{"id":5328,"date":"2026-05-13T14:59:39","date_gmt":"2026-05-13T18:59:39","guid":{"rendered":"https:\/\/oge.mit.edu\/msrp\/?post_type=profiles&#038;p=5328"},"modified":"2026-08-13T14:46:47","modified_gmt":"2026-08-13T18:46:47","slug":"ayomide-olumide-attah","status":"publish","type":"profiles","link":"https:\/\/oge.mit.edu\/msrp\/profiles\/ayomide-olumide-attah\/","title":{"rendered":"Ayomide Olumide-Attah"},"content":{"rendered":"<div class=\"wp-block-image\">\n<figure class=\"alignleft size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"400\" height=\"599\" src=\"https:\/\/oge.mit.edu\/msrp\/wp-content\/uploads\/sites\/2\/2026\/05\/Olumide-Attah-Ayomide.jpg\" alt=\"by Corban Swain\" class=\"wp-image-5622\" style=\"aspect-ratio:1;object-fit:cover;width:200px;height:auto\" srcset=\"https:\/\/oge.mit.edu\/msrp\/wp-content\/uploads\/sites\/2\/2026\/05\/Olumide-Attah-Ayomide.jpg 400w, https:\/\/oge.mit.edu\/msrp\/wp-content\/uploads\/sites\/2\/2026\/05\/Olumide-Attah-Ayomide-200x300.jpg 200w\" sizes=\"auto, (max-width: 400px) 100vw, 400px\" \/><\/figure>\n<\/div>\n\n\n<div class=\"wp-block-group\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<p class=\"wp-block-paragraph\"><strong>Fisk University<\/strong><br>Faculty Advisors: Prof. Justin Solomon<br>Department: Electrical Engineering and Computer Science<\/p>\n<\/div><\/div>\n\n\n\n<div style=\"height:0px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Biography<\/strong><\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">Ayomide Olumide-Attah is a rising junior at Fisk University, double majoring in<br>mathematics and computer science. He is a budding computer scientist and mathematician with<br>formidable competitive problem-solving and programming skills as well as interests spanning<br>data science, AI\/ML, and quantum computing. He\u2019s explored these interests through building<br>innovative projects, participating in diverse programs, and competing in hackathons. He also<br>has extensive experience participating in competition-level math contests, which have enabled<br>him to hone formal reasoning, problem-solving, and deduction skills. Beyond his experiences,<br>he\u2019s an extremely curious individual who has always sought to answer questions and solve<br>problems, which has led him to learn more about the world. His goal is to conduct innovative<br>research at the intersection of mathematics and computer science and develop innovative<br>solutions to the world\u2019s hardest problems, one line of code at a time.<\/p>\n\n\n\n<p class=\"has-text-align-center wp-block-paragraph\"><br><strong>A Sparse Multigrid Hierarchy Construction for Linear Systems<br>Ayomide Olumide-Attah1 and Dr. Justin Solomon2<\/strong><br>1Department of Mathematics and Computer Science, Fisk University<br>2Electrical Engineering and Computer Science, Massachusetts Institute of Technology<\/p>\n\n\n\n<p class=\"has-text-align-center wp-block-paragraph\"><br>Multigrid (MG) methods are widely considered a powerful class for solving large linear<br>systems of equations that arise in many application domains, including the discretization of<br>partial differential equations (PDEs), computing surface parameterizations, fluid simulations,<br>and many others. These methods solve linear systems by restricting them to smaller domains,<br>solving them in these domains, and extending the resulting solution to the larger original space.<br>However, as observed in [Liu et al., 2021], the resulting matrices become much denser than<br>the corresponding Laplacians as one descends the hierarchy, undermining the efficiency of a<br>multigrid implementation. For our project, we propose a multigrid hierarchy construction with<br>improved sparsity properties, and we demonstrate its efficiency by implementing a multigrid<br>solver that implements our construction. Our method builds on the approach proposed by<br>[Wiersma et al., 2023] by employing strategies to improve the sparsity of the level matrices,<br>and we demonstrate that the best results are obtained when the level matrices are modified so<br>that the smallest nonzero entries are removed. We hope our work will lead to more efficient<br>multigrid solvers, which can offer significant speedups in solving linear systems.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n","protected":false},"featured_media":5622,"template":"","profile_category":[25],"class_list":["post-5328","profiles","type-profiles","status-publish","has-post-thumbnail","hentry","profile_category-2026-interns"],"acf":[],"_links":{"self":[{"href":"https:\/\/oge.mit.edu\/msrp\/wp-json\/wp\/v2\/profiles\/5328","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/oge.mit.edu\/msrp\/wp-json\/wp\/v2\/profiles"}],"about":[{"href":"https:\/\/oge.mit.edu\/msrp\/wp-json\/wp\/v2\/types\/profiles"}],"version-history":[{"count":4,"href":"https:\/\/oge.mit.edu\/msrp\/wp-json\/wp\/v2\/profiles\/5328\/revisions"}],"predecessor-version":[{"id":5832,"href":"https:\/\/oge.mit.edu\/msrp\/wp-json\/wp\/v2\/profiles\/5328\/revisions\/5832"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/oge.mit.edu\/msrp\/wp-json\/wp\/v2\/media\/5622"}],"wp:attachment":[{"href":"https:\/\/oge.mit.edu\/msrp\/wp-json\/wp\/v2\/media?parent=5328"}],"wp:term":[{"taxonomy":"profile_category","embeddable":true,"href":"https:\/\/oge.mit.edu\/msrp\/wp-json\/wp\/v2\/profile_category?post=5328"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}