Vision & Mission
We are a team of aerospace engineers, machine learning engineers, and space weather scientists who share the vision of making humanity a multiplanetary civilization. Our mission is to build the foundational technology required to make humanity's ambition in space and on Earth resilient to space weather. We want to make it safer to operate technologies and human-centric missions anywhere from vLEO to the Moon, Mars, and Beyond, by providing advanced space weather predictions.
Team
Padmashri Suresh, Ph.D.
Founder & CEO
Padmashri is a space weather scientist with a diverse career background. She began her professional journey at IBM, applying novel machine learning (ML) and artificial intelligence (AI) techniques to address various business challenges. A life-long passion for space led her to Utah State University to work on SmallSats. Recognizing the critical need for accurate space weather predictions to ensure the reliability and performance of SmallSat missions, she pursued a PhD to enhance space weather forecasting using ML as a NASA Earth and Space Science Fellow. She gained further experience at Los Alamos National Lab as a Vela Fellow and at the National Academy of Sciences as a Mirzayan Policy Fellow. Later, she transitioned to the tech industry, where she established AI/ML practices from ground-up in both startups and large organizations. In response to the growing demand for improved space weather predictions in the space industry, she founded Perceptive Space to mitigate the risks of space weather on humanity's space ambitions.
Peng Mun Siew, Ph.D.
Aerospace Lead
Peng Mun is a research scientist with expertise in developing end-to-end physics-informed deep learning models for the space environment With previous stints as a Research Scientist at Massachusetts Institute of Technology (MIT) and University of Minnesota, his background spans space weather modelling, scalable multi-agent sensor tasking systems for space domain awareness, state estimation and space object tracking. His passion for machine learning and space environment modelling brought him to Perceptive Space, where he is excited to work on revolutionizing space environment modeling through machine learning and artificial intelligence.
Alok Shenoy
Data & Software Lead
Alok has ~10 years of experience designing and building data platforms and cloud infrastructures to support highly scalable ML/AI products and services. With previous stints as an early employee at startups like Coursera & Precima, he has led and contributed efforts to build enterprise systems and products used by companies like Google, Meta and AWS. He holds Master's in Informations Systems as well as a Master's in Chemistry from Utah State University and used to run a life science lab in a different life. A life long sci-fi fan, he is very excited to be a part of Perceptive Space where he can contribute towards the development of crucial space weather technologies required to turn science fiction into reality.
Jonathan Chalaturnyk
Machine Learning Scientist
Jonathan is a machine learning scientist with expertise in modern AI systems, such as AI/ML models for edge deployment, computer vision, and user-facing ML platforms. His background spans multiple interdisciplinary fields, including astro-particle physics, space physics and cell biology, with stints at the Sudbury Neutrino Observatory, and most recently at Applied Brain Research, where he worked on lightweight ML models. He holds a Master's degree in Applied Mathematics from the University of Waterloo. Joining the Perceptive Space team was a perfect opportunity to combine his passion for space and his expertise in building AI products and help build the best possible AI-driven space weather insights for a safe and scalable space environment.
Sayantan Auddy, Ph.D.
Machine Learning Scientist
Sayantan is a machine learning scientist specializing in integrating physics and machine learning to solve complex problems. He was formerly a Research Scientist at NASA JPL where he used computer vision (CV), large language models (LLM), and generative AI to advance understanding of the formations of stars and planets. His previous engagements include research scientist appointments at Johns Hopkins University, Center for Astrophysics @ Harvard and Iowa State University. Sayantan joined Perceptive Space because of his enduring passion for space & AI and is excited to leverage his background to help make humanity a multiplanetary civilization. He holds a PhD in Physics from Western University.
Interested in joining us?
If you are an Aerospace Engineer or a Machine Learning Scientist looking to join us in building critical space weather technologies required for safe and reliable operations in space, send a copy of your CV to [email protected].
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