Kushagra Agrawal

Computer Engineering Master's Student | Erasmus Mundus Scholar

Åbo Akademi University (Finland) · EDISS Programme (EU)

Master’s student specializing in edge AI, software engineering for machine learning, intelligent food systems, and multi-agent intelligence. I value clarity, reproducibility, and collaborative research.

Phone: +358 40 369 8875 · +91 87802 26117

Email: kushagra.agrawal@abo.fi · kush4409@gmail.com · kushagra.agrawal@ieee.org

I am open for research collaboration, paper authorships, and industry partnerships.

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* as of 13 Sept 2026

Find me online

Work Experience

Taipei Medical University & National Tsing Hua University

Research Intern | July 2025 - August 2025

MIDAS Lab, IIIT Delhi

Research Intern | May 2025 - July 2025

Defence Research & Development Organization - DYSL-AI

Research Intern | May 2025 - June 2025

Indian Statistical Institute

Data Science Intern | Jul 2024 - Oct 2024

IEEE Silchar Subsection

Research Intern | Jul 2024 - Aug 2024

Education

Åbo Akademi University

Master of Science degree (Technology) in Computer Engineering

2026 - Present · Website

EDISS Programme | EMJM Scholarship Holder

Erasmus Mundus Joint Master Degree in Engineering of Data-intensive Intelligent Software Systems

2026 - Present · Website

KIIT Deemed to be University

Bachelor of Technology in Computer Science Engineering (Honours)

2022 - 2026 · CGPA: 9.64 · Website

Selected Projects

Personalized AI Nutrition Chatbot

Oct 2024 - Dec 2024

Predictive Maintenance Analytics

Jul 2024 - Oct 2024

Fine Tuning LLMs on CPU – Intel Unnati Industrial Training Program

Apr 2024 - Aug 2024

Medicinal Leaf Detection Model - Smart India Hackathon 2023

May 2023 - Sept 2023

Summer Schools & Workshops

Cambridge ELLIS Unit Summer School on Probabilistic Machine Learning

ELLIS Cambridge Unit, University of Cambridge, UK

Jul 2026

CVIT Summer School on Artificial Intelligence

Centre for Visual Information Technology (CVIT), IIIT Hyderabad

Jul 2026 & Jul 2024

Quantum Computing: Circuits, Algorithms, and Machine Learning (QuCAM)

National Institute of Technology (NIT), Rourkela

Dec 2024

Machine Learning for Biomedical Signal Processing & Networking

ABV-Indian Institute of Information Technology and Management

Jun 2024 - Jul 2024

Selected Publications

Institutions & Collaborations

Student Achiever Award - Year 2025

Recognised on the occasion of 77th Republic Day 2026 at KIIT In 🇮🇳

This award didn’t come from one win. It came from a year of showing up, pushing limits, and betting hard on research.

Some milestones from the journey:

Secured an IIPP-funded research internship in Taiwan (R.O.C.), supported by the National Science & Technology Council, Taiwan (NT$ 60,000), and conducted a fully funded research internship abroad
Indian patent published (2025): Methodological Framework for Equity-Focused Nutrition Recommendation System
Oral papers at ICDCIT 2025 (Main Track + SRS, Best Paper Award), ICEDGE 2025 (IISc Bengaluru), PReMI 2025 (IIT Delhi)
Poster at ACM Compute 2025 (IIT Ropar), with Student Travel Grant Awards at ACM Compute and ICEdge
Research internships at DRDO DYSL-AI and MIDAS Lab, IIIT Delhi
2025 output so far: 2 Q1 journals (IF ~5.0), 9 book chapters, 150+ citations, h-index 7

I’m deeply thankful to Achyuta Samanta Founder, KIIT & KISS, and the Vice Chancellor KIIT, Prof. (Dr.) Saranjit Singh, for conferring this honour. Grateful to KIIT - Kalinga Institute of Industrial Technology and the School of Computer Engineering, KIIT DU for trusting students to aim beyond the obvious.

Special thanks to the faculty who shaped my research mindset across disciplines: Dr. Amlana Panda, Dr. Anjan Bandyopadhyay, Dr. Sujata Swain, Dr. HRUDAYA KUMAR TRIPATHY, Dr. seba mohanty and Dr. Banipriya Mishra.

And a special thanks to Prof.(Dr.) Prachet Bhuyan and Dr. Abhishek Ray : your guidance made this path clearer and bolder.

Above everything, this award is for my parents. Their belief carried me through every uncertain step.

This moment means a lot - not as a finish line, but as proof that focused effort, good mentorship, and persistence compound.

Open to research collaborations.

100+ Applications - 365+ Days

Reflecting on a year of master's applications and selecting my next chapter. 🎓

Excited to share where the last year of applications led me.

Over the past year I applied to master's programs across Canada, Europe, China, Taiwan, India and a lot more - not really knowing which door would open, or which one I'd want to walk through when it did.

A few of them opened (every one with full funding):

EDISS (Erasmus Mundus), Europe — Dual Master's
CODAS (Erasmus Mundus), Europe — Dual Master's
DEAI (DEAI TFW), Europe — Dual Master's
Algoma University, Canada — M.S. in Computer Science
Ontario Tech, Canada — MSc in Computer Science
Tsinghua University, China — Master's in DS&IT (Distinguished Fellowship)
National Taiwan University of Science & Technology — Master's in Computer & Information Science (MOE + Institutional Type A)
National Tsing Hua University, Taiwan — Master's in ISA (MOE + Institutional Type A)
Plaksha University, India — MS in AI (Institutional Scholarship)

Every one of these came with funding, which honestly still feels a little surreal to type out.

After a lot of back and forth, I've decided to join EDISS Master's programme on the Engineering of Data-intensive Intelligent Software Systems (EMJMD) with a full Erasmus Mundus Scholarship covering my tuition and living costs !

What tipped it for me wasn't the ranking or the country, it was the structure: a dual-degree program that moves me across universities and research environments in Europe, forces adaptability, and is genuinely built around the kind of data science work I want to do long term.

Turning down eight solid offers wasn't easy. Each one represented a version of the next two years I could have lived. But EDISS was the one I kept coming back.

Here's what the two years actually look like:

Year one is at Åbo Akademi University in Turku, Finland - a mix of core data science and software engineering courses (data science, AI, machine learning, edge computing for ML) plus practice-heavy components like an internship and a winter school (also some Aurora Chasing ?). It's the foundation year, built to get everyone to the same technical baseline before specializing.

Year two is where the program forks, and I get to choose the path:

Industrial Software Engineering at Mälardalen University in Sweden
Computer Vision and Intelligent Systems at the University of the Balearic Islands in Spain
Model Driven Machine Learning – Software Engineering at the University of L'Aquila in Italy

Three countries, three specializations, one decision still ahead of me. That's the part of this program that actually convinced me — it's not just "study abroad," it's a structured bet that moving across research environments makes you better at this work, not just well-traveled.

Grateful to everyone who wrote recommendation letters, reviewed my SOPs, and talked me through the decision fatigue. On to the next chapter.

ELLIS Summer School at University of Cambridge

Probabilistic Machine Learning · ELLIS Cambridge Unit, UK 🇬🇧

Just wrapped up the ELLIS Summer School at the University of Cambridge, and I'm still processing how much this experience gave me.

Over the past week, I had the privilege of learning from an exceptional lineup of researchers and practitioners representing some of the world's leading institutions, including the University of Cambridge, University of Bristol, University of Oxford, Imperial College London, The University of Edinburgh, DTU - Technical University of Denmark, Microsoft Research, AstraZeneca, and The Alan Turing Institute, among others.

A week ago I walked into rooms full of researchers, PhD students, and people years ahead of me in this field. I was often the youngest person there. Instead of being intimidating, it turned into one of the most motivating parts of the whole thing. It pushed me to ask more questions, listen harder, and hold my own in conversations I wasn't always sure I belonged in.

I'm leaving with a lot more than I came in with:

Conceptual clarity that lecture slides alone never gave me
Conversations with people whose papers I've read and cited
Friendships and connections that I know will outlast this summer
A few evenings walking around Cambridge and London, just taking it all in

There's something about learning surrounded by people who are genuinely obsessed with the same problems you are. It changes how you think, not just what you know.

Huge thanks to the organizers and everyone behind ELLIS for putting together something this well run and this generous with knowledge and time. It's rare to find a program that balances serious academic depth with an environment where people actually want to help each other grow.

Heading back with a sharper mind, a longer contact list, and a lot more clarity on what I want to work on next.

#ELLIS #Cambridge #MachineLearning #SummerSchool #AI #Research