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Kamil Arif.

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Data Scientist at AT&T building optimization and anomaly-detection systems for a national network. I work where applied ML meets hard operational constraints — algorithms that have to survive contact with real infrastructure, real budgets, and real engineering agreements.

Commits over time

86 repos · since Jan 27, 2019

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Experience

AT&TSr. Specialist, Member of Technical Staff

Present

Artemis Network Planning

  • Build algorithms that search for cost-effective L2/L3 network topologies subject to hard engineering and latency constraints.
  • Finalized plans now cover regions servicing 12.4M people, with $60M in confirmed cost savings to date.
  • Work directly with network operations at several levels to pin down real requirements and anticipate failure modes before they reach the plan.

AT&TData Analyst

IPSEA — Technical Development Program

  • Developed an IP reallocation algorithm with $9M in theoretical savings, freeing over 300K addresses.
  • Refactored the team's data pipelines for better parallelization and use of provisioned compute.
  • Built anomaly detection over backbone DNS server metrics to catch cyberattacks and infrastructure failures, and laid the foundation for the frontend team's dashboard.

NJITGrader

CS 370 — Intro to AI / Data Mining

  • Graded assignments for a senior-level data mining course — 228 students across 3 semesters.
  • Worked with a team of graders and the professor to keep standards consistent.
  • Took an active role in helping students learn from mistakes and build real intuition for AI/ML concepts.

CDx DiagnosticsIntern

Cancer Cell Classification

  • Differentiated cancerous cells from debris in dyed microscope slides, owning collection, annotation, training, and testing.
  • Reached 89% detection accuracy on a limited dataset by fine-tuning a ResNet-50.
  • Set up documentation for every deliverable at the end of the internship.

Selected work

All projects →

ML Architecture & Topology Research

Independent study into novel ML architectures, measured by computational efficiency and knowledge representation.

  • PyTorch
  • Topology
  • Visualization

Buckshot Roulette — RL in Stochastic Games

A Python engine for a hidden-information game, built to train reinforcement learning agents against it.

  • Python
  • Reinforcement Learning
  • Tensorboard

GalaxyGen

A worldbuilding and mapping tool for sci-fi galaxies — procedural generation with an interactive editor.

  • TypeScript
  • Next.js
  • Pixi.js