About Me
Hi, I'm Vinamra (aka Vin), a PhD candidate in the School of Computing Science at the University of Glasgow, researching AI compilers under the supervision of Dr José Cano Reyes. Beyond academia, I work as an AI Engineer at Unineed Limited, where I design and implement full-stack AI solutions. During weekends, you can often find me participating in hackathons around the world, developing cross-domain applications and exploring emerging technologies.
The woods are lovely, dark and deep,
But I have promises to keep,
And miles to go before I sleep,
And miles to go before I sleep.
— Robert Frost, Stopping by Woods on a Snowy Evening
My Story
My story is essentially one big love affair with technology. Ever since I was a kid, I was that curious troublemaker who had to know how everything worked. I literally unscrewed my mom's hair dryer and took apart the fridge just to see what was inside. That hands-on curiosity never left me. My early attempts at building a simple music streaming site as a kid in India, back when everyone had those old Nokia phones, gave me my first taste of creating something people could actually use.
When I got to college, I met my amazing mentor, Dr. Vishal Kumar, who took me under his wing and showed me just how much more I could do. That's when things really took off. My first big hackathon at Stanford's TreeHacks was a game changer; it opened my eyes to this huge, vibrant world of tech and incredible people. Even though I didn't win that first time, I was hooked. From there, I ended up at MIT's hackathon, winning as the first non-Ivy student, and just kept going. I've now been part of more than 110 hackathons with 65+ awards, but for me, it's never just about the accolades. It's about the community, the incredible people you meet, and the good that technology can bring into the world.
During my master's at the University of Glasgow, I collaborated with STMicroelectronics on Edge AI projects, especially around human activity recognition. Now, as a PhD candidate, I'm diving deep into developing AI compilers for next-gen workloads under the guidance of Dr. José Cano Reyes, who was also my supervisor during my master's. He's been a huge motivator and key part of the incredible work we're doing. I'm deeply passionate about deep tech, learning, research, and improving human life. Whether through compiler optimizations that make AI more efficient, or research that enables applications in healthcare, robotics, and beyond, I'm driven by the potential to make a real difference.
Besides my PhD, I'm working as an AI Engineer at Unineed Limited, building end-to-end systems to optimize business processes and boost productivity. I want AI to be seen as a tool to empower us, not something to worry about. And I just love learning new things every step of the way. Because I believe in giving back, I'm working on Mcurio (previously PERPLEXED), a platform offering free, decentralized educational resources for everyone. I'm also passionate about the environment, working on ClimateThread to connect community action for environmental causes.
In the end, hackathons and open-source resources really changed my life, and that's why I'm so committed to building tools and platforms that help others learn and grow. This is my story so far, and it's only the beginning of what I hope to do.
Key Achievements
Recognition and impact across research, innovation, and community
Publications
Research papers including 3 Best Paper Awards
Hackathons
Global participation and collaboration
Awards & Recognition
Hackathon awards from MIT, Harvard, Duke, UNICEF, and more
Collaborators
From 38+ countries worldwide
Why AI Compilers
While working on high-level programming and developing AI/ML systems, I realized there's a fundamental limit to what you can optimize operationally and algorithmically at the high level of programming. No matter how efficient your algorithms or how well you structure your code, the bottleneck always comes down to one critical question: how can the machine understand these AI workloads and process them efficiently in hardware?
This realization led me to AI compilers; the bridge between high-level AI models and the hardware that executes them. By focusing on how compilers can translate and optimize AI workloads for different hardware architectures, I'm aiming to address the root cause of performance limitations, not just the symptoms.
Education
PhD in Computing Science
University of Glasgow, School of Computing Science, UK
Researching Transfer Learning for Adaptive Compiler Optimization in Edge Devices. Developing advanced AI Compilers to make AI systems more efficient and accessible across diverse hardware platforms. Supervised by Dr. José Cano Reyes.
MSc in Computing Science
University of Glasgow, School of Computing Science, UK
Specialized in Edge AI and On-Device Learning. Key courses: Programming Systems, Data Science and Systems, Human-Centred Security, Cyber Security Fundamentals, Text as Data (NLP), Web Science. Collaborated with Danilo Pietro Pau from STMicroelectronics and Dr. José Cano Reyes. Thesis grade: A3.
B.Tech in Computer Science & Engineering
Bipin Tripathi Kumaon Institute Of Technology, Uttarakhand Technical University, India
Graduated with First Class Honours (84%, Top 1% of class). Merit-Based Scholar. Focused on foundational computer science, algorithms, and software engineering. Completed thesis under Dr. Vishal Kumar. Served as Class Representative for 4 years, Secretary IEEE Student Branch BTKIT, and Mess Secretary for Gomukh and Kailash Hostel.
Skills & Technologies
A comprehensive toolkit for building AI systems and applications
Programming Languages
Libraries
Frameworks
LLM APIs/SDKs
DevOps & Cloud
Tools
Recent Projects
Turning ideas into real-world impact
Mcurio
Building Equitable AI Education for All
At mcurio I am building a free Decentralised AI-powered EdTech platform that allows you to design your own learning journey using the best open courses, hackathons, and global opportunities.
Want to Learn More?
Explore my research, projects, and download my resume.