All posts by erman

People, Undergrad posts

New AI unit in Math 100

Math 100 now features a new unit covering AI, including analyzing what makes ChatGPT and Gemini work, and how students can use them responsibly and effectively. These AI tools and concepts are also woven throughout the course. This new initiative was selected as part of UH’s ongoing Integrating AI into Curriculum initiative.

“By engaging directly with new AI tools, our learning assistants are not only supporting their peers but also preparing to be part of a broader shift in how technology is integrated into math education,” said UH Mānoa math Professor Monique Chyba, who co-teaches the course with Professor Elizabeth Gross. “This is about equipping the next generation to shape, rather than just follow, the future of learning.”

You can read more about Math 100’s advances in this UH News Article.

Graduate posts

Faculty and students organize professional development groups

In Fall 2025, there are two ongoing professional developments based groups at the UHM math department. Daniel Erman and Elizabeth Gross have been organizing a Brown Bag Professional Development Seminar, which covers an array of topics, and has regular guest panelists:

  1. How to make the most out of attending conferences and seminars (with Elizabeth Gross)
  2. Collaboration etiquette (with Rufus Willett)
  3. Applying for academic jobs (with Forrest Glebe and Max Hill)
  4. How to build a teaching portfolio
  5. What is “service”? Why does it matter for jobs? (with Sarah Widiasih Post)
  6. How do you build a research program? How do you decide what to work on? (with Asaf Hadari and Hailun Zheng)

Further topics will be determined by the interests of the student attendees. This group meets every other Friday from 11:30-12:30. For more information, contact Daniel Erman.

A second group is organized by PhD student Janani Lakshmanan . This is a Job Market Working Group, where PhD students get together, work on job application materials, and share thoughts, experiences, and advice. For more information, contact Janani Lakshmanan.

Graduate news, Graduate posts

GSO Awards

The UHM Graduate Student Organization offers academic enrichment awards (for conference travel or registrations, etc) and merit based awards (anonymous, peer-elected awards across several categories). Our PhD student Janani Lakshmanan recently won one of these awards!

You can read more about these awards in general here. (Lakshamanan’s award is covered in the 2024-25 report available at that link.)

And you can find more about the program through the links above.

Uncategorized

UH PhD students attend SLMath Summer Schools

Every summer, the Simons Laufer Mathematics Insitute (SLMath, formerly known as MSRI) hosts a wide array of summer schools for graduate students. In Summer 2026, two UH PhD students attended these summer schools: Janani Lakshmanan attended the “Principled Scientific Discovery with Formal Methods” school at the IBM Research Campus in Yorktown Heights, New York. And Kawika O’Connor who attended the “Topological and Geometric Structures in Low Dimensions” school in Berkeley, CA.

“The summer school brought together graduate students from all over the country at very different stages of their careers and gave us a crash course in the current frontiers of machine learning. We did a lot of hands-on learning, and it really gave me a lot more confidence in writing code. We also were invited to present our own work and make connections with researchers at IBM. “ -Janani Lakshmanan.

“It was a lot of fun meeting other graduate students at around the same point in their careers. I will admit to having quite a bit of imposter syndrome going into the summer school, but that — thankfully — dried up pretty quickly. It was very hands on, very geometric, and just an all around blast. ” – Kawika O’Connor.

We include a couple of photos below:

UH Math PhD student Janani Lakshmanan in front of Quantum System II, the most advanced quantum computer in the world right now.

Students gathering data on pendulum frequencies to feed into an AIHilbert program, a brand new machine-learning powered polynomial regression model introduced by researchers at Samsung and IBM.