Meet the Team
DesertData Research Groups
Prof. Shimon Rachmilevitch, Eco-physiologist
Prof. Shimon Rachmilevitch, at the Blaustein Institute for Desert Research, studies whole plant ecophysiology. His research focuses on how desert plants adapt to extreme conditions, particularly through root dynamics and functions.
DeserTech Project Involvement
Prof. Rachmilevitch's research group is the backbone of the DesertData Database Team. The group is responsible for creating and maintaining the inclusive database that bridges the gap between knowledge and action through data-driven solutions. Their efforts ensure that data related to agriculture, water, health, desert ecology, and climate are accurately collected, processed, and made accessible for scholars, scientists, policymakers, and stakeholders.
Prof. Lena Novack, Environmental Epidemiologist & Biostatistician
Lena Novack is an environmental epidemiologist and biostatistician at Soroka University Medical Center. She also serves as the head of the Negev Environmental Health Research Institute (NEHRI). Over the past decade, Lena's team at NEHRI has been dedicated to investigating how environmental factors affect human health in the Negev region and across Israel.
DeserTech Project Involvement
In the DeserTech project, the NEHRI team aims to make essential data for environmental health studies as accessible as possible. Typical investigations in this field require comprehensive information on both exposure factors and health indices.
Exposure Factors: These include a wide range of elements, from traditional meteorological and pollution measurements to less obvious parameters such as greenness indices, water quality, and airborne allergens. The NEHRI team will process this publicly available exposure information into cleaned, quality-controlled, and organized databases ready for diverse investigations. This will encompass at least two decades of meteorological and pollutant data recorded by the Israel Meteorological Services and the Ministry of Environmental Protection. Some exposure factors, like drinking water quality and airborne allergens, will necessitate dedicated investigations to identify relevant data points and measurement methods.
Health Indices: To adhere to privacy protocols, health indices will be provided on the DeserTech platform in an aggregated format, ensuring the confidentiality of sensitive medical information.
Our Commitment
Lena and her team are committed to advancing environmental health research and ensuring that data is accessible and useful for all stakeholders. Through their meticulous work, they aim to improve public health outcomes and contribute valuable insights to the scientific community.
Prof. GIlad Ravid,
Prof. Gilad Ravid, Ph.D., is an Associate Professor in the Department of Industrial Engineering and Management at Ben-Gurion University of the Negev. His multidisciplinary background uniquely positions him at the intersection of agricultural science, technology, and data analysis.
Prof. Ravid's academic journey began with a B.Sc. in Agricultural Engineering from the Technion - Israel Institute of Technology, laying a solid foundation in agricultural sciences. He then broadened his expertise with an MBA from the Hebrew University of Jerusalem and a Ph.D. in Interdisciplinary Studies from the University of Haifa. His doctoral research, which examined knowledge sharing in small groups with a focus on online discussion forums, presaged his later work in agricultural data analysis and sharing.
Following postdoctoral research at the University of Southern California (USC), where he delved deeper into knowledge-sharing environments and participatory media, Prof. Ravid has developed a research program that leverages advanced computational methods to address critical agricultural challenges. His work employs Computer-Mediated Communication (CMC), Social Network Analysis (SNA), machine learning, and artificial intelligence to enhance our understanding of complex agricultural systems.
A significant portion of Prof. Ravid's current research focuses on the application of data science to agriculture, with notable contributions to the understanding of cotton and corn growth. By analyzing vast datasets related to these crops, he has developed models that provide insights into optimal growing conditions, pest management strategies, and yield prediction. His work in this area has been particularly impactful, offering farmers and agricultural researchers tools to make data-driven decisions that improve crop productivity and sustainability.
Prof. Ravid's innovative approach to agricultural data sharing and processing has led to the development of platforms that facilitate collaboration among farmers, researchers, and industry stakeholders. These initiatives have not only increased agricultural productivity but also promoted more sustainable farming practices.
Through his multifaceted research program, Prof. Ravid continues to bridge the gap between cutting-edge data science and practical agricultural challenges, contributing significantly to the advancement of precision agriculture and sustainable farming practices, particularly in the cultivation of cotton and corn.
