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@Comcast
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denopink/README.md

Hi there đź‘‹

LinkedIn

The Rookies

Go Rust Python C++

Skills

Machine Learning, AI/ML Applications, Exploratory Data Analysis, Python, Git, Golang, Rust, C++, Unreal Engine, Docker, Ambassador, Kubernetes, AWS, Concourse

Education

Computer Science & Mathematics, B.S • Dec 2018 • Temple University

Personal Projects

Software/Game Dev • Unreal Engine AR Prototyping

  • Setout to prototype an AR app build with Unreal Engine and create an educational blog post on how the app works to a non-technical audience while staying true to the internal workings of Unreal Engine
  • Project blog post link: https://www.therookies.co/projects/22349
Experience

ENG 2, SOFTWARE DEV • COMCAST- Xmidt/Webpa, PHILADELPHIA• MARCH 2022 – Current

• Golang backend developer for highly scalable opensource IoT management related softwares such as xmidt, webpa, codex

ENG 2, SOFTWARE DEV & ENGINEERING, MACHINE LEARNING• COMCAST- DATA NETWORK SERVICES & PRODUCTS, PHILADELPHIA• JAN 2019 – MARCH 2022

• Developer lead for the inner-source AMP project, a ML platform for ML application development & orchestration • Data science lead for the virtual service gateway (VSG) usage anomaly detection project, used to detect usage byte counting anomalies of cm/cmts/vsg and later expanding the solution to detect anomalies/major deviations in dscp usage/ip family usage • Designed and implemented a scalable monitoring tool for Comcast’s business and residential voice services’ application servers using SNMP Trap data

ENGINEERING & TECHNOLOGY INTERN, MACHINE LEARNING• COMCAST- NETWORK SERVICE & ANALYSIS, PHILADELPHIA• MAY 2017 – DECEMBER 2018

• Developed a ML application that detects real-time network anomalies, abnormal packet loss, between Data-Centers and Cloud-RAN using IP SLA probe data • Developed a tool that analyzes Comcast’s backbone health and predicts several network anomalies 5 minutes in advance with high precision and recall using WLA2 probe data

COMPUTER VISION RESEARCH ASSISTANT • DR. RICHARD SOUVENIR, TEMPLE UNIVERSITY, PHILADELPHIA• JAN 2017 – FEB 2020

• Developed algorithms/architectures to better understand human driving behaviors and the impact of low penetration rates of autonomous vehicles within our society • Assisted with the advanced study of multi-target tracking algorithms and effectively analyzed large amounts of motion data collected from a variety of sensors • Developed algorithms for large-scale tracking and group behavior and that allowed domain scientists to analyze large amounts of motion and behavioral data to find activities of interest

Github Stats

denopink's GitHub stats Top Langs

Pinned

  1. xmidt-org/webpa-common xmidt-org/webpa-common Public

    The collection of small common packages for the webpa project.

    Go 25 25

  2. xmidt-org/talaria xmidt-org/talaria Public

    The Xmidt routing agent.

    Go 10 19

  3. xmidt-org/wrp-go xmidt-org/wrp-go Public

    go implementation of the Web Routing Protocol

    Go 4 7