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Area Engineering

Data-centric AI: Dataset augmentation techniques for bias and data quality improvement

azienda Thesis in external company    


keywords ALGORITHM FAIRNESS, ARTIFICIAL INTELLIGENCE, DATA ETHICS, DATA QUALITY, DATA SCIENCE, EXPLAINABLE AI, HUMAN-COMPUTER INTERACTION, SOFTWARE ENGINEERING, SYNTHETIC DATA

Reference persons MARCO TORCHIANO, ANTONIO VETRO'

Research Groups DAUIN - GR-16 - SOFTWARE ENGINEERING GROUP - SOFTENG, DAUIN - GR-22 - Nexa Center for Internet & Society - NEXA

Thesis type EXPEIRMENTAL, IN COMPANY, INDUSTRIAL, RESEARCH / EXPERIMENTAL, RESEARCH THESIS WITH A COMPANY, RESEARCH, INNOVATIVE

Description Clearbox AI Control Room has a feature to generate synthetic datasets for dataset augmentation. The thesis work is focused in the experimentation of techniques that can help detect bias in the original datasets and mitigate them by augmenting the original dataset using synthetic points. The project will require identifying the types of bias within a dataset and identifying intervention mechanisms to remove the bias using synthetic data generation methods.

Clearbox AI is an innovative SME, incubated in I3P, winner of the National Innovation Award (PNI 2019) in the ICT category and the EU Seal of Excellence awarded by the European Commission. Clearbox AI is developing a unique and innovative technology ("AI Control Room"), which allows to put into production artificial intelligence models that are robust, explainable and monitorable over time.

See also  https://www.clearbox.ai

Required skills Good programming skills and basic knowledge of common data analytics tools and techniques. Grade point average equal to or higher than 26 will play a relevant role in the selection.

Notes When sending your application, we kindly ask you to attach the following information:

- list of exams taken in you master degree, with grades and grade point average
- a résumé or equivalent (e.g., linkedin profile), if you already have one
- by when you aim to graduate and an estimate of the time you can devote to the thesis in a typical week


Deadline 30/11/2023      PROPONI LA TUA CANDIDATURA




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