, and connected ecosystems. With a strong focus on innovation, IP creation, and ecosystem building, he now plays a key role in shaping how India’s startups and enterprises navigate the next phase of digital transformation.
In this conversation, he shares insights on the evolution of embedded systems, the realities of digital transformation, the growing importance of IP, and what lies ahead as AI and IoT continue to converge.
Some edited excerpts:
You have over 25 years of experience across companies like HCL, Agilent, Marvell, Freescale, and Juniper. What drew you to the embedded domain, and how has the field evolved since you began?
I have always been drawn to software development. Even during my engineering days, I gravitated towards software work. My favourite lab was the microprocessor lab, where we worked with kits based on 8085 and 8088 processors. Writing assembly code, converting it into machine language, feeding it into the system, and watching it drive hardware operations had a strong appeal.
My first job was with HCL in R&D hardware. The role involved not only working with tools like CROs and logic analysers but also deep assembly-level programming—debugging BIOS issues and firmware for add-on controllers. Seeing a product come to life in the real world was incredibly satisfying.
After HCL, I moved fully into software, working extensively on drivers and firmware. Operating at the intersection of hardware and software—and seeing systems come alive—is an experience only an engineer can truly appreciate.
Over the years, embedded systems have evolved significantly. What started as standalone devices has grown into highly connected, complex systems. With the rise of RTOS, virtualisation, and software-defined architectures, embedded technology has moved from being “invisible” within devices to powering entire ecosystems across automotive, communications, industrial automation, and consumer electronics.
Today, embedded systems sit at the core of innovations such as drones, robotics, 5G, IoT, and edge AI. The shift has been from individual devices to “systems of systems.” What was once a niche engineering field is now foundational to digital transformation.
From networking and storage to medical equipment and IoT, you’ve worked across multiple verticals. Which projects stand out as career-defining moments?
For an engineer, every project matters. Each one teaches something new.
I have worked on drivers and firmware for storage controllers, brought networking controllers to life to ensure seamless data transfer, and even tested cancer therapy systems in hospitals to validate their ability to control radiation beams. I have also built and led multicore software teams whose solutions were widely adopted.
Each of these experiences contributed to my learning and shaped the next phase of my career.
Digital transformation is a buzzword today. What does it truly mean for industries like automotive and healthcare?
Digital transformation is no longer just a buzzword—it is a necessity. Organisations understand that without digital adoption, they risk falling behind.
However, true digital transformation goes beyond deploying sensors or building dashboards. It is about using data for decision-making. It requires leadership to trust and act on data, and for frontline teams to see technology as an enabler, not a threat.
The biggest challenge is not technology—it is culture. Unless stakeholders across the organisation embrace digital adoption, the expected benefits will not materialise. At Nasscom CoE, we work closely with enterprises to help them navigate these challenges.
How crucial is IP awareness for early-stage tech ventures?
IP awareness is critical, especially for technology-driven ventures.
In large organisations, IP creation builds both personal credibility and organisational value. For startups, IP becomes a key asset alongside revenue and customers. It creates entry barriers and signals technological depth to investors.
At Nasscom CoE, we actively support innovators through mentoring and knowledge sessions to help them build and protect their IP.
What skills should young professionals focus on in embedded and IoT?
Embedded development requires a hardware-aware mindset. Developers must understand how systems interact—interrupts, memory constraints, caching, and data flows—while working within highly resource-constrained environments.
Working at the kernel level demands precision. A small mistake can crash an entire system, not just an application. This makes rigorous testing non-negotiable.
More than anything, success in this field comes down to attitude—taking full ownership of your work.
How do you see India’s participation in global standards evolving?
India’s participation in global standards needs to grow. A services-led industry has limited exposure to standard-setting, as it typically focuses on implementation.
However, as India shifts towards product development, participation in standards becomes critical—especially in areas like IP, interoperability, and design decisions. We expect this involvement to increase significantly, and Nasscom CoE is actively contributing to IoT standardisation efforts.
What trends in IoT and AI excite you most?
The convergence of IoT and AI is particularly exciting. Edge AI is already enabling intelligence closer to where data is generated, reducing dependency on the cloud.
Going forward, domain-specific AI will be key. Generic models can only go so far—high-accuracy applications, especially in sectors like healthcare, will require specialised intelligence.
We are also at the early stages of autonomous AI. While there are technical and ethical challenges ahead, the direction is clear. At Nasscom CoE, we have a front-row view of these developments and are actively shaping conversations around the future of AI.