Hello, I am Md. Faiyaz Abdullah Sayeedi, currently pursuing a Bachelor of Science in Computer Science and Engineering at United International University (UIU), Bangladesh. With a strong academic record, I have served as a Grader and Undergraduate Teaching Assistant at UIU, supporting students and faculty in foundational computing courses.

I am currently an AI Intern at Ontik Technology and a Research Assistant at the MIRA Wing, Center for Cognitive and Decision Sciences (CCDS), Independent University, Bangladesh (IUB). My research interests include, but are not limited to, Computer Vision, Large Language Models, and Multimodal Machine Learning—with a focus on impactful, real-world applications.

I have published several peer-reviewed papers in reputable international workshops, conferences, and journals such as ICLR (Tiny Papers Track), IEEE TENSYMP, NeurIPS Workshop (MusIML), and Data in Brief (Elsevier). I have collaborated with researchers from globally recognized institutions, including Charles Darwin University, Johannes Kepler Universität Linz, and the University of Alberta. Check out my Google Scholar profile for more details.

When I am not immersed in code, datasets, or late-night paper submissions, I am likely cheering for my favorite football club. As a die-hard fan of Real Madrid, I follow every match with the same passion I bring to my research— Hala Madrid, siempre!

Machine learning is often portrayed as objective and neutral, but real-world applications tell a different story. From facial recognition systems misidentifying people of color to hiring algorithms favoring male applicants, bias in AI has emerged as a serious concern.

Massive AI models like GPT-4 and PaLM 2 dominate headlines—but small models are quietly powering healthcare, agriculture, and on-device apps with comparable performance at a fraction of the cost. From TinyML to DistilBERT, these efficient models are driving a shift toward ethical, inclusive, and sustainable AI.