To all Computer Science student, See below a Seminar for this week in the ISE Department. Best, Sharon Sharon Kinder-Potter Graduate Program Coordinator Virginia Tech Department of Computer Science 3210 Torgersen Hall; (MC 0106) 620 Drillfield Drive Blacksburg, VA 24061 540.231.6932/ mailto:skpotter@vt.edu skpotter@vt.edu https://cs.vt.edu/ https://cs.vt.edu **BE COMMITTED. BE WELL** Zoom Link: https://virginiatech.zoom.us/j/83861560159 Abstract: Semidefinite and polynomial optimization (SDO and PO) are topics of great theoretical and practical interest, with numerous applications in theoretical computer science, control theory, and statistics. Due to advances in efficient interior point methods, there has been lots of interest in SDO, as an emerging computational tool, in PO and quantum information sciences. However, the existence of an exact algorithm with polynomial complexity for both SDO and PO is still an open problem. The focus of my talk is computational complexity in SDO and PO, through the lens of real algebraic geometry. While SDO can be solved "efficiently" using path-following interior point methods, PO can be approximately solved using a converging hierarchy of SDO relaxations. I show how recent developments in theoretical and algorithmic real algebraic geometry can be utilized to quantify complexity of the central path, and improve error bounds that are significant in proving convergence rate of numerical optimization schemes for PO. I end this talk by illuminating promising interactions between continuous optimization, real algebraic geometry, and data science, which form the backbone of my research program. Bio: Ali Mohammad Nezhad is a Postdoctoral Research Associate in the Department of Mathematical Sciences at Carnegie Mellon University (CMU). He is also affiliated with the Hoskinson Center for Formal Mathematics at CMU. He was previously a Golomb Visiting Assistant Professor in the Department of Mathematics at Purdue University, a Visiting Scholar in the Department of Industrial and Systems Engineering at Lehigh University, and a postdoctoral research associate in the School of Industrial Engineering at Purdue University. Ali received his PhD degree in Industrial and Systems Engineering from Lehigh University, and his Master degree in Industrial Engineering from Sharif University of Technology, Iran. Ali's research is supported by the collaborative NSF Grant CCF-2128702 and CCF-2128527 (Purdue and Lehigh universities). The main theme of his research is computational complexity in continuous optimization, computational optimization, and their algorithmic implications for data science and engineering. In recent years, the focus of his research has been centered on different facets of stability, complexity, and computation in semidefinite and polynomial optimization through the lens of (real/complex) algebraic geometry and algebraic topology. Ali recently developed interest in computational topology and its interplay with computational optimization, quantum computing, and machine learning. Ali has been an organizer of several special sessions and mini-symposiums for Informs, SIAM, JMM, and AMS sectional meetings. He is currently organizing "Optimization, Algebra, and Geometry" seminar series in the Math Department at CMU.