Jefferson Cavalcante
Staff Software Engineer at CESAR
Ceará, Brazil
Summary
👤
Senior🎓
Top SchoolJefferson Cavalcante is a Staff Software Engineer and PhD candidate in Computer Science with 11 years’ experience blending research-grade networking expertise with hands-on systems engineering. He leads platform and Kubernetes-driven infrastructure work at CESAR and has engineered smartNIC firmware, RISC‑V firmwares, and Linux kernel modules for high-performance network monitoring and acceleration. His background spans IPv4/IPv6, Optical Transport Networks, Metro Ethernet, data-center telemetry and protocol development, with practical implementations in C, Go, Python and OpenDaylight/NETCONF/YANG. Jefferson’s work bridges academia and product: it has produced papers, patents and production plugins (e.g., SPIRE attestation) while driving scalable forecasting and observability pipelines. Based in Ceará, Brazil, he brings a rare combination of low-level kernel/firmware skill and modern cloud-native ops, with a growing focus on applying ML to networking and embedded systems.
11 years of coding experience
5 years of employment as a software developer
MSc in Computer Science, Computer Networks, MSc in Computer Science, Computer Networks at Universidade Estadual do CearáDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Universidade Federal do CearáBSc on Computer Science, Computer Networks, BSc on Computer Science, Computer Networks at State University of CearáInglês, Interpretação e Tradução de Idiomas, Inglês, Interpretação e Tradução de Idiomas at IMPARH
Portuguese, English
Github Skills (17)
network-graph8
r-package7
igraph7
mathematics6
graph-algorithms6
r6
network-analysis6
complex-networks4
graph-theory4
python3
face3
machine-learning2
face-detection2
pattern-recognition2
face-recognition2
Programming languages (2)
Github contributions (5)
jeffcav/grasp-max-matching
Jul 2016 - May 2021
Contributions:2 pushes, 1 branch in 4 years 10 months
jeffcav/ml-from-scratch
Mar 2022 - Jun 2022
Implementation of traditional machine learning models and algorithms
Contributions:2 PRs, 70 pushes, 21 branches in 3 months
pythontraditionaldata-sciencemachine-learningpattern-recognition
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