• Viam

  • Nicholas Frańczak

Nicholas Frańczak

Robotics Engineer at Viam

Nicholas Frańczak has work experience in various roles and companies. In 2019, they worked as a Course Instructor at iD Tech Camps. In 2020, they were a Research Intern at Aplikacje Krytyczne Sp. z o.o. In 2021, they served as a Dean's Tutor and Course Assistant at Wesleyan University, and also worked as a Machine Learning Engineer Intern at Terrascope. In 2021, they had an Engineering Internship at Viam, Inc. In 2022, they became a Course Assistant at Wesleyan University, and later joined Viam, Inc. as a Robotics Engineer.

Nicholas Frańczak earned a Bachelor of Arts (BA) degree in Mathematics and Computer Science from Wesleyan University, completing their education from 2018 to 2022. In addition to their formal education, they pursued various certifications related to machine learning and deep learning. Nicholas obtained certifications in Convolutional Neural Networks in TensorFlow, Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning, Natural Language Processing in TensorFlow, Sequences, Time Series and Prediction, TensorFlow in Practice Specialization, Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization, Machine Learning, and Neural Networks and Deep Learning. These certifications were obtained between 2019 and 2020 from Coursera.

Location

New York, United States

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Viam

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Robotics has the potential to do so much good, but progress has been slowed by complicated hardware and software integrations, long development cycles, and people's fear of tripping over a robot on their way to work. At Viam, we’re addressing these issues by building a novel robotics platform that relies on standardized building blocks rather than custom code to create, configure and control robots quickly and intuitively. We’re empowering engineers - aspiring and experienced - across industries to solve complicated automation problems with our innovative and developer-friendly software tools.


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51-200

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