Behzat Aslanoğlu
من الجزيئات إلى العصبونات إلى الوكلاء
نمت الرياضيات والكود في رأسي معًا — ثم انتقلتا عبر الجزيئات والأدمغة وتعلّم الآلة إلى الحدود القصوى: LLMs، والذكاء الاصطناعي الوكيلي، وأسراب الوكلاء. خيط واحد لا ينقطع.
القوس الموازي.
Math never waited for the code, and the code never waited for the math. They arrived together and stayed together — one continuous, intertwined thread from the very start.
— the through-line · BSc → MSc → PhD → the work
لم يكن الانضباط يومًا حفظ الصيغ — بل تفكيك مشكلة واقعية فوضوية إلى معادلات يمكنك حلها فعلًا.
— applied mathematics · University of Tabriz
Don't just fit the curve — model the mechanism.
— molecular dynamics · TÜBİTAK, F876L resistance story
Vision
Intelligence from molecules to neurons to agents — one unbroken thread. Mathematics, science, and agentic AI grown together, and shared as I build.
Mission
Build LLMs and agentic AI that don't just answer — they act. From first-principles ML to coordinated swarms of agents, ship systems, not notebooks.
Philosophy
Reduce a messy, real system to a model you can trust. Respect the physics, model the mechanism — don't just fit the curve. Math and code arrived together and never waited for each other.
The Goal
Coordinated swarms where emergence echoes the brains I studied — resilience, parallel exploration, and answers that come from collective reasoning rather than one model's guess.
ثلاثة فصول، خيط واحد
الأعمدة التي تقوم عليها القصة — والمحرك الذي ما زلت أبني به.
From Proofs to Physics
Applied mathematics, molecular dynamics, and the F876L resistance story. The discipline of decomposing a messy, real problem into equations you can actually solve.
Connectomics as Graph Theory
Super-resolution for the most complex known graph — predicting high-resolution brain graphs from sparse, noisy observations. Open data, released to the community.
From ML to Swarms
From-scratch ML → federated learning → agents. Today: LLM systems end to end, and a working thesis that emergence echoes the brains I studied.