Selection Process
Nominations announced after careful consideration by the MCBIOS nomination committee. Applicants are reviewed and weighted on a number of factors including passion for the work they do along with alignment with the conference’s goals and mission.
After announcing nominations, MCBIOS members will be able to preview all the finalists and vote for the board members (1 student member, 2 board members) by the June 2nd 2023 deadline.
2023 Board Member Nominees
Mazen Istanbouli
I have always been passionate about studying mental health disorders, striving to make a positive impact on people's lives. My accomplishments include winning two 2nd place posters at MCBIOS, receiving a prestigious ORISE internship with Walter Reed Army Institute of Research, and mentoring students at different levels in computational biology projects. As a dedicated caretaker for my centenarian grandmother for over 9 years, my genuine passion for caregiving showcases my empathetic nature. My strong leadership qualities, expertise in computational biology, and exceptional communication skills make me an invaluable board member for the conference.
Nisha Pillai
I am a Research Scientist at Mississippi State University with 1.5 years of postdoctoral experience in bioinformatics and 7 years of doctoral experience in robotics, artificial intelligence, computer vision and natural language processing. In 2023, I served on the AAAI Association for Advancement of Artificial Intelligence's Senior program committee, a tier 1 conference in the field of Artificial Intelligence. I served as a judge for poster presentations at MCBIOS 2022 and as a member of the conference planning committee at MCBIOS 2023.
Qianqian Song
Dr. Song’s research aims to advance precision medicine through the development of innovative computational methods and graph-based artificial intelligence algorithms. With a specialization in large-scale biomedical data, her expertise spans from the molecular level, including genomics and transcriptomics data, to the cutting-edge single-cell and spatial omics data at the cellular level, and to the population level with EHR data. She has designed a series of tailored deep learning and statistical methods to facilitate data representation and interpretation in complex diseases.
Vinay Raj
Dr. Vinay Raj is an Assistant professor of Bioinformatics and Public Health at UAPB. Previously, he served as the principal bioinformatics analyst in the genomics core at UAMS. His collaborative research has been published in prestigious cancer research journals. He has mentored numerous students on bioinformatics and public health research projects as part of NIH and NSF research programs. Dr. Raj serves on the editorial board of bioinformatics journals and has rich experience in serving from different bioinformatics related organizations.