{"id":236009,"date":"2025-10-07T07:30:28","date_gmt":"2025-10-07T11:30:28","guid":{"rendered":"https:\/\/today.uconn.edu\/?p=236009"},"modified":"2025-10-07T13:14:12","modified_gmt":"2025-10-07T17:14:12","slug":"uconn-researchers-receive-nsf-career-awards","status":"publish","type":"post","link":"https:\/\/today.uconn.edu\/2025\/10\/uconn-researchers-receive-nsf-career-awards\/","title":{"rendered":"UConn Researchers Receive NSF CAREER Awards"},"content":{"rendered":"

Five UConn faculty members received prestigious CAREER Awards from the National Science Foundation (NSF) in the 2025 cycle. <\/span>\u00a0<\/span><\/p>\n

“Our students come to UConn to learn from the very best,” says UConn President Radenka Maric. “These awards are a testament to the quality of research being done at UConn, and to our institution-wide commitment to excellence. I am very proud of our progress, and with faculty members like these, I look forward to reaching even greater heights in the years to come.\u201d<\/p>\n

The Faculty Early Career Development (CAREER) Program is\u00a0a\u00a0highly competitive\u00a0and prestigious\u00a0award for early-career scientists.\u00a0NSF CAREER funding supports researchers in\u00a0establishing\u00a0a\u00a0strong basis for\u00a0a\u00a0lifetime of leadership in research\u00a0and education.\u00a0<\/span>\u00a0<\/span><\/p>\n

These awards represent a $3 million total investment by the NSF in UConn\u2019s early career faculty. <\/span>\u00a0<\/span><\/p>\n

Each project includes a significant educational and\/or outreach element such as training undergraduate and graduate students, hosting seminars to share research, collaborating with stakeholders, and developing courses related to the work. <\/span>\u00a0<\/span><\/p>\n

The faculty members who received the awards in the 2025 cycle are:<\/p>\n

\"Headshot
Daniel Angl\u00e9s-Alc\u00e1zar, Associate Professor, Physics (UConn Photo)<\/figcaption><\/figure>\n

Daniel Angl\u00e9s-Alc\u00e1zar, Associate Professor, Physics, College of Liberal Arts and Sciences. \u201cPushing the Frontiers of Galaxy Evolution Modeling with Multi-Scale and Empirically Constrained Hydrodynamic Simulations\u201d\u00a0 <\/span><\/b>\u00a0<\/span><\/p>\n

Through this\u00a0award,\u00a0Angl\u00e9s-Alc\u00e1zar\u00a0will develop improved simulations of galaxy formation\u00a0and evolution.\u00a0<\/span>\u00a0<\/span><\/p>\n

Angl\u00e9s-Alc\u00e1zar\u2019s project is concerned with\u00a0two levels of\u00a0simulations\u00a0\u2013 extremely high-resolution models of\u00a0individual\u00a0galaxies (like our own Milky way)\u00a0from the Big Bang\u00a0to the present day,\u00a0and big-picture\u00a0simulations that\u00a0take into\u00a0account\u00a0many\u00a0galaxies\u00a0and their large-scale environment\u00a0with much less detail.\u00a0<\/span>\u00a0<\/span><\/p>\n

Angl\u00e9s-Alc\u00e1zar\u00a0will use these simulations, constituting thousands of\u00a0plausible universes,\u00a0to train machine learning models\u00a0to be\u00a0able to extract key physical parameters related to the origin of our universe.\u00a0These simulations will\u00a0also help\u00a0astronomers better interpret observations\u00a0and understand the\u00a0detailed\u00a0physics of galaxy formation.<\/span>\u00a0<\/span>\u00a0<\/span><\/p>\n

\u201cWe\u2019re interested in what galaxies can tell us\u00a0about the fundamental properties of the universe,\u201d\u00a0Angl\u00e9s-Alc\u00e1zar\u00a0says.\u00a0\u201cWe\u2019re going to generate these very large data\u00a0sets\u00a0and use them to train machine learning models that will be\u00a0able to extract\u00a0the fundamental\u00a0parameters\u00a0that govern\u00a0the universe,\u00a0despite the fact that we still don\u2019t fully understand the physics of galaxy formation.\u201d<\/span>\u00a0<\/span><\/p>\n

Francesco Carbone, Assistant Professor, Mechanical Engineering, College of Engineering. \u201cCAREER: The Role of Electric Charges and PAHs in Molecular Clustering and Soot Inception in Laminar Premixed Flame\u201d<\/span><\/b><\/p>\n

\"Headshot
Francesco Carbone, Assistant Professor, Mechanical Engineering (UConn photo)<\/figcaption><\/figure>\n

Carbone\u2019s project will develop a model to predict soot formation.\u00a0<\/span>\u00a0<\/span><\/p>\n

Specifically,\u00a0Carbone\u2019s research will lead to\u00a0a\u00a0better understanding of the role electric charges\u00a0play\u00a0in how\u00a0<\/span>Polycyclic\u00a0Aromatic Hydrocarbons (PAHs), carcinogenic compounds\u00a0produced from burning organic matter like fossil fuels or wood, cluster to form soot.\u00a0<\/span>\u00a0<\/span><\/p>\n

This work will support efforts to reduce the environmental\u00a0and human health impacts of\u00a0soot\u00a0emissions,\u00a0which\u00a0are\u00a0a\u00a0feature of many modern technologies,\u00a0including\u00a0car engines\u00a0and manufacturing.\u00a0<\/span>Improving predictions of soot formation will support the development of cleaner combustors\u00a0for use in these sectors.<\/span>\u00a0<\/span>\u00a0<\/span><\/p>\n

Diego Cerrai, Assistant Professor, Civil and Environmental Engineering, College of Engineering. \u201cAPEX-STORM: Advancing the Preparedness to Extreme Winter Storms Through Outage and Restoration Model\u201d<\/span><\/b>\u00a0<\/span><\/p>\n

\"Headshot
Diego Cerrai, Assistant Professor, Civil and Environmental Engineering (UConn Photo)<\/figcaption><\/figure>\n

This\u00a0award will support\u00a0Cerrai\u2019s\u00a0work on\u00a0an Outage Prediction Model (OPM) for\u00a0power\u00a0outages\u00a0winter storms.\u00a0<\/span>\u00a0<\/span><\/p>\n

This project focuses\u00a0on better understanding\u00a0snow\u00a0and ice\u00a0accretion on infrastructure\u00a0during winter storms.\u00a0This understanding, in turn,\u00a0will enable\u00a0the\u00a0improvement of the OPM in\u00a0forecasting\u00a0accretion,\u00a0and\u00a0more\u00a0accurately predicting power outages\u00a0and restoration\u00a0timelines.<\/span>\u00a0<\/span><\/p>\n

\u201cThe goal here is to predict snow\u00a0and ice\u00a0accretion on powerlines, because those\u00a0are very correlated to power outages,\u201d\u00a0Cerrai\u00a0says.<\/span>\u00a0<\/span><\/p>\n

Cerrai will also improve modeling of road conditions during storms to help road crews move to restore power more safely and effectively.\u00a0<\/span>\u00a0<\/span>\u00a0<\/span><\/p>\n

Cerrai\u00a0is collaborating with power companies\u00a0and decision-makers to help them understand how to best use the\u00a0OPM through this grant.\u00a0<\/span>\u00a0<\/span><\/p>\n

Yao Zheng, Associate Professor, Statistics, College of Liberal Arts and Sciences. \u201cNew Frontiers in Time Series Analysis\u201d <\/span><\/b>\u00a0<\/span><\/p>\n

\"Headshot
Yao Zheng, Associate Professor, Statistics<\/figcaption><\/figure>\n

Zheng will develop new statistical methods to better\u00a0analyze today\u2019s increasingly complex time series data. Time series data\u00a0is\u00a0any data\u00a0observed\u00a0over time, like temperature or GDP.<\/span>\u00a0<\/span><\/p>\n

Such data\u00a0may involve many variables\u00a0at once,\u00a0contain\u00a0non-linear relationships, shift over time,\u00a0arrive\u00a0at different frequencies, or be incomplete \u2014 making it harder for statisticians\u00a0and decision-makers to extract reliable insights.<\/span>\u00a0<\/span><\/p>\n

Zheng will integrate established statistical frameworks with contemporary machine learning\u00a0approaches, with\u00a0an emphasis on statistical inference. The project\u00a0aims to\u00a0advance innovation in time series\u00a0analysis, bridge the gaps between interpretability, uncertainty quantification,\u00a0and black-box\u00a0algorithms,\u00a0and promote the use of time series data\u00a0collected from diverse sources.<\/span>\u00a0<\/span><\/p>\n

\u201cPushing the boundaries of time series\u00a0analysis is our goal,\u201d Zheng says. \u201cOur team wants to incorporate the best of machine learning while retaining the unique strengths of statistical methods.\u201d<\/span>\u00a0<\/span><\/p>\n

Junbo Zhao, Electrical and Computer Engineering, College of Engineering. \u201cCAREER: A New Robust Power System Dynamic Estimation Paradigm with High Penetration of Black-box Inverter-based Resources: Theory, Algorithms, and Applications\u201d <\/span><\/b>\u00a0<\/span><\/p>\n

Zhao is now faculty\u00a0at Dartmouth College.<\/span>\u00a0<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Five early career UConn faculty received NSF CAREER Awards to support their research, education, and outreach efforts<\/p>\n","protected":false},"author":147,"featured_media":236011,"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":[2275,2429,1866,2226,2460,2668,2076,2235,2227,2233],"tags":[],"magazine-issues":[],"coauthors":[2277],"class_list":["post-236009","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-academic-affairs","category-awards-scholarships","category-engr","category-clas","category-faculty","category-institute-enviro-energy","category-research","category-today-homepage","category-uconn-edu-homepage","category-university-news"],"pp_statuses_selecting_workflow":false,"pp_workflow_action":"current","pp_status_selection":"publish","acf":[],"publishpress_future_action":{"enabled":false,"date":"2026-05-10 08:22:26","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\/236009","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\/147"}],"replies":[{"embeddable":true,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/comments?post=236009"}],"version-history":[{"count":6,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/posts\/236009\/revisions"}],"predecessor-version":[{"id":236131,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/posts\/236009\/revisions\/236131"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/media\/236011"}],"wp:attachment":[{"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/media?parent=236009"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/categories?post=236009"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/tags?post=236009"},{"taxonomy":"magazine-issue","embeddable":true,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/magazine-issues?post=236009"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/coauthors?post=236009"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}