{"id":243131,"date":"2026-04-02T07:15:54","date_gmt":"2026-04-02T11:15:54","guid":{"rendered":"https:\/\/today.uconn.edu\/?p=243131"},"modified":"2026-04-06T16:30:17","modified_gmt":"2026-04-06T20:30:17","slug":"uconn-engineering-professor-embraces-uncertainty-for-stronger-engineering-systems","status":"publish","type":"post","link":"https:\/\/today.uconn.edu\/2026\/04\/uconn-engineering-professor-embraces-uncertainty-for-stronger-engineering-systems\/","title":{"rendered":"UConn Engineering Professor Embraces Uncertainty For Stronger Engineering Systems"},"content":{"rendered":"

A few years after receiving\u00a0the\u00a0National Science Foundation\u00a0Early\u00a0CAREER Award,\u00a0UConn College of Engineering\u00a0Assistant Professor\u00a0Hongyi Xu is\u00a0demonstrating\u00a0how embracing uncertainty can lead to stronger, smarter engineering systems.<\/span>\u00a0<\/span><\/p>\n

Xu\u2019s research focuses on a\u00a0simple, but challenging, fact, which is that\u00a0not everything in engineering is perfectly\u00a0uniform. Many real-world materials\u00a0contain\u00a0a mix of order and randomness, a concept known as stochasticity. Rather than\u00a0designing around\u00a0that uncertainty, Xu has developed new computational tools that allow engineers to use it\u00a0intentionally, and\u00a0combine it seamlessly with ordered materials.<\/span>\u00a0<\/span><\/p>\n

\u201cTraditional engineering tries to eliminate randomness as much as possible,\u201d\u00a0says\u00a0Xu, who is\u00a0the project\u2019s PI and a\u00a0professor within\u00a0the School of Mechanical, Aerospace, and Manufacturing Engineering. \u201cOur work asks a different question: what if we can\u00a0design with\u00a0it? What if controlled randomness\u00a0actually leads\u00a0to better performance?\u201d<\/span>\u00a0<\/span><\/p>\n

At the core of the project is a novel\u00a0computational\u00a0framework that bridges predictable structures with stochastic ones, enabling engineers to create materials and systems with tailored properties. Using advanced\u00a0generative artificial intelligence\u00a0techniques, Xu and his team built a unified \u201cdesign space\u201d that allows them\u00a0and future researchers\u00a0to explore\u00a0putting together\u00a0both fully ordered and partially random configurations,\u00a0something that was previously difficult to achieve.<\/span>\u00a0<\/span><\/p>\n

\"A
Scanning electron micrograph (SEM) of a freeze-fractured nasturtium stem, showing numerous vascular bundles (Steve Gschmeissner\u2014Science Photo Library\/Getty Images).<\/figcaption><\/figure>\n

Xu\u2019s research also takes inspiration from natural materials,\u00a0which often have randomized\u00a0but sturdy\u00a0architectures, like\u00a0the cells of tree\u00a0leaves, the wings of dragonflies, or the\u00a0gills of a mushroom.<\/span><\/p>\n

The implications span a wide range of industries. Xu points to applications in\u00a0batteries and\u00a0energy storage, where\u00a0optimizing\u00a0material structure can improve battery performance, as well as in automotive design, where lightweight yet durable materials are critical.<\/span>\u00a0<\/span><\/p>\n

\u201cThese tools give us a new level of control,\u201d Xu says. \u201cWe can design systems that are not only\u00a0high-performing, but also more robust and reliable under real-world uncertainty.\u201d<\/span>\u00a0<\/span><\/p>\n

That real-world relevance has driven collaborations beyond the lab, including partnerships with leaders such as Ford Motor Company\u00a0and the\u00a0<\/span>U.S. Army<\/span><\/a>. The research also connects to broader systems like power grids and transportation networks, where managing variability is key to long-term resilience.<\/span>\u00a0<\/span><\/p>\n

Xu is currently in the fourth year of this five-year project, and the findings and collaborations have already been lucrative.<\/span>\u00a0<\/span><\/p>\n

Since the\u00a02022 NSF CAREER\u00a0grant was awarded, the project has generated significant scholarly output, including\u00a016\u00a0journal papers, four full-length refereed conference papers, and seven invited seminar\/keynote talks.\u00a0<\/span>\u00a0<\/span><\/p>\n

Xu\u2019s work has been published in journals\u00a0with high impact factors (IF)\u00a0like Advanced Energy Materials (IF: 26),\u00a0Energy & Environmental Science (IF: 31), Journal of Manufacturing Systems\u00a0(IF: 14.2), Reliability Engineering & System Safety (IF: 11), and Small (IF: 12.1), among others.<\/span>\u00a0<\/span><\/p>\n

But for Xu, the most meaningful outcomes extend beyond publications.<\/span>\u00a0<\/span><\/p>\n

Students involved in the research have earned national recognition, including multiple honors from the American Society of Mechanical Engineers, alongside strong career placements in academia and industry.\u00a0<\/span>\u00a0<\/span><\/p>\n

\"A
Students and faculty involved in the stochasticity research (Contributed photo).<\/figcaption><\/figure>\n

Zihan Wang received the prestigious ASME Design Automation Dissertation Award and first place in the ASME CIE\u00a0Hackathon, and\u00a0is now a postdoctoral researcher at Northwestern University.\u00a0Leidong\u00a0Xu, also a CIE Hackathon winner and recognized for research presentations and publications, will join Ford. Majid\u00a0Kheybari\u00a0earned distinction as an\u00a0editor\u2019s\u00a0pick in AIP Advances and has begun his academic career as an assistant professor at Saint Mary\u2019s University of Minnesota.\u00a0<\/span>\u00a0<\/span><\/p>\n

Current doctoral students continue to build on that momentum: Kiarash\u00a0Naghavi\u00a0Khanghah\u00a0has earned both a best paper award and a hackathon win through ASME, while\u00a0Zhengkun\u00a0Feng has received competitive fellowships supporting his research. At the master\u2019s level, Filip Penda is now an engineer at Newport News Shipbuilding, and William Hobson-Rhoades is pursuing a doctorate at\u00a0University\u00a0of Michigan.\u00a0<\/span>\u00a0<\/span><\/p>\n

Together, these outcomes reflect the project\u2019s strong emphasis on student development and its impact in preparing engineering leaders.<\/span>\u00a0<\/span><\/p>\n

Future research might involve more connections to cognitive science.<\/span>\u00a0<\/span><\/p>\n

Xu has also emphasized connecting research to the broader community. Through outreach efforts, the project has introduced K\u201312 students and teachers to hands-on STEAM learning, while also sharing\u00a0new design\u00a0tools with small businesses and manufacturers across Connecticut.<\/span>\u00a0<\/span><\/p>\n

\u201cBy working with educators and industry partners, we can help translate these ideas into real economic and societal impact,\u201d Xu says.<\/span>\u00a0<\/span><\/p>\n

As engineering systems grow more complex, Xu believes that embracing\u00a0(not avoiding)\u00a0uncertainty will be essential.<\/span>\u00a0<\/span><\/p>\n

\u201cStochasticity is everywhere,\u201d he says. \u201cThe challenge is learning how to work with it in a systematic way. This project shows that when we do, we can unlock entirely new possibilities for\u00a0materials\u00a0design.\u201d<\/span>\u00a0<\/span><\/p>\n

 <\/p>\n

The research conducted by Xu and his team was made possible through the NSF Division of Civil, Mechanical,\u00a0and Manufacturing Innovation, through the\u00a0Engineering\u00a0Design and Systems Engineering program.\u00a0<\/span><\/i>\u00a0<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Many real-world systems\u2014from materials to infrastructure\u2014contain a mix of order and randomness, a concept known as stochasticity<\/p>\n","protected":false},"author":185,"featured_media":243158,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_crdt_document":"","wds_primary_category":0,"wds_primary_series":0,"wds_primary_attribution":0,"footnotes":""},"categories":[1866,2711,2460,2648,2076,2235],"tags":[],"magazine-issues":[],"coauthors":[2445],"class_list":["post-243131","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-engr","category-emerging-technology","category-faculty","category-blue-research","category-research","category-today-homepage"],"pp_statuses_selecting_workflow":false,"pp_workflow_action":"current","pp_status_selection":"publish","acf":[],"publishpress_future_action":{"enabled":false,"date":"2026-04-17 22:53:27","action":"change-status","newStatus":"draft","terms":[],"taxonomy":"category","extraData":[]},"publishpress_future_workflow_manual_trigger":{"enabledWorkflows":[]},"_links":{"self":[{"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/posts\/243131","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/users\/185"}],"replies":[{"embeddable":true,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/comments?post=243131"}],"version-history":[{"count":5,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/posts\/243131\/revisions"}],"predecessor-version":[{"id":243218,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/posts\/243131\/revisions\/243218"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/media\/243158"}],"wp:attachment":[{"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/media?parent=243131"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/categories?post=243131"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/tags?post=243131"},{"taxonomy":"magazine-issue","embeddable":true,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/magazine-issues?post=243131"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/coauthors?post=243131"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}