CAMELOT is a CMU|Portugal joint project by Feedzai, CMU, U.Coimbra, IST and FCUL, funded by FCT and FEDER.
I am the PI on the FCUL side, coordinating the efforts on verification and automatic optimization of machine learning pipelines.
The CAMELOT (autonomiC plAtform for MachinE Learning using anOnymized daTa) project aims at developing an innovative machine learning platform, which will tackle three key issues that hinder the efficiency and accuracy of modern AI applications:
• Ensuring real-time constraints during both the training and inference phases of machine learning models, while minimizing operational costs deriving from the use of cloud resources.
• Enabling learning over anonymized data, thus circumventing the privacy issues that currently prevent the reuse of information across models trained on datasets belonging to different entities (e.g., different financial institutions).
• Integrating information from different, independent and heterogenous data plataforms (e.g., key-value stores, relational and graph databases) in an automatic approach that maximizes the performance of machine learning applications.
CAMELOT was funded by some FCT, Lisboa2020, Portugal2020 and FEDER:
POCI-01-0247-FEDER-045915– Main funding
CPCA/A1/402869/2021– CAMELOT HPC (2021-2022)
CPCA/A1/5613/2020– CAMELOT HPC (2020-2021)
CPCA/A2/6009/2020– CAMELOT Cloud (2020-2021)
- Alcides Fonseca (PI)
- Guilherme Espada (PhD Student)
- Paulo Canelas Santos (PhD Student)
- Catarina Gamboa (PhD Student)
- Pedro Barbosa (PhD Student)
- Máximo Oliveira (MSc Student)
- João David (MSc Student)
- Pedro Silva (MSc Student)
- Leon Ingelse (MSc Student)
- Lukas Abelt (MSc Student)
- Francisco Pimenta (BSc Student)
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- Aeon A programming language with liquid types, focused on synthesis
- LiquidJava A library+typechecker + VSCode plugin for Java that adds Liquid Types and TypeState.
- Clinical significance of genetic variation in hypertrophic cardiomyopathy: comparison of computational tools to prioritize missense variants @ Fronteirs in Cardiovascular Medicine
- Genetic Engine: Genetic Programming for the Common Programmer @ <Programming> 2022
- Dive into LiquidJava — Extending Java with Liquid Types @ <Programming> 2022
- Genetic Engine: Grammar-Guided Genetic Programming without the Grammar @ <Programming> 2022
- Improving Machine Learning Pipeline Creation using Visual Programming and Static Analysis by João David
- Exploring a Larger Search Space for Automatic Program Repair by Máximo Oliveira
- LiquidJava: Extending Java with Refinements by Catarina Gamboa