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Department of Biomedical Informatics

Methods Areas

Artificial Intelligence and Machine Learning Theory and Methods

Nasim Katebi, Hyeokhyen Kwon, Samaneh Nasiri, Saima Rathore, Matthew Reyna, Reza Sameni, Yun Wang

Advancing foundational theories and methodologies in AI and ML to enhance learning algorithms and decision-making process.  

 

Artificial Intelligence and Machine Learning Applications

Selen Bozkurt, Nasim Katebi, Hyeokhyen Kwon, Babak Mahmoudi, Samaneh Nasiri, Saima Rathore, Matthew Reyna, Abeed Sarker, Yun Wang

Implementing AI and ML techniques across various domains to address real-world biomedical and clinical problems. 

 

Bias, Ethics, and Fairness

Selen Bozkurt, Azra Ismail, Hyeokhyen Kwon

Investigating ethical implications, addressing bias, and measuring and supporting fairness in AI systems. 

 

Biostatistics and Bioinformatics

Selen Bozkurt, J. Lucas McKay, Samaneh Nasiri, Matthew Reyna

Applying statistical methods and computational tools to analyze biological data for insights into biological processes and personalized medicine.  

 

Biomedical Signal and Image Processing

Nasim Katebi, Babak Mahmoudi, J. Lucas McKay, Samaneh Nasiri, Saima Rathore, Reza Sameni, Yun Wang

Developing signal processing and image analysis techniques for extracting meaningful information from biomedical data. 

 

Clinical Research

Selen Bozkurt, J. Lucas McKay, Saima Rathore, Yun Wang

Systematic investigation of medical treatments, interventions, and outcomes to generate evidence-based knowledge for healthcare practices. 

Computer Vision

Hyeokhyen Kwon, J. Lucas McKay, Tony Pan, Yun Wang

Developing algorithms for machines to interpret and understand visual information, enabling applications such as image recognition and object detection. 

 

Edge Computing and Tiny Machine Learning

Nasim Katebi, Hyeokhyen Kwon, Babak Mahmoudi

Developing machine learning models for efficient processing on edge devices with limited resources, facilitating decentralized applications. 

 

High-Performance Computing and Databases

Babak Mahmoudi, Tony Pan, Matthew Reyna

Designing and optimizing computing systems and databases for large-scale data processing, storage, and retrieval. 

 

Human-Computer Interaction

Azra Ismail, Babak Mahmoudi, Tony Pan

Studying and designing user interfaces to improve usability, accessibility, and the overall user experience of technology systems. 

 

Natural Language Processing

Selen Bozkurt, Abeed Sarker

Developing algorithms and models for computers to understand, interpret, and generate human language for biomedical applications. 

 

Application Areas

Brain Health  

Selen Bozkurt, Azra Ismail, Hyeokhyen Kwon, Babak Mahmoudi, J. Lucas McKay, Samaneh Nasiri, Saima Rathore, Yun Wang

Understanding, monitoring, and enhancing brain health to address neurological disorders and cognitive well-being.

 

Cancer

Selen Bozkurt, Saima Rathore, Matthew Reyna

Enhancing cancer research, diagnosis, treatment, and personalized medicine to improve detection and outcomes for individuals affected by various forms of cancer. 

Cardiovascular Disease

Qiao Li, Babak Mahmoudi, Samaneh Nasiri, Matthew Reyna, Abeed Sarker

Studying and managing data related to cardiovascular health, including prevention, diagnosis, and treatment of heart diseases.

Global/Public/Rural Health and Social Determinants of Health

Azra Ismail, Nasim Katebi, Abeed Sarker

Addressing health disparities and promoting global, public, and rural health by leveraging informatics to analyze and integrate data related to social determinants, healthcare accessibility, and public health interventions.

Maternal-Child Health

Azra Ismail, Nasim Katebi, Reza Sameni, Yun Wang

Enhancing the health and well-being of mothers and children by analyzing data related to maternal care, childbirth, and pediatric health, especially in low-and-middle-income countries (LMICs) and underrepresented and underserved groups. 

Pain, Addiction, and Palliative Care

Selen Bozkurt, Abeed Sarker

Studying and managing pain, addiction, and palliative care to improve patient outcomes and support effective pain management strategies.