Date: November 13, 2025
Speakers: Bradley Emi
Title: Can AI Text be Detected?
Abstract: Is it possible for algorithms to distinguish AI-generated text from large language models like ChatGPT from genuine human writing? And if so, what are the statistical signals
within AI-generated text that make it different?

In this talk, we will first focus on recent research explaining why AI text is different from human writing. We will present two recent notable works: Measuring AI Slop in Text (Chaib et. al., 2025) and People who frequently use ChatGPT for Writing Tasks are Accurate and Robust Detectors of AI-Generated Text (Russell et. al., 2025).

We will then go over how Pangram’s software is able to accurately detect AI-generated writing algorithmically. Finally, we will preview Pangram’s state-of-the-art technology which is able to distinguish AI-edited or AI-assisted text from fully human and fully AI generated writing, in our recent preprint, EditLens: Quantifying the Extent of AI Editing in Text (Thai et. al., 2025).

Date: December 11, 2025
Speakers: Johann Thiel
Title: Turing Tumble
Abstract: Turing Tumble is a marble-powered computer. Despite its relatively simple design, this machine can do a lot. In this meeting we will solve various logic puzzles and explore its computational capabilities.

Date: April 10, 2025
Speakers: Thomas Johnstone
Title: Envy-free cake-cutting
Abstract: We’ve all had this problem: Mom made delicious cake, and we each want as much as possible of that cake. What should we do? If there are only two siblings who want cake, then the maybe fairest method is the “I cut, you choose” procedure, a method known and used since antiquity. However, when there are three siblings who want cake, the problem becomes much more difficult and interesting. This question sparked an entire new research area called envy-free cake-cutting, and a solution of this question for three people was discovered only about 60 years ago. This talk will be accessible to anyone who likes cake and knows the pain of envy.

Date: Oct. 17, 2024
Speakers: Johann Thiel
Title: The Quake III Algorithm
Abstract: The small chunk of unusual code above was found in the source code for Quake III Arena (1999). This algorithm computes the reciprocal of the square root of a number very quickly. In this talk, we will discuss the mathematics and clever programming trickery need to understand how it works.

Date: April 18, 2024
Speakers: Alex Iosevich
Title: An elementary perspective on exact signal recovery
Abstract: Consider a signal and suppose that it is sent via its Fourier transform. Suppose that some of the transmission is lost, in the sense that the some values are unobserved for some set. The question we ask is, can we still recover the original signal exactly. It turns out that under some reasonable assumptions on the size of and how sparse the original signal is, the answer to our question is affirmative. The talk will be completely self-contained and does not require any knowledge of mathematics beyond pre-calculus.

Date: March 14, 2024
Speakers: Mark Hughes
Title: Can AI learn to perform research in pure mathematics?
Abstract: With the rapid advancement of AI impacting multiple scientific fields, it is natural to inquire about the role machine learning will play in the development of mathematics. In this talk, I will discuss several avenues through which AI has been used, is being used, and may be used to advance research in pure mathematics. These applications range from solving Olympiad-level geometry problems to searching for counterexamples to conjectures and constructing formal proofs.

Date: November 9, 2023
Speakers: Alfred Posamentier
Title: Mathematics Wonders
Abstract: In this talk, we will demonstrate the many wonders of mathematics that most math majors have not experienced and that can generate a genuine love for mathematics. The intent is to show students that this is what the job of a math teacher is. That is, not just to teach the curriculum but also to motivate the students to love mathematics. All of this material will be on a pre-college level covering the fields of number theory, algebra, and geometry.

Date: November 10, 2022
Speakers: Ronald Michael Baecker
Title: Ethical Tech Startups: Principles for Success
Abstract: As of 2020, 14 of the world’s 50 wealthiest billionaires made their money in technology. Microsoft alone has created over 10,000 millionaires. Unicorns are privately held startup companies worth over $1 billion. Approximately 2000 unicorns have emerged since 2015. Of the 50 with the greatest valuation, at least 39 are digital tech firms or companies leveraging software.Although many digital tech products now cause much evil, you can create ethical tech startups — both “ethical tech” startups and ethical “tech startups”. Based on my experience creating 5 software startups and 36 years of learning and teaching, I will outline 7 principles for success:

1. Seek solutions that solve important problems or that leverage opportunities created by new technologies.
2. Develop competitive advantage through proprietary technology and distinctive competence.
3. Validate your strategy and products by user experience design at every stage from idea to shipping product.
4. Think about your strengths; leverage them in creating an identity and communicate this to customers.
5. Design your business model and go-to-market strategy; devote significant resources to digital marketing.
6. Plan and project your finances carefully with a forecasting model; raise funds expeditiously but vigorously.
7. Hire only the best; motivate and guide them with inspirational leadership by a capable management team.

I shall illustrate these principles using examples of successful ethical tech ventures. I will highlight examples of ethical and unethical behavior throughout the presentation.

Date: April 14, 2022
Speakers: Brian Holliday
Title: Life After City Tech
Abstract: Brian Holliday is a City Tech graduate from the Applied Math program. In this talk, Brian will discuss his current work, as well as his journey from student to data scientist for the CUNY Institute for State and Local Governance.

Date: October 14, 2021
Speakers: Charles Meyers
Title: Trustworthy Machine Learning
Abstract: At this week’s math club, we will discuss state-of-the-art modelling techniques and their weaknesses with an NYCCT alumni who is now a research scientist in Sweden, studying for
his PhD. He will demonstrate why linear algebra, multivariable calculus, discrete
mathematics, numerical methods, statistics, and optimization techniques are critical to
understanding artificial intelligence and its pitfalls. From there, we will draw concrete
connections between the theory you learn in the classroom and the real-world
applications. As an added bonus, he will highlight the tools and skills needed to turn your
NYCCT STEM degree into expertise, financial freedom, endless recruitment emails, and the ability to work remotely in the country of your choosing.