- MSc Researcher
- Istanbul University-Cerrahpaşa
Research
Topics I have worked on since starting my MSc, in approximately anti-chronological order.
A complete list of publications is on ORCID.
Covert Channels in Multi-Agent LLM Systems
As LLM agents are given more freedom to reason and to talk to each other, a single
compromised agent can leak task-external information to another by embedding it in
stylistic, ordering or timing choices — a steganographic channel that syntactic filters
and static DLP see as perfectly clean. The field has established that such covert
collusion exists, but has not measured how much capacity a given
interface carries. My thesis defines that quantity and draws a practical consequence
from it: runtime monitoring cannot reduce the capacity; the only lever is constraining
the interface at design time.
Deep Learning for Medical Imaging
On MRI, CT and X-ray, deep models can approach expert-level accuracy; the real
bottleneck is not the model but labelled data. Medical annotation is expensive, slow
and imbalanced — for rare classes even a few hundred examples are hard to obtain.
Working with clinicians and faculty, I built transfer-learning based solutions:
meningioma grading, thoracolumbar fracture detection, oral cancer classification, and
an ongoing study on dental furcation. This line of work forms my academic backbone.
Autonomous Agents and Orchestration
Autonomous agents are impressive in a demo and brittle in production: they stall under
ambiguity, fail silently, and are hard to debug. The question I care about is whether
splitting responsibility across several agents — instead of one enormous prompt —
genuinely makes the system more reliable. I built an autonomous browsing agent that
substantially reduced manual QA on Google Maps, and a hierarchical orchestration system
that turns natural-language input into a task plan. This line also provides the
practical ground for my thesis work.
Retrieval and RAG
The hard part of RAG is not generation but retrieval: finding the right fragment in a
hundred-table schema or a corpus of thousands of papers. Given the wrong context, the
model confabulates confidently. I wrote a post series that walks through exactly where
hallucination comes from, using a natural-language-to-SQL assistant; I am currently
building an academic RAG system enriched with a citation graph to survey the literature
around my thesis.
msc thesis · in progress
Measuring the Undetectable: Covert-Channel Capacity in Multi-Agent LLM Systems
Advisor: Şafak Durukan Odabaşı — Istanbul University-Cerrahpaşa
I measure the undetectable covert capacity an interface between two agents can carry
in multi-agent LLM systems.
Work in progress; the paper is not published yet.
Happy to share it by email on request.
education
2025 – present
Istanbul University-Cerrahpaşa
MSc, Computer Engineering
2021 – 2025
Istanbul Medeniyet University
BSc, Computer Engineering