Nov. 28, 2023
Noah Marchel
My research interests are in the use pervasive computing and AI for the healthcare domain, with particular focus on novel ad-hoc machine learning models of multi-modal sensor and electronic medical records as components for augmented decision support interfaces. The primary application of my research is for adaptive model building using continual machine learning and meta-modelling techniques to generate precision health analytics. I have additional interest in the computational mediation of human motor functioning and rehabilitation through remote analysis and verification for clinical therapy and impact of biotelemetry monitoring on quality of life for aging populations.
Nov. 27, 2023
Katrina Boles
Prior to receiving a MS in Data Science & Analytics at Mizzou in 2020, Katrina was a motion graphics artist and art director in marketing and communications. She is currently a PhD candidate and a Data Analyst with ECHO Autism. Her research interests include: human-computer interaction, user-centered design, and visualizing personal sensor data. She is a member of the Precision Smart Technologies for Rapid Translation (Precision START) lab and her dissertation research focus is on the user-centered design of an integrated sensor interface to support remote care coordination for the Age-friendly Sustainable Smart and Equitable Technologies for Aging in Place…
Nov. 27, 2023
Mohammad Beheshti
I’m a Health Informatician and PhD student in Health Informatics, specializing in data analytics and data science, with a keen focus on clinical and population data analysis. Currently, I’m a Graduate Research Assistant at the Missouri Cancer Registry and Research Center, where I collaborate closely with the database team to perform the ETL process for cancer data collected from across the state of Missouri. My work also involves building predictive models and utilizing data to enhance patient outcomes. I’m deeply passionate about using data to drive positive changes in healthcare.
Oct. 24, 2023
Sonia Akter
Sonia is currently pursuing her doctoral research in Health Informatics. Her research interests focus on artificial intelligence (AI), machine learning (ML), deep learning (DL), large language models (LLM), and analyzing various types of healthcare-related data, including electronic health records (EHR), cognitive data, and sensor data, to predict clinical outcomes. Sonia earned her BS in Forestry from the Institute of Forestry and Environmental Sciences at Chittagong University (CU) in Bangladesh. She then received a European Union (Erasmus Mundus) Scholarship to pursue her MS in European Forestry, which provided her the unique opportunity to immerse herself in diverse academic environments across several…
Oct. 24, 2023
Olabode Ogundele
I was born and raised in Lagos, Nigeria. I also had my undergraduate education in Nigeria. The Informatics PhD journey has been a huge learning curve, and the unlimited opportunities are inspiring. There are more fun things than studying and researching. Beyond my academic pursuits, I am an ardent supporter of Arsenal Football Club of England. I am either cheering my team or playing a soccer match myself. I enjoy hiking and the compelling narratives and dramatic landscapes of Western movies.
Oct. 24, 2023
Trevor Mandy
As a Columbia Native I’ve been lucky enough to call Mizzou my home for 26 years! Coming from a background in healthcare management and finance, my focus area is health and biomedical informatics. My research interests include the application of AI models to large-scale EHR data to predict clinical outcomes and derive the cost-effectiveness of clinical practices. Currently, I am researching the effectiveness of Ivacaftor and the rest of the -caftor family of medications in their ability to moderate weight gain/loss in patients with Cystic Fibrosis, as compared to traditional interventions such as high-fat diets and therapeutic interventions. Towards the…
April 12, 2022
Ai-Ling Lin
Dr. Lin is an expert on translational neuroimaging of brain vascular and metabolic function in aging, Alzheimer’s disease, stroke and traumatic brain injury. She developed and applied magnetic resonance imaging and spectroscopy and positron emission tomography to test nutritional and pharmacologic approaches for protecting the brain from aging, traumatic brain injury, and Alzheimer’s disease. She also has applied artificial intelligence to identify markers that are highly predictable for Alzheimer’s disease development and progression and applied gut microbiome analyses to study gut-brain interaction underlying Alzheimer’s disease.
Sep. 29, 2021
Hua Qin
I am an environmental and resource sociologist with emphasis on human population dynamics and sustainable development. I have a diverse academic background in sociology, demography, geography, human ecology, environmental science, as well as mixed and spatial methodological research. My interdisciplinary training and research experience focus on analyzing social and cultural aspects of natural resources and environmental systems. I was a postdoctoral research fellow supported by the NSF-funded Data Conservancy project at the National Center for Atmospheric Research (NCAR). This project focused on data practices and curation across life, earth, and social sciences. While at NCAR, I also engaged in the…
July 29, 2021
Ram Raghavan
I am broadly interested in spatially-enabled computational epidemiology of vector-borne and infectious diseases and applications of geospatial approaches for enhancing animal/public health. I extensively use Geographic Information System (GIS) and remote-sensing concepts in my research alongside geo-statistical, correlative modeling, and Bayesian approaches for understanding spatio-temporal dynamics of non-stationary epidemiological processes. Our current and prior research has identified important spatio-temporal patterns and spatial determinants for vector/water-borne zoonotic diseases from climatic, environmental, and socio-economic themes. Increasingly, my research strives to identify consistencies in complex meteorological variable associations with vector-borne diseases through the utilization of high-resolution ground-based and NASA Earth Observing System (EOS)…