{"id":64361,"date":"2025-01-09T07:35:31","date_gmt":"2025-01-09T12:35:31","guid":{"rendered":"https:\/\/blogarchive.utc.edu\/news\/?p=64361"},"modified":"2025-01-15T07:53:32","modified_gmt":"2025-01-15T12:53:32","slug":"model-forecasting-utc-mathematicians-research-going-global","status":"publish","type":"post","link":"https:\/\/blogarchive.utc.edu\/news\/2025\/01\/model-forecasting-utc-mathematicians-research-going-global\/","title":{"rendered":"Model forecasting: UTC mathematician\u2019s research going global"},"content":{"rendered":"
\"Dr.

Dr. Xiunan Wang served as lead author for a recent paper published in the prestigious SIAM Journal on Applied Mathematics, in which she proposed a novel discrete inverse method for estimating the transmission rates of infectious diseases. Photo by Angela Foster.<\/p><\/div>\n

University of Tennessee at Chattanooga Department of Mathematics Assistant Professor Xiunan Wang is drawing international recognition for her work in mathematical modeling to forecast the spread of infectious diseases.<\/p>\n

Wang, who joined UTC in August 2021 and specializes in mathematical biology, has been garnering significant attention in North America and abroad. Her innovative research was recently highlighted in an article by the Society for Industrial and Applied Mathematics (SIAM), one of the three major U.S. math organizations with international memberships.<\/p>\n

She has served as lead author for a recent paper published in the prestigious SIAM Journal on Applied Mathematics<\/strong><\/a>, in which she proposed a novel discrete inverse method for estimating the transmission rates of infectious diseases.<\/p>\n

\u201cHer research is getting a good deal of press coverage, including outlets like the CBC in Canada and BioSpace in the United States,\u201d said Dr. Chris Cox, head of the UTC Department of Mathematics. \u201cTo get an article published in one of the SIAM journals is a big deal.\u201d<\/p>\n

Originally from Tieling, a city in northeastern China, Wang said she developed her passion for applied mathematics early on during her undergraduate studies at Southwest University in Chongqing, China\u2014where she earned a bachelor\u2019s degree in mathematics and applied mathematics and a master\u2019s degree in applied mathematics.<\/p>\n

\u201cIn my second year, I attended a mathematical modeling contest and won a prize,\u201d she recalled. \u201cI collaborated with a team of my classmates and found it very interesting.\u201d<\/p>\n

Wang then traveled to Canada to continue her education. She received her Ph.D. in applied mathematics from Memorial University of Newfoundland in 2017 and then spent one year as a postdoctoral researcher at the University of Western Ontario.<\/p>\n

She started her postdoc fellowship at the University of Alberta in September 2018 and was there nearly three years before coming to UTC.<\/p>\n

\u201cAt the University of Alberta, I broadened my research area, including not only epidemiology but also ecology,\u201d she said, \u201cbecause there are some deeper connections between epidemiology and ecology.\u201d<\/p>\n

\"Dr.

Dr. Xiunan Wang, who joined the UTC faculty in 2021, specializes in mathematical biology.<\/p><\/div>\n

Wang\u2019s research took on new importance in 2020 with the onset of the COVID-19 pandemic.<\/p>\n

\u201cWe had an urgent need to forecast how many people are infected each day in the United States or Canada,\u201d she said. \u201cWe developed a hybrid method combining the strengths of differential equations and machine learning to forecast how many people were infected each day.\u201d<\/p>\n

The forecast, called the \u201cdiscrete inverse method,\u201d served as a bridge between differential equations and machine learning.<\/p>\n

She collaborated with University of Alberta Professor Hao Wang, the Canada Research Chair (Tier 1) in Mathematical Biosciences and director of the Interdisciplinary Lab for Mathematical Ecology and Epidemiology, and applied the method to forecast transmission rates of various infectious diseases\u2014including COVID-19, influenza and measles.<\/p>\n

The researchers showed that the properties of transmissibility and number of infections can be quite different.<\/p>\n

\u201cUsually the data on the website, given by the CDC or some health department, is about how many people are infected each day, but they never tell the value of the transmission rates,\u201d Wang said. \u201cThe value of transmission rates are not observable and cannot be recorded\u2014and that is where we, as mathematicians, can help.<\/p>\n

\u201cThe forecast is quite accurate. Hopefully that can provide some guidance for policymakers to design some control measures for the disease.\u201d<\/p>\n

Ironically, Wang\u2019s arrival at UTC was delayed by a year due to pandemic-related visa issues.<\/p>\n

\u201cMaybe it was not good for me to have delays to start here,\u201d Wang said, \u201cbut the good thing is \u2026 the one more year that I stayed at the University of Alberta, I learned new methods, including machine learning. That was the first time that I had access to it.\u201d<\/p>\n

Wang has quickly made her mark since arriving on campus, Cox said.<\/p>\n

\u201cHer contributions have been recognized both locally and internationally and she has published 24 peer-reviewed papers,\u201d Cox said. \u201cTo have 24 papers published in refereed journals \u2026 referee journals have very high standards. For many faculty, that\u2019s a lifetime of work. To be honest with you, that\u2019s about how many papers I have published.\u201d<\/p>\n

Cox has 40 years of higher education experience.<\/p>\n

\u201cBut it\u2019s more than just the research. Xiunan\u2019s done a great job teaching and the students like her a lot. They recognize that she cares about them and she\u2019s just a very warm individual,\u201d Cox continued. \u201cShe\u2019s basically firing on all cylinders for what we expect of a faculty member. We are very fortunate to have Xiunan at UTC.\u201d<\/p>\n

Deborah Barr, administrative specialist for the Department of Mathematics, echoed those sentiments.<\/p>\n

\u201cBeing an only child, she lights up when we talk about her family and culture,\u201d Barr said. \u201cShe is incredibly observant and intelligent. She always brings a thoughtful perspective to our conversations and I love how her curious, research-driven mind shines.\u201d<\/p>\n

Learn more<\/h4>\n

Visit UTC<\/a><\/p>\n

UTC Department of Mathematics<\/a><\/p>\n

Discrete Inverse Method for Extracting Disease Transmission Rates from Accessible Infection Data<\/a><\/p>\n

How to apply<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

UTC Department of Mathematics Assistant Professor Xiunan Wang is drawing international recognition for her work in mathematical modeling to forecast the spread of infectious diseases. Her innovative research was recently highlighted in an article by the Society for Industrial and Applied Mathematics, one of the three major U.S. math organizations with international memberships.<\/p>\n

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