About me
Third and final-year PhD candidate in Computer Science at Queen Mary University of London, under the supervision of Dr. Gianni Antichi.
I am actively looking for opportunities starting summer 2024, post-PhD.
My research is in the intersection of software and hardware, with a focus on algorithms, data structures, and system design.
Problem solving and system engineering are my passions, and I have applied these to innovative projects involving network monitoring and high-speed data collection techniques.
My work during the PhD has been highly collaborative, and I thrive working in teams with diverse and complementary competences.
List of works
| Venue | Year | Title | Authors |
|---|---|---|---|
| ACM SIGMETRICS | 2023 | Lightweight Acquisition and Ranging of Flows in the Data Plane | A. Monterubbiano, J. Langlet, S. Walzer, G. Antichi, P. Vasallo, S. Pontarelli |
| ACM SIGCOMM | 2023 | Direct Telemetry Access | J. Langlet, R. B. Basat, G. Oliaro, M. Mitzenmacher, M. Yu, G. Antichi |
| IEEE TMC | 2022 | Hybrid P4 Programmable Pipelines for 5G gNodeB and User Plane Functions | S. K. Singh, C. E. Rothenberg, J. Langlet, A. Kassler, P. Vörös, S. Laki, G. Pongrácz |
| ACM HotNets | 2021 | Zero-CPU Collection with Direct Telemetry Access | J. Langlet, R. B. Basat, S. Ramanathan, G. Oliaro, M. Mitzenmacher, M. Yu, G. Antichi |
| Thesis | 2020 | Offloading Virtual Network Functions - Hierarchical Approach | J. Langlet |
| IEEE EuroP4 | 2019 | Towards Neural Network Inference on Programmable Switches | J. Langlet, A. Kassler, D. Bhamare |
| Thesis | 2019 | Towards Machine Learning Inference in the Data Plane | J. Langlet |
Teaching
| Year | Course | University |
|---|---|---|
| 2021 - 2022 | Distributed Systems | Queen Mary University of London |
| 2019 | Data Structures and Algorithms | Karlstad University |