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.
Sebastiano Busato joined theEnBiSys Lab as a Postdoctoral Research Scholar in 2021. His research uses data science, large-scale genomic datasets and AI to provide quantitative insights and aid in decision-making in a variety of agricultural and biological contexts. Sebastiano is currently working on modeling uncertainty in the gap gene network of Drosophila. Additionally, he provides support to other EnBiSys projects by designing data management solutions.
Originally from Italy, Sebastiano obtained a B.S. in Agronomy from Zamorano University in Honduras, and a Ph.D. in Animal Science from Oregon State University. His graduate work focused on molecular aspects of lipid nutrition in dairy cows by evaluating the transcriptomic response to dietary long chain fatty acids.
Selene Schmittling is a Ph.D. student in the EnBiSys Lab, within the Department of Electrical and Computer Engineering at NC State. Her research focuses on developing interpretable, data-driven machine-learning models to understand how plants react to stress and hormones. Recent work using static and temporal data, and logistic regression models with LASSO uncovered transcription factors likely controlled outside of transcription that are involved in iron deficiency response in Arabidopsis thaliana root epidermis. Future work involves comparative network analysis to identify differences in networks developed using transcriptional vs. translational data. Selene is an Initiative for Maximizing Student Diversity (IMSD) Fellowship Fellow.
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 Department of Electrical and Computer Engineering at NC State and a member of the EnBiSys Lab. He received a B.S. in Electronics & Communication Engineering from Manipal Institute of Technology (India), and a M.S. in Electrical Engineering from 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.
Srija Movva is a Master’s student in the Department of Electrical and Computer Engineering and a member of EnBiSys Lab at NC State. Originally from Hyderabad, India, Srija obtained her B.S. in Electrical and Electronics Engineering from GITAM University, Hyderabad. Srija’s research uses unsupervised machine learning algorithms to find consistent sub classes of sweetpotatoes.
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.
Rashmi Datta is a Master’s student in the Department of Electrical and Computer Engineering and a member of the EnBiSys Lab at NC State. She received a Bachelor’s in Electronics & Communication Engineering from National Institute of Technology, Silchar India in 2019. Rashmi’s research focuses on using user-perception features data along with features that can be extracted from images of sweetpotatoes to train machine learning models that are able to objectively grade sweetpotatoes (e.g., deviation from a high value sweetpotato).
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.