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Report abuseI'm a final-year Computer Systems Engineering student at ESI Algiers, and my center of gravity is networking and infrastructure — how you take a network from "it works" to "it scales, fails over, and stays secure without anyone noticing."
Outside of networks, I like reaching into adjacent territory — combinatorial optimization, HPC, IoT and full-stack development — mostly because understanding how systems behave under load, or how a scheduling problem gets solved, makes me a better network engineer too.
class Ikram:
def __init__(self):
self.role = "Computer Systems Engineer, ESI Algiers (Final Year)"
self.focus = ["Networking & Infrastructure", "Systems Architecture", "HPC / Optimization", "IoT"]
self.currently = "designing networks that don't blink when something fails"
self.fun_fact = "will benchmark literally anything twice"|
🕸️ Data Center & Redesigned a real data center's 3-Tier network into a Leaf-Spine fabric. |
🧩 Combinatorial Metaheuristics, exact methods, and what happens when you let an RL agent tune them instead of a human. |
⚙️ High-Performance GPU-resident pipelines, kernel design, and hunting for the actual bottleneck instead of the obvious one. |
🌐 Full-Stack Laravel/Vue/Symfony apps and IoT pipelines, built end to end when a project calls for it. |
Feel free to reach out — networking talk especially welcome.
📫 li_chouider@esi.dz · 🔗 LinkedIn · 🧑💻 GitHub
This repository presents a structured, comparative study of optimisation methods applied to the Flow Shop Scheduling Problem (FSP), a classical NP-hard combinatorial optimisation problem in operati…
Jupyter Notebook 1
A Deep Q-Network controller that dynamically steers Genetic Algorithm operators (selection, crossover, mutation) in real time to solve the Flow Shop Scheduling Problem.
Jupyter Notebook 1
Redesigning ESI's data center from a legacy 3-Tier network to a Leaf-Spine fabric with VXLAN/BGP EVPN overlay, eBGP+ECMP underlay, and full security hardening — validated in an EVE-NG lab.
A full Big Data pipeline that ingests, cleans, vectorizes, and semantically searches millions of HDFS log entries using Apache Spark, Sentence-Transformers, and PostgreSQL + pgvector.
Python 1
Fully GPU-resident CUDA training pipeline for a shallow neural network — up to 47× faster than a naive per-kernel CUDA baseline by eliminating host↔device transfers and moving forward/backward/loss…
Jupyter Notebook 1
Robots learning to follow natural language instructions using RL and multi-modal AI.
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