Tamjid On The Internet

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Curriculum Vitae

Hi, I am Tamjid Hasan Fahim. Computer Science & Engineering ~~freshman~~ ~~sophomore~~ ~~junior-year~~ senior-year student (shocker!) at RUET. Wannabe a real computer scientist someday.

To me, Computer Science feels like just as Terry Pratchett wrote, “It is still magic even if you know how it is doing.” Magic not with wands and robes, but the kind where absurdly simple building blocks stack up through layers of abstraction until they turn into systems of remarkable complexity and elegance. This enduring sense of wonder, of being able to grasp the underlying mechanism yet still be astonished by its form, drives me to explore deeper into the black boxes that make modern computing possible.

My primary research question is: how do we get AI systems to move beyond token-level statistics toward representations closer to human perception — forming coherent understanding from language and vision instead of fragmented signals across modalities.

Personally, I am INTP. Interested in architecture, cognitive science, literature & technology. I’m open to team collaborations, internships and publication opportunities in relevant domains.

[July 2026] Paper accepted at the BioNLP Workshop (ACL 2026) PsyDefDetect Shared Task: “Overcoming Extreme Response Bias in LLMs via Rubric-Grounded Retrieval and Supervised Clinical Reasoning Distillation for Fine-Grained Ordinal Classification”. Awarded Best Interdisciplinary Insight Paper for the shared task and secured 3rd place on the leaderboard.
[Jul 2026] Co-authored paper, “AREG: Adversarial Resource Extraction Game for Evaluating Persuasion and Resistance in Large Language Models”. Accepted at the MusIML Workshop, ICML 2026.
[Mar 2026] Academic update for the third-year even semester: Achieved an SGPA of 3.90, placing in the top 1.7% of the class among 177 students.
[Nov 2025] Paper accepted at the Bangla Language Processing Workshop (IJCNLP-AACL) Shared Task: “Domain-Adapted BERT for Bangla Hate Speech Detection: Contrasting Single-Shot and Hierarchical Multiclass Classification”.