Ciao visitor, this is Cristina! 👋
I’m a postdoc in the Data Science Institute at Brown University 🇺🇸, and I work with Prof. Stephen Bach in the BATS lab 🦇. My research focuses on developing versatile and responsible AI systems, addressing both the practical challenges of adapting models to new tasks and the critical need to ensure the ethical and safe deployment of advanced AI technologies.
I arrived at Brown as Visiting Ph.D. student and worked with Eli Upfal and Matteo Riondato. In July 2021, I defended my Ph.D. thesis in Computer Engineering from Sapienza University 🇮🇹, advised by Aris Anagnostopoulos and Stefano Leonardi.
I earned my master’s degree in Data Science at Sapienza University, after a one-year exchange in the School of Computer and Communication Sciences at EPFL 🇨🇭, where I joined Data Science Lab led by Robert West. Before that, I got a bachelor’s degree in Statistics, Economics, and Finance at Sapienza University.
📻 News
- (Sept ‘23) We found another good reason why we shouldn’t leave low-resource languages behind: they jailbreak GPT-4!
- (Sept ‘23) I’ll see you all in New Orleans! Our work on exploring strategies for using CLIP as a pseudolabeler for prompt tuning will appear in NeurIPS 2023!
- (Sept ‘23) I joined the Data Science Institute at Brown University as postdoctoral research associate!
- (May ‘23) I studied for a while how we can exploit pseudolabels in many learning settings to improve vision-language models like CLIP. Check out what we found in this new paper!
- (Feb ‘23) Register to the Woman in Data Science datathon organized by DSI at Brown University!
- (Dec ‘22) I gave a talk about Wikipedia’s structural bias at COSC-355 Network Science @ Amherst College!
- (Sept ‘22) Our paper on theoretical limitis of zero-shot learning has been accepted at NeurIPS 2022!
- (Aug ‘22) I presented TAGLETS at MLSys 2022 in Santa Clara!
- (Jun ‘22) Our work demonstrating that #MyBodyMyChoice is not uniquely associated to women’s rights after Covid-19 has received an honorable mention for the best paper award at WebSci 2022! 🏆
📝 Publications
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Low-Resource Languages Jailbreak GPT-4
NeurIPS 2023, SoLaR Workshop - 🏆 Best Paper Award (Spotlight)
Z.-X. Yong, C. Menghini, S. H. Bach
[pdf] -
Enhancing CLIP with CLIP: Exploring Pseudolabeling for Limited-Label Prompt Tuning
NeurIPS 2023
C. Menghini, A. Delworth, S. H. Bach
[pdf][code] -
Reducing polarization and increasing diverse navigability in graphs by inserting edges and swapping edge weights
Data Mining and Knowledge Discovery 2022
S. Haddadan, C. Menghini, M. Riondato, E. Upfal
[pdf] -
Tight Lower Bounds on Worst-Case Guarantees for Zero-Shot Learning with Attributes
Neurips 2022
A. Mazzetto *, C. Menghini *, A. Yuan, E. Upfal, S. H. Bach
[pdf] -
The Drift of #MyBodyMyChoice Discourse on Twitter
WebSci 2022 - 🏆 Best Paper Award Honorable Mention
C. Menghini, J. Uhr, S. Haddadan, A. Champagne, B. Sandstede, S. Ramachandran
[pdf] -
TAGLETS: A System for Automatic Semi-Supervised Learning with Auxiliary Data
Machine Learning and Systems 2022
W. Piriyakulkij, C. Menghini, R. Briden, N. V. Nayak, J. Zhu, E. Raisi, S. H. Bach
[pdf] -
Algorithms for fair k-clustering with multiple protected attributes
Operations Research Letters 2021
M. Bohm, A. Fazzone, S. Leonardi, C. Menghini, C. Schwiegelshohn
[pdf] -
RePBubLik: Reducing polarized bubble radius with link insertions
WSDM 2021 - 🏆 Best Paper Award Honorable Mention
S. Haddadan, C. Menghini, M. Riondato, E. Upfal
[pdf] -
How Inclusive Are Wikipedia’s Hyperlinks in Articles Covering Polarizing Topics?
Big Data 2021
C. Menghini, A. Anagnostopoulos, E. Upfal
[pdf] -
Spectral Relaxations and Fair Densest Subgraphs
CIKM 2021
A. Anagnostopoulos, L. Becchetti, A. Fazzone, C. Menghini, C. Schwiegelshohn
[pdf] -
Wikipedia Polarization and Its Effects on Navigation Paths
Big Data 2019
C. Menghini, A. Anagnostopoulos, E. Upfal
[pdf] -
Compiling Questions into Balanced Quizzes about Documents
CIKM 2018
C. Menghini, J. Dehler-Zufferey, R. West
[pdf]