Data Science User Group monthly meetup

Sep 3, 2021 · Champaign, United States of America

To kick off the fall season of our data science user group, we are excited to welcome Srinivas Sridharan, Corteva UIUC Site Leader and Lead Imaging Data Scientist, to provide an ML 101 hands-on workshop that will utilize an AWS EC2 instance for participants who register. This workshop will introduce the participants to machine learning and deep learning concepts. It will mainly focus on using deep learning to solve Ag problems for image classification, multiple object detection, and segmentation. To register for an AWS EC2 instance for the workshop, please fill out this form (in addition to RSVPing for the event on Meetup): https://forms.gle/tiLWptc4d6jBK8gw8 .

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Speaker Bio
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Dr Srinivas Sridharan joined Corteva Agrisciences in 2017 and is the Lead Imaging Data Scientist Corteva UIUC research park site leader. As the UIUC site leader Srini is responsible in hiring and mentoring student interns in data science and data analytics. He is also currently working on collaborating with faculty and researchers in the University to advance innovation and technology in digital agriculture. His work as the lead imaging data scientist focuses on developing machine learning and deep learning algorithms to phenotype germplasm in lab and field environments and build robust, ubiquitous, and cost-effective image analytic solutions for customers. Before Corteva, he worked as an assistant professor in the computer science department at Stevens Institute of Technology, Hoboken, NJ. Srinivas received his Master’s in Electrical Engineering and Ph.D. in Computing and Information Sciences from Rochester Institute of Technology, Rochester, NY. His Ph.D. dissertation focused on machine learning and applied perception in guiding visual attention, task-based eye movement prediction, and real-world search task inference using eye tracking. Before coming to US, Srinivas worked as a senior software engineer in India and Germany for Hexaware and Infosys Technologies Limited. His research interests are machine learning, deep learning, computer vision, and virtual and augmented reality for 3D graphics and visualization.

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Workshop abstract
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Agriculture today has changed drastically in the past few decades due to ever growing demands to feed an increasing population. At Corteva we aim to enrich the lives of those who produce and those who consume, ensuring progress for generations to come. Our customers are posed with multiple challenges that limit the yield and quality potential of our seed products. There is a great need to apply state-of-the-art tools and technology to develop integrated solutions to improve crop productivity with the goal of feeding the world.
At Corteva, we use AI and Machine Learning to develop robust, ubiquitous, and cost-effective solutions to our customers that help them overcome challenging problem in today’s Agriculture. State-of-the-art machine learning and deep learning algorithms are applied to varied problems in remote sensing, proximal imaging and computer vision, environment and agronomic system modelling, systems biology and biostatistics, and predictive business analytics.
This workshop will introduce the participants to machine learning and deep learning concepts. It will mainly focus on using deep learning to solve Ag problems for image classification, multiple object detection, and segmentation.

Pre-req:
A laptop and charger
Network firewall should not block AWS URLs
Good if familiar with Python programming (no issues if you don’t)
Interest in learning Machine Learning, Deep Learning, and Computer Vision

Event organizers
  • Champaign-Urbana Data Science User Group

    The aim of the user group is to build a community of interest around data science to foster learning, collaboration, and networking. The group will serve both students and professionals to bridge the gap between the analytical sciences and practical applications of industry. Anyone is invited and included, from undergraduate students (or younger!) to seasoned professionals. There is no requirement for admission, only an interest in learning more about data science.

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