{"id":243964,"date":"2026-04-21T07:10:14","date_gmt":"2026-04-21T11:10:14","guid":{"rendered":"https:\/\/today.uconn.edu\/?p=243964"},"modified":"2026-04-23T16:26:28","modified_gmt":"2026-04-23T20:26:28","slug":"farhad-imani-wins-nsf-career-award-to-build-manufacturing-systems-that-think","status":"publish","type":"post","link":"https:\/\/today.uconn.edu\/2026\/04\/farhad-imani-wins-nsf-career-award-to-build-manufacturing-systems-that-think\/","title":{"rendered":"Farhad Imani Wins NSF CAREER Award to Build Manufacturing Systems That Think"},"content":{"rendered":"

A critical challenge is\u00a0emerging\u00a0in manufacturing: how to repair and restore high-value components when current systems\u00a0can\u2019t\u00a0handle deviation. Factories are full of automation systems that perform well when processes are repetitive. The moment geometry shifts, the process changes, or defects evolve, they struggle.\u00a0<\/span>\u00a0<\/span><\/p>\n

NSF CAREER Award recipient Farhad Imani, an assistant professor in mechanical engineering at the University of Connecticut, is tackling this challenge head-on through the development of a new class of intelligent robotic manufacturing systems that can inspect parts, interpret multimodal sensor data, and reason through uncertainty.<\/span>\u00a0<\/span><\/p>\n

Imani\u2019s CAREER project, \u201cIntegrated Digital Thread for Self-Evolving Cooperative Robotics Remanufacturing,\u201d uses remanufacturing as the proving ground, but the ambition is far greater. The real target is the next generation of robotic manufacturing systems that can handle variability and make informed decisions.\u00a0<\/span>\u00a0<\/span><\/p>\n

\u201cThe next generation of manufacturing systems must do more than execute instructions,\u201d says Imani. \u201cThey need to sense, reason, and adapt when the real world stops matching the plan.\u201d<\/span>\u00a0<\/span><\/p>\n

In remanufacturing, no two components are the same. There are differences in damage, wear, and geometry, meaning a strategy that works for one part may fail on the next. This is where traditional automation begins to fall apart.\u00a0<\/span>\u00a0<\/span><\/p>\n

Imani\u2019s lab is building cooperative robotic systems capable of inspecting damage in real time, diagnosing what has changed,\u00a0determining\u00a0a feasible\u00a0repair or manufacturing strategy, and adapting as conditions change.\u00a0<\/span>\u00a0<\/span><\/p>\n

The goal is to shift from programmed automation to cognitive\u00a0automation, where machines can reason through changing scenarios rather than relying solely on predefined instructions.\u00a0<\/span>\u00a0<\/span><\/p>\n

While artificial intelligence has made significant strides in manufacturing, many current approaches still depend on static models, larger training demands, and black-box behavior that becomes fragile when conditions shift.\u00a0<\/span>\u00a0<\/span><\/p>\n

\"Researchers
Professor Imani and 3rd year Ph.D. student, Zhiling Chen, working with robotic arms in his lab. (UConn Photo\/Chris LaRosa)<\/figcaption><\/figure>\n

Imani\u2019s approach takes a different route. At the center of his project is hyperdimensional computing, a brain-inspired framework that combines multimodal sensing, engineering knowledge, physical constraints, and simulation into an interpretable decision loop.\u00a0<\/span>\u00a0<\/span><\/p>\n

This intelligence is paired with an adaptive digital twin that runs rapid \u201cwhat if\u201d scenarios as the process unfolds. This helps the system evaluate options, refine decisions, and close the loop between prediction and robotic action. The result is a manufacturing system built to adapt, not just automate.\u00a0<\/span>\u00a0<\/span><\/p>\n

Across industries like aerospace, energy, transportation, and defense, manufacturers are under pressure to do more than just produce parts at scale. They need reliable systems that can restore damaged assets,\u00a0modify\u00a0components to new specifications, intelligently respond to variation, and reduce downtime, scrape, and costly rework.<\/span>\u00a0<\/span><\/p>\n

A robotic system that succeeds in remanufacturing can improve how AI and robotics are deployed across inspection, process planning, and high-stakes manufacturing more broadly.<\/span>\u00a0<\/span><\/p>\n

\u201cFactories shouldn\u2019t just make components,\u201d Imani explains. \u201cThey should be able to intelligently restore, upgrade, and extend the life of the systems we depend on.\u201d<\/span>\u00a0<\/span><\/p>\n

For Imani, the CAREER Award is more than getting recognition for his past\u00a0work,\u00a0it is a platform to drive research on a larger scale.\u00a0<\/span>\u00a0<\/span><\/p>\n

\u201cThis award is not the finish line,\u201d Imani says. \u201cIt\u2019s the moment a bold research direction gets the runway to become real.\u201d<\/span>\u00a0<\/span><\/p>\n

Over the next five years, Imani\u2019s lab will work to develop a unified manufacturing framework by integrating cognitive intelligence, embodied robotics, multimodal sensing, and digital twin technology.<\/span>\u00a0<\/span><\/p>\n

The award also strengthens UConn Engineering\u2019s momentum in advanced manufacturing, intelligent systems, and robotics, positioning the university at the forefront of next generation industrial innovation.<\/span>\u00a0<\/span><\/p>\n

A core\u00a0component\u00a0of the CAREER Award is education and outreach. Imani\u2019s project will give UConn students hands-on experience with robotic platforms, AI-driven decision-making, sensing systems, and digital twins.<\/span>\u00a0<\/span><\/p>\n

Planned initiatives include new curriculum modules, research opportunities, and partnerships with local schools, community colleges, and industry.\u00a0<\/span>\u00a0<\/span><\/p>\n

\u201cI\u2019m not interested in training students for yesterday\u2019s factory,\u201d Imani says. \u201cWe\u2019re building engineers who can design, think, and invent the manufacturing systems of tomorrow.\u201d<\/span>\u00a0<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Automation dominates modern factories, but much of it still breaks when parts vary, damage is uncertain, and expert judgement is required. Farhad Imani\u2019s project targets this failure by developing robotic manufacturing systems that can sense change and adapt in real time<\/p>\n","protected":false},"author":224,"featured_media":243965,"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":[2719,1866,2711,2460,2648,2235],"tags":[],"magazine-issues":[],"coauthors":[2646],"class_list":["post-243964","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai","category-engr","category-emerging-technology","category-faculty","category-blue-research","category-today-homepage"],"pp_statuses_selecting_workflow":false,"pp_workflow_action":"current","pp_status_selection":"publish","acf":[],"publishpress_future_action":{"enabled":false,"date":"2026-05-08 22:01:30","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\/243964","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\/224"}],"replies":[{"embeddable":true,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/comments?post=243964"}],"version-history":[{"count":6,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/posts\/243964\/revisions"}],"predecessor-version":[{"id":244173,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/posts\/243964\/revisions\/244173"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/media\/243965"}],"wp:attachment":[{"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/media?parent=243964"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/categories?post=243964"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/tags?post=243964"},{"taxonomy":"magazine-issue","embeddable":true,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/magazine-issues?post=243964"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/coauthors?post=243964"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}