Louvere has presented and continues to present at several STEM-related conferences on various topics and is an active STEM advocate. Louvere has worked in three different engineering roles throughout her 20-plus-year career while at MathWorks. She has a bachelor’s degree in biomedical engineering and a master’s degree in geographic information technology with a specialization in remote sensing. She also manages a team of application engineers. Louvere Walker-Hannon is a MathWorks application engineering senior team lead who provides technical guidance and strategic direction on the implementation of AI and data science workflows for various applications. She is affiliated with GWISE, Northeastern Chapter, and was an invited presenter to CRA-W 20. Shweta was also part of the team to create the vGHC 20 workshop “Do You See What I See? Using AI and AR.” Outside of work, she also presented in NanoDays at the Museum of Science and Girls Scouts conference. Shweta has delivered multiple workshops, including “Deep Learning and IoT” at Ohio State University and the “Pocket AI and IoT” enrichment workshop at Black Girls Code in 2020. Prior joining to MathWorks, she worked as an assistant professor with Delhi College of Engineering, India, and taught various STEM-related courses to undergraduate students. Shweta also has multiple publications in conferences and journals. Her research focus is to detect undesirable emergent behaviors in system of systems using machine learning. thesis at Northeastern University in Boston, MA. She holds master’s and bachelor’s degrees in computer science and engineering from India and is currently working on her Ph.D. When she joined MathWorks in 2019, she worked in Engineering Development Group, where she worked directly with customers to resolve issues related to multiple MATLAB toolboxes. Shweta Singh is a senior software engineer at MathWorks working to ensure that MATLAB and Simulink products and services are designed and implemented to the highest possible security standards. She also delivered the workshop “Pocket AI and IoT” in-person at GHC 19. She delivered the interactive virtual workshop “Do You See What I See? Using AI and AR” at vGHC 20, Women in Data Science (WiDS) 2021, and Open Data Science Conference (ODSC) East 2021. Sarah loves teaching and building tech that empowers women to tackle tough problems in fun and engaging ways. Sarah holds dual bachelor’s degrees in computer science and biology from the University of Virginia, and a master’s degree in computational science and engineering from Harvard University. She has also worked as an application support engineer, helping customers to investigate and overcome technical challenges in their own machine and deep learning applications. Her team builds tools that enable scientists and engineers to exchange deep neural networks between MATLAB and other tools, such as PyTorch, ONNX™, and TensorFlow™. Sarah Mohamed is a software engineer at MathWorks, working on deep learning in the Statistics and Machine Learning group. She has been promoting Women in Technology by mentoring students at the Boston Museum of Science. She holds a master’s degree in electrical engineering, focusing on signal processing and computer vision, from the University of California Los Angeles.Ĭhinmayi has contributed to various Women in Technology events, such as GHC and SWE, by assisting with content development and serving as a TA at multiple hands-on exercise sessions, notably the “Edge AI with Raspberry Pi” workshop presented at GHC 19. She has also worked in a customer-facing role, helping engineers to investigate and overcome technical challenges in their own deep learning applications. During her time at MathWorks, she has contributed to development and qualification of several key deep learning functionalities in the product suite. Chinmayi Lanka manages a quality engineering team responsible for designing and implementing cutting-edge tools to qualify the deployment of deep learning algorithms to Raspberry Pi, FPGA, NVIDIA ® Jetson ®, and other embedded devices.
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