On My Radar

I am thrilled to share that I will be presenting a poster at the Princeton Workshop on Optimization, Learning, and Control. The presentation will take place tomorrow, and I'll be discussing the application of quantum linear algebra in optimization and machine learning. As I'm delving into this fascinating area, I am eager to learn more and exchange ideas with fellow researchers.

Additionally, I am pleased to announce the defense of my thesis scheduled for July 2, 2024, at 10 AM EST. The defense will be hosted online, and I warmly invite all who are interested to join and participate. Here is the link to join.

I am thrilled to announce the publication of our paper, "Efficient Use of Quantum Linear System Algorithms in Inexact Infeasible IPMs for Linear Optimization," in a special issue of the Journal of Optimization Theory and Application. This issue honors the significant contributions of Professors Kees Roos and Florian Potra on their milestone birthdays.

Our paper explores the integration of quantum linear algebra with interior point methods, assessing both the benefits and challenges. We also demonstrate how classical iterative refinement techniques can enhance quantum methods, improving complexity and precision.

Special thanks to my coauthors, Prof. Tamás Terlaky and Dr. Ramin Fakhimi, for their invaluable collaboration. This paper is not just a contribution to the field but also pays homage to the pioneering efforts of Prof. Roos and Prof. Potra on interior point methods.

I am presenting today on "Recent Advances in Quantum Interior Point Method" at the 2024 Annual Quantum Symposium. This event is organized by the NC State Quantum Initiative, the IBM Quantum Innovation Center at NC State. A recording of the presentation will be available here.

I'm thrilled to share that I recently presented our paper on "Iterative Refinement Methods for Semidefinite Optimization" at the 2024 INFORMS Computing Society Conference in Houston, engaging in enriching discussions and receiving insightful questions. Alongside my colleague Zeguan Wu, we successfully organized two sessions dedicated to the fascinating realms of quantum computing and optimization, which were met with great enthusiasm. I’d like to express my heartfelt gratitude towards the conference organizers for awarding me a travel grant, making this incredible experience possible.

I'm thrilled to announce that I will be presenting a talk at the 2024 SIAM Conference on Parallel Processing for Scientific Computing (PP24). The topic of my presentation is "Novel Inexact Feasible Quantum Interior Point Methods for Linear Optimization." If you're attending this conference, make sure not to miss it! Discover how quantum computers can accelerate the solution of linear optimization problems.

Exciting news alert! Today, I conquered the PhD general exam like a boss! Huge shoutout to my fantastic committee members for their insightful comments – they're like the Jedi Masters of academia. 🌟 Now, onto the next adventure: the epic thesis defense! I'm gearing up for battle, armed with knowledge and a dash of humor. Massive thanks to my awesome advisor for guiding me through this crazy journey. Let's do this, thesis! 

I'm thrilled to announce that our paper, titled "An inexact feasible interior point method for linear optimization with high adaptability to quantum computers," has been selected as the runner-up for the INFORMS Computing Society Ph.D. Student Paper Award. I want to extend my heartfelt thanks to the committee for this recognition. This achievement would not have been possible without the collaboration of my esteemed co-authors Ramin Fakhimi, Zeguan Wu, and my incredible advisor Prof. Tamás Terlaky.