Mathematician

Author

Speaker

Noah Giansiracusa (PhD in math from Brown University) is a tenured associate professor of mathematics and data science at Bentley University, a business school near Boston. After publishing the book How Algorithms Create and Prevent Fake News in July 2021 (about which Nobel Prize-winning economist Paul Romer said "It's a joy to read a book by a mathematician who knows how to write... There is no better guide to the strategies and stakes of this battle for the future"), Noah has gotten more involved in public writing/speaking and policy discussions concerning data-driven algorithms and their role in society. He's appeared on cable TV and BBC radio, written for Washington Post, Scientific American, TIME, Barron's, Boston Globe, Wired, Slate, Ms. Magazine, and Fast Company, and been quoted in a range of newspapers. Noah is currently working on a second book, a popular math book forthcoming with Riverhead Books (an imprint of Penguin).

Noah's CV/resume.

To discuss speaking engagements, please email: ngiansiracusa@bentley.edu

Follow me on Twitter @ProfNoahGian

Media

Op-Eds Authored:

Interviews:

Profiles: 

Quoted in: 

with President Leonel Fernández of the Dominican Republic

with Robert McNamara

Speaking Engagements

To inquire about booking me, please email: ngiansiracusa@bentley.edu

Books

How Algorithms Create and Prevent Fake News is available from Amazon and the publisher Apress (a division of Springer Nature) and other book sellers.

Blurbs

"It's a joy to read a book by a mathematician who knows how to write, even when it tells the discouraging tale of a business model targeted digital advertising that is hijacking the tech sector and destroying its soul. With no hype, little jargon, and precise explanations, the author describes both the conquests the ad-tech empire made by deploying more powerful algorithms and the preparations rebels are making to fight algorithms with algorithms. There is no better guide to the strategies and stakes of this battle for the future."

—Paul Romer, Nobel Laureate, University Professor in Economics at NYU, and former Chief Economist at the World Bank


"By explaining the flaws and foibles of everything from Google search to QAnon and by providing level-headed evaluations of efforts to fix them Noah Giansiracusa offers the perfect starting point for anyone entering the maze of modern digital media."

—Jonathan Rauch, senior fellow at the Brookings Institution and contributing editor of The Atlantic


"Noah’s book brings the refreshingly impartial, data-driven content one gets from a lucid mathematics professor. The scale of reach enabled by technology means algorithms are the only viable operational approach. Mastering their limitations and moderating the commercial interests they serve is the responsibility of all those who work in data science. The effects of algorithms on the fabric of society could be comparable to carbon emissions on global warming. We have a chance to act early. Highly recommended reading."

—Leda Braga ("the most powerful woman in hedge funds"), founder and CEO of Systematica Investments


"You can read a hundred writers bemoaning the pollution of the infosphere; Noah Giansiracusa is one of the few who dares takes you behind the curtain to see the gears and guts of the fake news machine, and the competing algorithms that aim to counterbalance it."

Jordan Ellenberg, bestselling author of How Not To Be Wrong and Shape and John D. MacArthur Professor of Mathematics, University of Wisconsin


"A wonderful book! Very approachable, very informative, a very important contribution to understanding the interaction of computing and misinformation."

—Grady Booch, Chief Scientist for Software Engineering at IBM Research


"The issues surrounding AI and misinformation are some of the most complicated – and important – we face. Giansiracusa helps us understand and confront them."

Jonathan Zittrain, George Bemis Professor of International Law and Professor of Computer Science, Harvard University


"Imagine Genghis Khan with an AK-47 – that's what cutting-edge technology and computer algorithms have put in the hands of the next generation of liars, tyrants, and autocrats. Through the use of social media bots, deep fakes, and computer-assisted writing, fake news is now much more threatening and insidious than the "yellow journalism" of old; through the weaponization of technology, you won't even know that it's happening. Numerous TV pundits decry the assault on truth these days, but how many really understand its deep roots in information technology? To fight back, we not only have to go after the liars, but also the truth-assault weapons they have at their fingertips. Read this book to understand just how scary things have gotten over the last decade, but also how those of us who want to defend truth, facts, and evidence can employ the tools of technology to fight back."

—Lee McIntyre, author of Post-Truth


"Misinformation and deepfakes are the unique social-technological challenges of the era of social media and deep learning that every information consumer should be aware of. The book by Noah Giansiracusa provides a comprehensive yet concise account of this complex multi-facet problem, from its very cause to its impact and potential solutions. The book strikes a superb balance between readability and accuracy in the description of the core technologies."

—Siwei Lyu, SUNY Empire Innovation Professor of Computer Science and Engineering, University at Buffalo.


"AI is ushering in breakthroughs in just about every industry. Yet there is a dark side:  fake news. So what can be done? Well, Noah Giansiracusa’s book is the answer. He provides an engaging look at fake news – along with the cutting-edge technologies like GPT-3 and deepfake GANs – and shows the various tools that can fight it. This book should be a priority for anyone looking at AI."  

Tom Taulli, author of Artificial Intelligence Basics: A Non-Technical Introduction


Reviews

Review-essay in the Los Angeles Review of Books by Pulitzer Prize finalist Nicholas Carr on Jonas Bendiksen's "Book of Veles" and the deepfakes chapter of my book.

Review for the Math Association for America (MAA) by Bill Wood

Short review in the Notices of the American Mathematical Society (AMS) by Katelynn Kochalski

Recommended summer reading by the MAA

 Papers

Pure Math

Algebraic Geometry

Fibonacci, golden ratio, and vector bundles

Mathematics 9 no. 4 (2021).

Chow quotients of Grassmannians by diagonal subtori 

with Xian Wu.  Proceedings of the Facets in Algebraic Geometry conference in honor of William Fulton's 80th birthday, to appear (2020).

Equations for point configurations to lie on a rational normal curve

with Alessio Caminata, Han-Bom Moon, and Luca Schaffler. Advances in Mathematics 340 (2018), 653-683.

Modular interpretation of a non-reductive Chow quotient

with Patricio Gallardo.  Proceedings of the Edinburgh Mathematical Society 61 no. 2 (2018), 457-477.

A simplicial approach to the effective cone of \bar{M}_{0,n}

with Brent Doran and Dave Jensen. International Mathematics Research Notices no. 2 (2017), 529-565.

Projective linear configurations via non-reductive actions

with Brent Doran. Preprint on arXiv.

The dual complex of \bar{M}_{0,n} via phylogenetics

Archiv der Mathematik 106 no. 6 (2016), 525-529.

Factorization of point configurations, cyclic covers and conformal blocks

with Michele Bolognesi. Journal of the European Mathematical Society 17 (2015), 2453-2471. 

On Kapranov's description of \bar{M}_{0,n} as a Chow quotient

with W.D. Gillam. Turkish Journal of Mathematics 38 (2014), 625-648. 

GIT compactifications of M_{0,n} and flips

with Dave Jensen and Han-Bom Moon.Advances in Mathematics 248 (2013), 242-278.

Conformal blocks and rational normal curves

Journal of Algebraic Geometry 22 (2013), 773-793.

The cone of type A, level one conformal blocks divisors

with Angela Gibney. Advances in Mathematics 231 (2012), 798-814.

GIT compactifications of M_{0,n} from conics 

with Matthew Simpson. International Mathematics Research Notices no. 14 (2011), 3315-3334.

Tropical Geometry/Matroids

The universal tropicalization and the Berkovich analytification 

with J.H. Giansiracusa. Kybernetica 58 no.5 (2022), 790-815.

Point configurations, phylogenetic trees, and dissimilarity vectors

with Alessio Caminata, Han-Bom Moon, and Luca Schaffler.Proceedings of the National Academy of Sciences (PNAS) 118 n. 12 (2021).

Matroidal representations of groups

with Jacob Manaker. Advances in Mathematics 366 (2020).

A module-theoretic approach to matroids 

with Joshua Mundinger and Colin Crowley. Journal of Pure and Applied Algebra 224 no. 2 (2020), 894-916.

A Grassmann algebra for matroids

with J.H. Giansiracusa.Manuscripta Mathematica 156 no. 1 (2018), 187-213.

Equations of tropical varieties

with J.H. Giansiracusa.Duke Mathematics Journal 165 no. 18 (2016), 3379-3433.

Miscellaneous

Experimental study of energy-minimizing point configurations on spheres

group project led by Henry Cohn. Experimental Mathematics 18 no. 3 (2009), 257-283.

Applied/Interdisciplinary

Topological Data Analysis/Machine Learning

Persistent homology machine learning for fingerprint classification

with Bob Giansiracusa and Chul Moon. Proceedings of the 18th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2019), Boca Raton, FL, USA, 2019, 1219-1226.

Persistence terrace for topological inference of point cloud data

with Chul Moon and Nicole Lazar. Journal of Computational and Graphical Statistics 27 no. 3 (2018), 576-586.

Math and Law

Branching on the bench: Quantifying division in the Supreme Court with trees

Constitutional Political Economy (2022), https://doi.org/10.1007/s10602-022-09360-2.

An evolutionary view of the U.S. Supreme Court

Mathematical and Computational Applications 26 no 2 (2021), 1-31.

Computational geometry and the U.S. Supreme Court

with Cameron Ricciardi. Mathematical Social Sciences 98 (2019), 1-9.

Spatial analysis of U.S. Supreme Court 5-to-4 decisions

with Cameron Ricciardi. Preprint on arXiv.

Geometry in the courtroom

with Cameron Ricciardi. American Mathematical Monthly 125 no. 10 (2018), 867-877.

Teaching the quandary of statistical jurisprudence: a review-essay on the book Math on Trial

Journal of Humanistic Mathematics 6 no. 2 (2016), 207-224.

Miscellaneous

Predicting financial crises with tree leaves

with Chase Cicchetti. Submitted.

The mathematics of misinformation

Notices of the American Mathematical Society, 69 no. 10 (2022), 1707-1715.

Predicting friendships and other fun machine learning tasks with graphs

American Mathematical Society Feature Column.

Trust your instincts when opportunity arises

Notices of the American Mathematical Society 68 no. 3 (2021), 372-375.

From Poland to Petersburg: The Banach-Tarski paradox in Bely's modernist novel

with Anastasia Vasilyeva. Annals of Language and Literature 4 no. 3 (2020), 1-8.

Mathematical symbolism in a Russian literary masterpiece

with Anastasia Vasilyeva. The Mathematical Intelligencer 40 no. 3 (2018), 2-11.

When mathematical reasoning gets murky

The Phoenix (op-ed in Swarthmore student newspaper, response to John Fan).

Finding, and sharing, mathematical beauty in the world

Wisaarkhu Special volume 1 topic 2 (2020).

Policy aware geospatial data

with P. Kishor and O. Seneviratne.Accepted in, but not presented at, ACMGIS 2009. arXiv.CS/1304.5755