efaz@arch: ~
~whoami
mohammed efaz
~cat /etc/role
full stack developer, ml engineer and tech enthusiast
~pwd
dhaka, bangladesh·budapest, hungary
~cat about.md

i'm a full stack developer with around 1 year of internship experience at genesys. i create utility-based apps that solve real problems.

computer science graduate from eötvös loránd university (elte), hungary in 2025. specializing in machine learning, ai, and privacy-preserving local llm applications. experienced in building scalable apis, android/kotlin apps, and chrome extensions. passionate about creating practical solutions that generate value.

profile.ascii
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mohammed efaz

[ hover to reveal ]

skills.json
~jq '.skills[]' ~/.config/profile.json
pytorchtensorflowscikit-learnhuggingfacelangchainpythontypescriptjavakotlinjavascriptsqlc#reactvue.jsnext.jsfastapispring bootangularandroidchrome extensionstauridockergitlinuxawsci/cd
~ fastfetch
      /\
     /  \
    /\   \
   /      \
  /   ,,   \
 /   |  |  -\
/_-''    ''-_\
efaz@arch
───────────────
os: arch linux x86_64
host: framework laptop 13
kernel: 6.18.3-arch1-1
shell: zsh 5.9
wm: hyprland
terminal: ghostty
experience.log
~cat ~/.config/experience/* | less

software engineer intern

genesys

sep 2024 — jan 2025

achieved 100% code coverage in journey management. resolved 20+ bugs across angular and vue codebases.

angularvuetypescriptcypress

qa automation engineer intern

genesys

mar 2024 — oct 2024

automated end-to-end testing with playwright and cypress. maintained fedramp compliance standards.

playwrightcypresstdd

teaching assistant

eötvös loránd university

sep 2024 — jul 2025

mentored 20+ first-year computer science students through coding fundamentals and career guidance.

pythonjava
research.bib
~bibtex --format ieee ~/research/mereader.bib
under reviewieee access · 2024

mereader: offline, privacy-preserving, progress-aware ai reading assistant

first author

abstract

this paper introduces mereader, an offline, privacy-preserving, and progress-aware ai companion for reading on consumer-grade computers. unlike systems that process entire books and risk revealing future content, mereader confines both retrieval and generation to the reader's current position in the text. the system integrates epub parsing, a hybrid retrieval stack (vector similarity, bm25, summary embeddings, and query expansion). we evaluate across three novels with 600 items (300 comprehension queries; 300 spoiler checks) using bertscore precision, recall, f1, and the llm-as-judge rubric (contextual fidelity, relevance, helpfulness, coherence, instruction following). results show a clear quality-latency frontier: mid-size models (like gemma3n:e4b, llama3.1:8b) achieve f1 ≈ 0.74-0.75 at ≈ 30s per item, while deepseek-r1:1.5b provides a low-latency alternative (≈ 15-20s, f1 ≈ 0.69-0.70). performance remains stable even with 1-2 evidence passages, showing efficient and non-redundant retrieval. the spoiler prevention system prevents future text leakages while staying relevant to the query, aligning quantitative metrics with higher judged coherence and fidelity.

~/projects
~ls -la ~/projects/ --color=always
mereader/

privacy-preserving ai reading assistant with progress-aware retrieval

pythonpytorchvue.js
tron/

light-motorcycle battle game with mvc architecture and sql scoring

javasql
smart-home-iot/

home automation simulation with sensors and controls

pythonoop
pokemon-tcg/

trading card platform with php backend

phpjavascript
atmosphere-sim/

gas layer simulation using design patterns

c#oop
mapmaker/

procedural terrain generator with grid-based maps

javascript
contact.yml

# available for opportunities

status: open