Current Members

Jerome Maleski joined the lab as a research scholar in 2023. His research uses machine vision for agricultural and post-harvest processing, as well as remote sensing and hyperspectral imaging. Jerome is also working to create a dashboards for agricultural data analytics.

Jerome obtained his B.S. in Physics from Penn State University, his Ph.D. in Agricultural Engineering from University of Florida, before going on to be a postdoctoral scholar for the USDA Agricultural Research Service. and completed a postdoctoral. Prior to joining the EnBiSys Lab, Jerome was also employed as a Senior Research Associate at the University of Georgia.

Kirtley Amos joined the lab as a postdoctoral research scholar in September 2022. His research interests include plant-microbe interactions, building machine learning models from NGS data, and translational research.

Originally from Lexington, Kentucky, Kirtley obtained his B.S. in Medicinal and Agricultural Biotechnology, his M.S. in Bio Systems and Agricultural Engineering, and his Ph.D. in Integrated Plant and Soil Science from the University of Kentucky. Before joining the EnBiSys Lab, Kirtley was also employed as a computational scientist at a start up in the area.

Hangjin Liu is a Ph.D. student in the EnBiSys Lab, in the Department of Electrical & Computer Engineering at NC State. Her research involves using machine learning and its applications for biological systems. More specifically, Hangjin is interested in how much data or information is needed to solve a complex statistical problem. She is also interested in digital signal processing, compressed sensing, signal reconstruction, detection and estimation.

Sharva Hiremath is a Ph.D. student in the EnBiSys Lab, in the Department of Electrical and Computer Engineering at NC State. Sharva’s research uses computer vision and image processing techniques to quantify spatiotemporal gene expression in Drosophila and uses this to builds predictive models for this process.

Max Gordon is a Ph.D. student in the EnBiSys Lab at North Carolina State University. He is a Trainee in the NCSU/NIH Molecular Biotechnology Training Program and an NSF Graduate Research Fellow. Max’s research uses machine learning-based models to better understand plant-microbe interactions as part of the InRoot project, which is under the Collaborative Crop Resilience Program.

Grace Vincent is a Ph.D. student in the EnBiSys Lab at North Carolina State University. She received a dual B.S. in both Mathematics and Computer Science from Fayetteville State University in 2022. Her research focuses on using machine learning to identify and assess the severity of Southern Leaf Blight (SLB) disease in maize. Grace employs hyperspectral field imagery to analyze the connection between space and spectral characteristics. Her goal is to detect disease when visual symptoms are limited by pinpointing key light wavelengths that have an impact on the presence and development of SLB. Grace is both a FFAR Fellow with a Bayer Sponsorship and a Graduate Fellowship for STEM Diversity (GFSD) Fellow with a NSA Sponsorship.

Peiran Wang is a Ph.D. student in the EnBiSys Lab at North Carolina State University. She received a B.S. in Electrical and Computer Engineering in 2020. Her research uses deep learning methods to analyze genomic and agricultural data. Her goal is to make more accurate plant breeding decisions, and eventually increase yield production. 

Somshubhra Roy is an M.S. candidate in Electrical and Computer Engineering at NC State University. A native of India, he earned his Bachelor’s degree in Electrical Engineering from the West Bengal University of Technology. Before coming to NCSU, Somshubhra served as a Machine Learning Engineer for the Government of India, where he spearheaded the creation of novel Computer Vision solutions for facial recognition and rapid medical diagnosis. Subsequently, he worked as a Deep
Learning Intern at a California-based startup, focusing on the development of a Continual Learning pipeline for video surveillance on Edge devices. Somshubhra joined EnBiSys Lab as a Graduate Research Assistant in July 2023. Currently, Somshubhra’s research interests focus on utilizing data analytics to discern trends and patterns in agricultural data, crafting and implementing feature engineering methods, and developing decision-support dashboard tools for North Carolina soybean farmers using supervised learning to streamline cultivation practices and provide data-driven insights as part of the Soybean Extension program in collaboration with N.C. Plant Science Initiative and NC State Data Science Academy.

Chanae Ottley is a PhD student in the EnBiSys Lab. She received her B.S. in Mathematics from Florida A&M University in 2019. Chanae is funded by the Louis Stokes Alliance for Minority Participation (LSAMP) – Bridge to the Doctorate (BD) Fellowship Program. Her research interests are the applications of mathematics and computer vision in agriculture. 

Azizah Conerly is a Ph.D. student in the Department of Electrical and Computer Engineering, a member of the EnBiSys Lab, and a member of the STEPS Center. She is a GAANN Biotech Fellow with an interest in academia. Her research focuses on the management of heterogeneous agricultural data, the interpretation of the collected data through different computer vision techniques, and the visualization of collected data. With further interests in utilizing computer vision techniques in biological applications. Originally from Glenn Dale, MD, she obtained her Bachelor’s degree in Electrical Engineering from Morgan State University and her Master’s degree from NC State.

Teague McCracken is a Ph.D. student in the Electrical and Computer Engineering Department at North Carolina State University, a Provost’s Doctoral Fellow, and a member of the EnBiSys Lab. Before attending NC State, he earned a B.S. in Biosystems Engineering in 2024 from Clemson University. His research focuses on exploring genetic regulatory mechanisms in maize and developing data processing procedures for high-throughput screening (HTS) platforms. Teague’s goal is to develop computational approaches that advance biological knowledge with the potential to positively impact medicine, agriculture, and sustainability. His research interests lie in systems biology.