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Nando Fioretto

@nandofioretto.bsky.social
1.4K followers 519 following 39 posts

Assistant Professor of Computer Science at the University of Virginia. I work on Responsible AI (differential privacy & fairness) and machine learning for science and engineering (differentiable optimization) | nandofioretto.github.io

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Nando Fioretto @nandofioretto.bsky.social · 31/05/2025
Excited to share that our work "Neuro-Symbolic Generative Diffusion Models" received a DARPA Disruptive Idea Award at NeuS 2025! 🌟 This work pushes toward integrating symbolic reasoning and generative modeling to meet the safety and robustness demands of scientific applications.
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Nando Fioretto @nandofioretto.bsky.social · 29/04/2025
If you are at #NAACL2025 check out our oral: 🔥 "Speculative Diffusion Decoding: Accelerating Language generation through diffusion" We use discrete diffusion as a drafting model to speed up #LLM inference---up to 7.2x faster over standard generation 🚀 tiny.cc/xt0i001
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Reposted by Nando Fioretto
Hank Green @hankgreen.bsky.social · 02/03/2025
We are experiencing an assault on science unparalleled by anything I’ve seen in my life. It’s not one issue or another anymore, the entire institution is under attack by the most powerful individuals in the country. This Friday, where will you be? standupforscience2025.org
standupforscience2025.org
STAND UP FOR SCIENCE
March 7, 2025. Washington DC and nationwide. Because science is for everyone.
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Nando Fioretto @nandofioretto.bsky.social · 02/03/2025
The Privacy Preserving AI workshop is back! And is happening on Monday. I am excited about our program and lineup of invited speakers! Check out the program here: ppai-workshop.github.io
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Nando Fioretto @nandofioretto.bsky.social · 27/02/2025
If you are at #AAAI2025 come and see our oral presentation today in Room 122A at 11:15AM. The paper "Fairness Issues and Mitigations in (Differentially Private) Socio-demographic Data Processes" shows how sampling errors in survey data can introduce (1/2)
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Nando Fioretto @nandofioretto.bsky.social · 13/02/2025
Learning to Solve Differential Equation Constrained Optimization Problems was awarded a spotlight at ICLR 2025 ✨ Congrats to my student Vincenzo Di Vito! We show how to build neural surrogates to solve constrained optimization problems coupled with system dynamics.
arxiv.org
Learning To Solve Differential Equation Constrained Optimization Problems
Differential equations (DE) constrained optimization plays a critical role in numerous scientific and engineering fields, including energy systems, aerospace engineering, ecology, and finance, where o...
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Nando Fioretto @nandofioretto.bsky.social · 01/02/2025
I just want to scream at my LaTeX compiler today! 😭
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Nando Fioretto @nandofioretto.bsky.social · 15/12/2024
What are your biggest takes from attending #NeurIPS24? Where do you think the field is moving/should move?
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Nando Fioretto @nandofioretto.bsky.social · 14/12/2024
Is there a Machine Learning floor in my hotel?
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Nando Fioretto @nandofioretto.bsky.social · 12/12/2024
Tomorrow (Dec 12) poster #2503! Come talk with us about our #NeurIPS work on constrained diffusion models!
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Nando Fioretto @nandofioretto.bsky.social · 09/12/2024
I'll be at #NeurIPS from Thursday to Saturday. DM me I'd you like to chat about generative ML for science or responsible AI broadly!
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Nando Fioretto @nandofioretto.bsky.social · 03/12/2024
Huge congratulations to James Kotary on defending his dissertation with flying colors!! 👏🔥🎉 Title of his dissertation: "Integrating Constrained Optimization with Machine Learning to Enhance Data-Driven Decision Making" j-kota.github.io
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Nando Fioretto @nandofioretto.bsky.social · 28/11/2024
Receiving reviews on Thanksgiving day is brutal! Should you be thankful for the reviews received? 🤔
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Nando Fioretto @nandofioretto.bsky.social · 23/11/2024
🆘Help needed! Are you working on Privacy (from a Technical (e.g., Differential Privacy), Policy, or Law perspective)? Please give your availability to review for PPAI (ppai-workshop.github.io) if you can! We'd highly appreciate it! 🙏 forms.gle/dqjVsBsR2y81...
ppai-workshop.github.io
Sixth AAAI Workshop on Privacy-Preserving Artificial Intelligence
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Nando Fioretto @nandofioretto.bsky.social · 21/11/2024
You ask and PPAI listens! We have extended the submission deadline of a few days, now papers are accepted until **November 29**! The AAAI Workshop on Privacy-Preserving Artificial Intelligence (PPAI-25) (ppai-workshop.github.io) looks forward to receive your best work!
ppai-workshop.github.io
Sixth AAAI Workshop on Privacy-Preserving Artificial Intelligence
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Nando Fioretto @nandofioretto.bsky.social · 18/11/2024
Excited to share our #NeurIPS2024 work on combining diffusion models with constrained optimization to generate data adhering to constraints and physical principles (with guarantees!) will be a spotlight at the workshop on AI for Accelerated Materials Design! 🔗 arxiv.org/abs/2402.03559
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Nando Fioretto @nandofioretto.bsky.social · 19/11/2024
#DifferentialPrivacy starter pack by @thegautamkamath.bsky.social
go.bsky.app
Differential Privacy Researchers
Join the conversation
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Reposted by Nando Fioretto
arxiv cs.CR @arxiv-cs-cr.bsky.social · 19/08/2024
Joonhyuk Ko, Juba Ziani, Saswat Das, Matt Williams, Ferdinando Fioretto Fairness Issues and Mitigations in (Differentially Private) Socio-demographic Data Processes arxiv.org/abs/2408.08471
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Juba Ziani @jubaz.bsky.social · 14/11/2024
Going to advertise this here too, but we have a new book on differential privacy led by Nando Fioretto and Pascal Van Hentenryck! I was asked to contribute to the first, intro chapter, available here: arxiv.org/abs/2411.04710 Full book available soon!
arxiv.org
Differential Privacy Overview and Fundamental Techniques
This chapter is meant to be part of the book "Differential Privacy in Artificial Intelligence: From Theory to Practice" and provides an introduction to Differential Privacy. It starts by illustrating ...
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Reposted by Nando Fioretto
Aaron Roth @aaroth.bsky.social · 18/11/2024
If you are on the job market, and work on the kinds of topics that might be published in FORC ("Foundations of Responsible Computing"), fill out this form and get on the job list. This covers mathematical research on privacy, fairness, and related topics.
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Nando Fioretto @nandofioretto.bsky.social · 18/11/2024
Excited to share our #NeurIPS2024 work on combining diffusion models with constrained optimization to generate data adhering to constraints and physical principles (with guarantees!) will be a spotlight at the workshop on AI for Accelerated Materials Design! 🔗 arxiv.org/abs/2402.03559
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Nando Fioretto @nandofioretto.bsky.social · 17/11/2024
I am giving a talk on differential privacy and fairness at the Workshop on Cyber Security in High Performance Computing (at SC 2024) today. Stop by if you are attending and interested! sc24.conference-program.com/presentation...
sc24.conference-program.com
Presentation – SC24 Schedule
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Emile van Krieken @emilevankrieken.com · 11/11/2024
I made a starter pack with the people doing something related to Neurosymbolic AI that I could find. Let me know if I missed you! go.bsky.app/RMJ8q3i
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Emily Tucker @emilyltucker.bsky.social · 08/11/2024
New starter pack if you're looking for the #orms community on here: go.bsky.app/SvBND16 Also if you have recommendations of people to add, feel free to send them my way.
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Nando Fioretto @nandofioretto.bsky.social · 16/11/2024
The AAAI Workshop on Privacy-Preserving Artificial Intelligence (PPAI-25) is back! 🔗 ppai-workshop.github.io **Submission deadline: Nov, 24** Topics of particular interest: - policy considerations for privacy; - privacy in AI agents and LLMs; - societal impact of privacy within AI.
ppai-workshop.github.io
Sixth AAAI Workshop on Privacy-Preserving Artificial Intelligence
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Differential Privacy Papers @dppapers.bsky.social · 13/11/2024
Differential Privacy Overview and Fundamental Techniques Ferdinando Fioretto, Pascal Van Hentenryck, Juba Ziani arxiv.org/abs/2411.04710
http://arxiv.org/abs/2411.04710
Differential Privacy Overview and Fundamental Techniques
Ferdinando Fioretto, Pascal Van Hentenryck, Juba Ziani
This chapter is meant to be part of the book "Differential Privacy in
Artificial Intelligence: From Theory to Practice" and provides an introduction
to Differential Privacy. It starts by illustrating various attempts to protect
data privacy, emphasizing where and why they failed, and providing the key
desiderata of a robust privacy definition. It then defines the key actors,
tasks, and scopes that make up the domain of privacy-preserving data analysis.
Following that, it formalizes the definition of Differential Privacy and its
inherent properties, including composition, post-processing immunity, and group
privacy. The chapter also reviews the basic techniques and mechanisms commonly
used to implement Differential Privacy in its pure and approximate forms.
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