Physics & Math Student Colloquium: Andrew Lee ’99 (Sept. 29 at noon in Olin 268)

Andy Lee, Bucknell ’99, will speak on his path from a degree in Physics to a career in Finance and how his undergraduate training influences his current work, including: the analysis that he works on and how it relates to physics/math (the system and the methods like Monte Carlo simulations); and how he gets from the analytics to financial decisions (fairly high level).

Open to all students and faculty; pizza will be provided…please bring your own water.

“Using Maths to Save The World”, Colloquium by Prof. Helen Greatrex; Thurs. Sept 15 at noon in Olin 268

Bucknell Mathematics Student Colloquium Series

Thurs, Sept. 15 | Noon-12:50PM  | Olin 268

Using Maths to Save The World
presented by Helen Greatrex, Professor of Geography and Statistics, Penn State University

ABSTRACT: Droughts kill thousands of people each year, especially in countries like Somalia where there is conflict and very little water to start off with.  Humanitarian experts often have to decide which places need the most help and alongside working with local communities, they also have to know how much rain has fallen. But how do you map rainfall in places where it’s too dangerous to gather data from weather-stations? Or in the vast spaces where we don’t have any weather stations at all?  
We turn to satellites! In this colloquium, we will chat about how simple mathematics can turn “space-photos” into useful weather information, and what happens when different satellites disagree…
Arrive early for free pizza!

“LSH Schemes (and how to improve them)”, Bucknell Machine Learning Association (MLA) Talk by Prof. Keegan Kang Monday Sept. 5 at 5.45pm at in the Traditional Reading Room (BERT 213).

The Bucknell MLA will hold its first meeting on Monday 9/5 at at 5.45pm in the Traditional Reading Room (BERT 213), for members to get to know each other and share their passion for machine learning. Prof. Keegan Kang will give an introductory talk on LSH Schemes.

ABSTRACT: There are some challenges with traditional machine learning in a Big Data world. Locality Sensitive Hashing (LSH) schemes are able to mitigate some of these challenges. The idea of LSH schemes will be briefly introduced in this talk by looking at an example of them: sign random projections. This will be followed briefly by an illustration of how LSH schemes can be improved, before concluding with several fun research areas using these schemes.

Bagels, Coffee, and Data Science! (Thurs 9/8 10am-noon, MacDonald Commons 104)

Bagels, Coffee, & Data Science! (Event with Axtria)

Interested in a career in data science? Come network with Bucknell alumni who work for one of the biggest players in the industry and learn about all things data science!

Thursday, September 8th
10:00 AM – 12:00 PM
MacDonald Commons 104
Feel free to come and go as you please

Bucknell Alumni:
Erin Ditmar ’18 (Chemical Engineering)
Caroline Edelman ’18 (Applied Mathematics)
Hannah Jarosinski ’21 (Mathematics)
Brendan Lowery ’22 (Business Analytics)