Associate Professor I at the Darcy Ribeiro State University of Northern Fluminense (UENF) in the Plant Breeding Laboratory. He specializes in the genetic improvement of perennial crops, with a focus on quantitative genetics, experimental statistics, and the use of DNA markers. His research includes the breeding of sour passion fruit through recurrent selection, improving passion fruit for resistance to the Cowpea aphid-born mosaic virus (CABMV) using segregating populations, and enhancing guava for agronomic traits through genomic selection and resistance to Meloidogyne enterolobii. Additionally, he collaborates with the University of California on vine breeding, focusing on resistance to downy mildew and powdery mildew.

Current Position:

• Associate Professor I, Plant Breeding Laboratory, Universidade Estadual do Norte Fluminense Darcy Ribeiro (UENF)

Areas of Expertise:

• Breeding of Perennial Crops
• Quantitative Genetics
• Experimental Statistics
• DNA Markers

Academic Background:

• Postdoctoral Research, University of California, Davis, USA, 2009-2010
• Ph.D. in Plant Production, Universidade Estadual do Norte Fluminense Darcy Ribeiro (UENF), 1998-2001
• Master's Degree in Crop Science (Plant Production), Universidade Federal de Viçosa (UFV), 1995-1997
• Bachelor's Degree in Agronomy, Universidade Federal de Viçosa (UFV), 1990-1995

Research Scientist at Corteva Agriscience, where he has been working for over 7 years. As a corn breeder, he focuses on the development, characterization, recommendation, and testing of hybrids, alongside the creation of inbred lines. His expertise spans computational intelligence, strategic planning, and biotechnology, which complement his plant breeding work. Diogo holds advanced degrees in genetics and plant breeding, as well as a background in biotechnology and computer science.

Current Position:

• Research Scientist, Corteva Agriscience, since September 2017

Areas of Expertise:

• Corn Breeding (Hybrid development, line breeding, hybrid testing)
• Computational Intelligence
• Strategic Planning
• Biotechnology

Academic Background:

• Bachelor’s Degree in Computer Science, Estácio, 2020-2024
• Master’s Degree in Genetics and Plant Breeding, Universidade Federal de Viçosa (UFV), 2007-2009
• Bachelor’s Degree in Biological Sciences-Biotechnology, Unipar - Universidade Paranaense, 2003-2006

Senior Scientist at Syngenta, where she has been working since 2017, specializing in molecular plant pathology. With extensive experience in plant and pathogen molecular biology, Sandra focuses on molecular genetics, functional genomics, and bioinformatics. Her work includes expertise in sequence analysis, molecular cloning, qPCR, and transcriptomics. Sandra holds a Ph.D. in Molecular Plant Pathology from the University of Delaware and has a solid background in plant breeding and biotechnology.

Current Position:

• Senior Scientist, Syngenta, since December 2017

Areas of Expertise:

• Molecular Genetics
• Plant Breeding
• Bioinformatics
• Biotechnology
• Plant Pathology
• Transcriptomics
• Functional Genomics

Academic Background:

• Ph.D. in Molecular Plant Pathology, University of Delaware, 2007-2011
• Master’s Degree in Genetics and Plant Breeding, Universidade de São Paulo (USP), 2004-2006
• Bachelor’s Degree in Agronomy, Universidade Federal de Santa Catarina (UFSC), 1998-2003

Research Scientist specializing in soybean breeding at Corteva Agriscience. He has been working in this role since 2022, focusing on agronomic improvement and high-throughput phenotyping for soybean. Leandro's research interests include genomic prediction for root traits in double haploid lines, with extensive experience gained during his visiting Ph.D. research at Iowa State University. He holds advanced degrees in Agronomy and Plant Breeding from the Universidade Federal de Viçosa.

Current Position:

• Research Scientist, Corteva Agriscience, since July 2022

Areas of Expertise:

• Corn and Soybean Breeding
• High-throughput Phenotyping
• Agronomy
• Genomic Prediction

Academic Background:

• Ph.D. in Agronomy and Plant Breeding, Universidade Federal de Viçosa, 2016-2020
  • Visiting Ph.D. Research in Plant Breeding, Iowa State University, 2018-2019
• Master’s Degree in Agronomy and Plant Breeding, Universidade Federal de Viçosa, 2015-2016
• Bachelor’s Degree in Agronomy, Universidade Federal de Viçosa, 2007-2012

Dr. Flavio Arantes is an experienced agronomist with over 10 years of industry expertise in breeding data management for multiple crops, including rubber trees, sugarcane, soybean, cotton, and wheat. He is passionate about data analysis and digital applications in plant breeding, leveraging his expertise in experimental design, quantitative genetics, and statistics to drive data-driven decision-making. Flavio has led key projects in data management platforms and is a global point of contact for multi-crop data workflows at BASF.

Current Position:

• R&D Digital Specialist, BASF, since August 2021

Previous Experience:

• Breeding Data Management Consultant for Cotton and Soybean, BASF, August 2018 - July 2021

Areas of Expertise:

• Breeding Data Pipeline for Multiple Crops (Rubber, Sugarcane, Soybean, Cotton, Wheat, Rice, Oilseed)
• Experimental Designs
• Quantitative Genetics
• Statistics
• Data Modeling and Visualization
• Digital Applications Optimization

Academic Background:

• Ph.D. in Genetics and Plant Breeding, UNESP - Universidade Estadual Paulista, 2010-2013
• Research Scholar in Statistics/Genetics, University of Wisconsin-Madison, 2012 (9-month exchange sponsored by CAPES)
• Master’s Degree in Crop Breeding, UNESP - Universidade Estadual Paulista, 2008-2010
• Bachelor’s Degree in Agronomy, UNESP - Universidade Estadual Paulista, 2003-2008

Dr. Caio Canella Vieira is an Assistant Professor at the University of Arkansas, where he leads the soybean breeding program. With a strong background in agronomy and plant genetics, Dr. Canella Vieira has been instrumental in developing and releasing over 20 soybean cultivars in Missouri. His work focuses on modernizing breeding programs by prioritizing data analysis and genomic prediction models. In Arkansas, his research targets the development of high-yielding conventional and herbicide-tolerant soybean cultivars with resistance to biotic and abiotic stresses, as well as improved seed composition. His program aims to incorporate economically important traits from diverse genetic lines into modern high-yielding genetic backgrounds, with a significant emphasis on genomic prediction and high-throughput phenotyping to enhance breeding efficiency.

Current Position:

• Assistant Professor of Soybean Breeding, University of Arkansas, since January 2023

Areas of Expertise:

• Soybean Breeding
• Genomic Prediction
• High-Throughput Phenotyping
• Data-Driven Breeding
• Biotic and Abiotic Stress Tolerance

Academic Background:

• Ph.D. in Plant Breeding, Genetics, and Genomics, University of Missouri, 2020-2022
• Master’s Degree in Plant Breeding, Genetics, and Genomics, University of Missouri, 2017-2020
• Bachelor’s Degree in Agriculture, Escola Superior de Agricultura "Luiz de Queiroz" (ESALQ/USP), 2012-2017
• Non-degree International Student, Plant Sciences, University of Minnesota, 2014-2015

Dr. Camila Azevedo is an Assistant Professor III at the Department of Statistics, Federal University of Viçosa (UFV), and serves as one of the coordinators of the Computational Intelligence and Statistical Learning Laboratory (LICAE - UFV). Her expertise focuses on statistical methods applied to plant breeding and Bayesian inference. Camila holds a Bachelor's degree in Mathematics, a Master's, and a Ph.D. in Applied Statistics and Biometry from UFV, and has completed a postdoctoral fellowship at the Blueberry Breeding Genomics Lab at the University of Florida. She is also a CNPq Research Productivity Fellow, classified at Level 1D.

Current Position:

• Assistant Professor III, Department of Statistics, Federal University of Viçosa (UFV), since 2021
• Coordinator, Computational Intelligence and Statistical Learning Laboratory (LICAE - UFV)

Areas of Expertise:

• Statistical Methods Applied to Plant Breeding
• Bayesian Inference
• Computational Intelligence
• Data Analysis

Academic Background:

• Postdoctoral Fellow, Blueberry Breeding Genomics Lab, University of Florida, 2022-2024
• Ph.D. in Applied Statistics and Biometry, Federal University of Viçosa (UFV), 2013-2015
• Master’s Degree in Applied Statistics and Biometry, Federal University of Viçosa (UFV), 2010-2012
• Bachelor’s Degree in Mathematics, Federal University of Viçosa (UFV), 2006-2010

Dr. Daniel Tolhurst is an inaugural Edinburgh Innovations Fellow at The Roslin Institute, leading the project selGxE: Scoping, Estimating and Leveraging genotype by environment interaction in breeding programmes. Trained as a biometrician and quantitative geneticist, Dr. Tolhurst focuses on leveraging both fields to improve the efficiency of breeding, particularly in the context of climate change. His research interests include the use of linear mixed models, variance parameter estimation, genetic variation partitioning, and experimental design, with a specific focus on hybrid breeding systems.

Current Position:

• Edinburgh Innovations Fellow, The Roslin Institute, since 2023

Areas of Expertise:

• Linear Mixed Models
• Variance Parameter Estimation
• Genetic Variation Partitioning
• Hybrid Breeding
• Experimental Design

Academic Background:

• Ph.D. in Genetics and Genomics, The University of Edinburgh, 2019-2023
• Master of Science in Quantitative Genetics and Genome Analysis, The University of Edinburgh, 2020-2021
• Bachelor’s Degree in Mathematics and Statistics, University of Wollongong, 2010-2014 (Graduated with Distinction and First-Class Honours)

Jennifer Luz Lopes is an agronomist and holds a Ph.D. in Plant Breeding with over six years of experience in agronomic research, covering both field and laboratory experiments. Her expertise spans plant selection methods, biometric models, agronomic management, and data analysis. Currently, she works as a Senior Data Analyst at Suzano, contributing to data management and systems for the Genetics and Forest Breeding Department. Jennifer is also a cofounder of R-Ladies Goiânia, a global organization promoting gender diversity in the R community, and is actively involved in supporting Brazil's largest statistics community led by Professor Thiago Marques.

Current Position:

• Senior Data Analyst, Genetics and Forest Breeding Department, Suzano, since December 2023
• Cofounder, R-Ladies Goiânia, since March 2023

Areas of Expertise:

• Plant Selection Methods
• Biometric Models
• Agronomic Management
• Data Analysis
• R Programming

Academic Background:

• Ph.D. in Plant Breeding, Universidade Federal de Pelotas (UFPel), 2019-2023
• Master’s Degree in Plant Breeding, Universidade Federal de Pelotas (UFPel), 2017-2019
• Bachelor's Degree in Agronomy, Universidade Federal de Pelotas (UFPel), 2011-2016
• Data Analysis Certification, Statistics and Data Science Community, Professor Thiago Marques, October 2023

Milene Figueiredo is a Research Scientist at the Federal University of Viçosa, working within the Sugarcane Breeding Program as part of the Interuniversity Network for the Development of the Sugarcane-Ethanol Sector (RIDESA). Her research focuses on the prospecting and validation of candidate genes involved in plant-pathogen interactions, integrating transcriptomic and phenotypic data from sugarcane genotypes affected by pests and pathogens. Milene has a strong background in plant genetics, genomics, and applied computational techniques for education.

Current Position:

• Research Scientist, Sugarcane Breeding Program, RIDESA, since June 2017

Areas of Expertise:

• Sugarcane Breeding
• Plant-Pathogen Interactions
• Genomics and Transcriptomics
• Data Analysis and Computational Techniques

Academic Background:

• Postgraduate Specialization in Applied Computing and Educational Technologies, Instituto de Ciências Matemáticas e de Computação (ICMC), 2020-2022
• Ph.D. in Genetics and Plant Breeding, Universidade Estadual do Norte Fluminense (UENF), 2012-2016
• Master’s Degree in Genetics and Plant Breeding, Universidade Estadual do Norte Fluminense (UENF), 2009-2011
• Bachelor’s Degree in Biological Sciences, Federal University of Ouro Preto (UFOP), 2002-2008