About me

I am a Quantitative Researcher at Two Sigma in New York. In 2020-2022, I was a Goldstine Fellow at IBM Research in New York. In 2020, I completed my PhD at Princeton University under the supervision of Amir Ali Ahmadi. Before joining Princeton, I graduated from Ecole Polytechnique.

I am broadly interested in Polynomial Optimization, Dynamical Systems & Control, and Machine Learning. You can learn more about my work by having a look at my papers. In my spare time, I make Machine Learning and Optimization videos with a strong emphasis on building intuition with visual explanations.

You can contact me at: bachir009 [at] gmail [dot] com

2022

I joined Two Sigma as a Quant Researcher.

2021

New video on Kalman Filters
New video on Newton’s method in optimization

2020

Slides I used for my Ph.D. dissertation defense.
New paper on motion planning using SDPs.
New video on Learning Dynamical Systems with Side Information.
I will be a Goldstine Fellow at IBM Thomas J. Watson Research Center starting in September.
The recording of my talk at MIT (Friday March 20^th, 2020) is now available. Video, Slides.
Our recent paper on “Learning with Side Information” has been accepted for an oral presentation at the L4DC conference.
Slides for recent talk at Oberwolfach.

2019

I received the Princeton SEAS Award for Excellence.
Cemil and I are organizing a session at INFORMS. Drop by if you are attending the conference.
I will be presenting in the IOS Award Presentations session at INFORMS in Seattle.
Recent talk on Generalized Cauchy-Schwarz Inequalities and his proof that all convex quaternary quartics are sums of squares. Video
I was a Keynote speaker at the Canadian Undergraduate Mathematics Conference.
Excited to have won honorable mention in the 2019 INFORMS Optimization Society Student Paper Prize Competition, for my paper Time-Varying Semidefinite Programs.