Faculty

• 

  Ozkan Aydemir, PhD

  Our access to genetic data continues to increase as the genomics technologies advance, so does our need to have the appropriate tools to make sense of these data. I am interested in adapting the existing computational tools to new data sets as well as developing new software, especially in multi-omics data integration and interpretation, to elucidate our understanding of the effects of genetic variation on a wide range of human diseases including type 1 diabetes, neurodegenerative disorders,  malaria and other infectious diseases.

• 

  Daniel Higgins, MS

  Dan Higgins is an affiliate instructor in PMM. Dan has a Master of Computer Science from Georgia Institute of Technology specializing in “Interactive Intelligence” and a Bachelor of Arts in Computer Science and Mathematics from Assumption University. Dan has more than 20 years of IT industry experience, with ten years in Enterprise Architecture and Framework Development. He is a Cloud Architect with AWS certifications in Machine Learning and Solution Architecture. He has played key roles in numerous projects, including the creation of a next-generation solution for a Whole-Genome Data Repository and the development of WormCat, a categorization and visualization tool for genome-scale data. 

• 

  Sithara Raju Ponny, MS

  With the advent of genomic technology and computational biology, there has been a significant transformation in medicine. The ability to sequence and analyze DNA has given us a better understanding of the genetic underpinnings of various diseases. By analyzing large amounts of data, we are now able to identify genetic mutations, variations and additional transcriptomics framework that contribute to disease susceptibility, progression, and treatment response. This knowledge has revolutionized the way we approach hypothesizing the way diseases manifest, their diagnosis and treatment. The field of genomics and computational biology interests me as it has the potential to transform healthcare by improving disease prevention, diagnosis, and treatment. I am interested in leveraging these transformative aspects of genomics, transcriptomics, and computational biology to gain a deeper understanding of human diseases.