Andre F. Zanella
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Andre F. Zanella

I’m Andre, a Researcher, Engineer, and Data Scientist making a fruit salad out of these themes. I mainly enjoy transforming internet and network measurements into interesting tools and insights.

I’m currently a Research Scientist at Telefónica Innovación Digital, where my focus is on creating tools that transform large-scale network measurements into useful insights for both the MNO, as well as parties interested in the cool stuff you can do with mobile networks data.

Background

I received my PhD in Telematics Engineering from UC3M, and my Masters and Bachelors in Electrical Engineering from UFPR.

Throughout my PhD, I worked as a Research Assistant at IMDEA Networks (quite the cool place, highly recommend) at the Networks Data Science Group, under the supervision of Dr. Marco Fiore.

I was also a part of the Group of Integrated Circuits and Systems (GICS) at UFPR during my Masters and Undergrad, under the supervision of Dr. Eduardo Gonçalves de Lima.

Let's Connect

If you want to get in touch with me about something or just to say hi, reach out on social media or send me an email.

Research Interests

  • Mobile networks
  • Network performance and measurements
  • Distributed/edge systems

Recent research

See all research
  • Paper Teaser
    Understanding the potential of urban parks to promote well-being
    Paper
    In
    Nature Cities

  • Paper Teaser
    Lost in Encryption: Monitoring Audio and Video Flows without Payload in Video-Conferencing Applications
    Julien Gamba, Andre Felipe Zanella, Ricardo Morla, Kyle Schomp, Álvaro Feal, Arash Molavi Kakhki
    Paper
    In
    NGNO Workshop @Sigcomm'25

  • Paper Teaser
    Characterizing, Modeling and Exploiting the Mobile Demand Footprint of Large Public Protests
    André Felipe Zanella, Diego Madariaga, Sachit Mishra, Orlando E. Martínez-Durive, Zbigniew Smoreda, Marco Fiore
    Paper
    In
    ACM IMC'24

Latest posts

See all posts
  • Characterizing the Mobile Demand Footprint of Large Public Protests
    How large-scale public protests leave a measurable footprint on mobile network traffic — and how aggregated data can reconstruct protest dynamics while preserving privacy.
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