SIAM Student Chapter Seminar: Difference between revisions

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|Eza [https://www.linkedin.com/in/enkhzaya-enkhtaivan-20a15222b/ Enkhtaivan]
|Eza [https://www.linkedin.com/in/enkhzaya-enkhtaivan-20a15222b/ Enkhtaivan]
|Industry talk
|Industry talk
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|4/14
|911 Van Vleck
|[https://people.math.wisc.edu/~ywu495/ Yandi Wu]
|Lessons Learned from Applying to Summer Internships  
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'''March 31, Qifan Chen:''' In this talk, we develop a new type of Runge-Kutta (RK) discontinuous Galerkin (DG) methods for solving hyperbolic conservation laws. Compared with the standard RKDG methods, the new methods feature improved compactness and allow simple boundary treatment. Limiters are applied only at the final stage for the control of spurious oscillations and further improves efficiency. Their connections with the Lax-Wendroff DG schemes and the ADER DG schemes are also investigated. Numerical examples are given to confirm that the new RKDG schemes are as accurate as standard RKDG methods, while being more compact and cost-effective, for certain problems including two-dimensional Euler systems of compressible gas dynamics.  
'''March 31, Qifan Chen:''' In this talk, we develop a new type of Runge-Kutta (RK) discontinuous Galerkin (DG) methods for solving hyperbolic conservation laws. Compared with the standard RKDG methods, the new methods feature improved compactness and allow simple boundary treatment. Limiters are applied only at the final stage for the control of spurious oscillations and further improves efficiency. Their connections with the Lax-Wendroff DG schemes and the ADER DG schemes are also investigated. Numerical examples are given to confirm that the new RKDG schemes are as accurate as standard RKDG methods, while being more compact and cost-effective, for certain problems including two-dimensional Euler systems of compressible gas dynamics.  
'''April 14, Yandi Wu:''' Between October of last year and March of this year, I applied to over 100 internships in machine learning/data science. In this talk, I will touch upon the realities of applying to tech internships as a math PhD (during a time that Big Tech is struggling), and the key takeaways from my experience. In particular, I would like to focus on what you can do to strengthen your resume, what types of interview questions you might be asked and how to prepare for them, and other useful information about the application process (including timelines and competitiveness) that I wish I had known before I applied.


==Past Semesters==
==Past Semesters==

Revision as of 20:46, 31 March 2023


Spring 2023

Date (1 PM unless otherwise noted) Location Speaker Title
2/3 911 Van Vleck Yunus Tuncbilek Value Investing: Get Rich “Slowly”
2/10 Zoom and 911 Van Vleck Yinda Li Industry talk
2/17 911 Van Vleck Rebecca Gasper (Epic) Two Careers in Mathematics, from Experience
2/24 Zoom and 911 Van Vleck Alisha Zachariah No Free Lunches: what’s your tradeoff?
3/3 Zoom and 911 Van Vleck Niudun Wang Industry talk
3/10 Zoom and 911 Van Vleck Kristina Wheatman (Penn State Applied Research Lab) Happy Accidents: Finding the Heuristic to an Optimal Assignment Problem
3/31 Zoom and 911 Van Vleck Qifan Chen(https://qifan-chen.github.io) The Runge–Kutta discontinuous Galerkin method with compact stencils for hyperbolic conservation laws
4/7 Zoom and 911 Van Vleck Eza Enkhtaivan Industry talk
4/14 911 Van Vleck Yandi Wu Lessons Learned from Applying to Summer Internships  
4/28 Zoom and 911 Van Vleck Peter Mueller Industry talk

Abstracts

February 3, Yunus Tuncbilek: I will talk about value investing and why, in many ways, mathematicians are better suited to be value investors than the general public or even the institutional investors. The talk should be informative and enjoyable for any person who wants to increase their income over a long period of time without doing much work.

February 10, Yingda Li: In this talk, I will begin with a brief intro of my background, followed by a discussion of my journey to my current role as a Research Scientist/Machine Learning Engineer in industry. Finally, I will illustrate the day-to-day duties of a RS/MLE at Meta.

February 17, Rebecca Gasper: There are so many careers in mathematics! Rebecca Gasper (Ph.D. Applied Mathematical and Computational Sciences, University of Iowa) decided to be a math professor by the end of her first calculus class. From tutoring through college and graduate school, preparation and luck, things fell into place. So what changed? She talks about her personal experience first in academia and then in corporate America, from pure math to data science, and gracefully changing her path. Plenty of time will be reserved for Q&A, so bring your questions about getting hired, workload, and culture in each “world.”

February 24, Alisha Zachariah: Any choice of career path comes with its own set of tradeoffs. In my current role as a data scientist at Amazon, my team identifies which products Amazon Retail should carry on the basis of their long-term profitability, in the US and worldwide. In this presentation, I would like to talk candidly about the pros and cons of this professional path, from compensation to #techlayoffs and everything in between.

March 3, Niudun Wang: Having to make a call could be stressful, especially when there's seemingly endless choices and the stake is high. I will be offering from my perspective the pitfalls and hinder sights as a puzzled graduate student that you might find relatable. El Psy Kongroo.

March 10, Kristina Wheatman: Do you ever feel like all your major life decisions keep you running in circles? In Happy Accidents, I discuss ideas for how to maneuver through the chaos and confusion of “grey” crossroads and unpleasant detours within mathematics and academia, especially when “black” and “white” options seem out of reach or prove to be disappointing. I share how I am able to build my own customized career in research by allowing myself some grace and flexibility. Ultimately, I am continuously finding ways to improve my life’s heuristic by acknowledging the “perfect optimal” exists solely to motivate us on our mathematical journey.  

March 31, Qifan Chen: In this talk, we develop a new type of Runge-Kutta (RK) discontinuous Galerkin (DG) methods for solving hyperbolic conservation laws. Compared with the standard RKDG methods, the new methods feature improved compactness and allow simple boundary treatment. Limiters are applied only at the final stage for the control of spurious oscillations and further improves efficiency. Their connections with the Lax-Wendroff DG schemes and the ADER DG schemes are also investigated. Numerical examples are given to confirm that the new RKDG schemes are as accurate as standard RKDG methods, while being more compact and cost-effective, for certain problems including two-dimensional Euler systems of compressible gas dynamics.  

April 14, Yandi Wu: Between October of last year and March of this year, I applied to over 100 internships in machine learning/data science. In this talk, I will touch upon the realities of applying to tech internships as a math PhD (during a time that Big Tech is struggling), and the key takeaways from my experience. In particular, I would like to focus on what you can do to strengthen your resume, what types of interview questions you might be asked and how to prepare for them, and other useful information about the application process (including timelines and competitiveness) that I wish I had known before I applied.

Past Semesters

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