Atinary Technologies
Daniel Pacheco Gutierrez is a highly skilled Machine Learning Engineer with experience at Atinary Technologies Inc. since September 2021, focusing on the continuous development and production of Bayesian optimization algorithms. Prior to this, Daniel served as a Software Engineer, where responsibilities included developing algorithms and data analysis pipelines for various clients and contributing to a Self-Driving Lab project showcased at major industrial conferences. Daniel's experience also encompasses work at REM Analytics, where significant advancements in DNA analysis and laboratory protocol automation were achieved. During a tenure as Co-Captain of McGill Chem-E Car, leadership was demonstrated in managing a multidisciplinary team. Earlier roles included research on sustainable methane conversion at Catalytic Process Engineering McGill and developing a chlorinator prototype at Terragon Environmental Technologies. Daniel holds a Master's degree in Computational Science and Engineering from EPFL and a Bachelor's degree in Chemical Engineering from McGill University.
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Atinary Technologies
Atinary is and AI company based in Lausanne and Silicon Valley. Atinary's no-code AI platform accelerates R&D and discovery of breakthrough molecules and materials. The sweet spot applications are in formulation, catalysis, and synthesis for the pharma, biotech, food, chemicals, energy, and climate tech industries. Atinary is committed to addressing global challenges and inspiring a future where science and innovation improve exponentially. The name Atinary comes from the verb in Spanish "atinar", which means hit, as in hit the target. Atinary's leading ML technology optimizes experimental planning, orchestrates workflows, and hit targets 10 to 100 times faster, in weeks or months, instead of years. Accelerating R&D matters because materials are essential to improve our lives and tackle some of humanity’s biggest challenges. For example, better materials are key to reduce pollution and address climate change, and to improve health. We need better materials to develop a) more affordable batteries that last longer and are not toxic; b) more efficient solar cells that can be deployed everywhere; and c) more effective carbon capture, use and sequestration tech. Similarly, to discover new medicines and vaccines, we need to find the optimal conditions to hit the right molecules. Products: Atinary’s proprietary ML algorithms can be seamlessly deployed in existing workflows using Atinary’s no-code AI platform, the Self-driving Labs Platform or SDLabs. SDLabs enables the labs of the future, these are Self-driving Labs or closed-loop Materials Acceleration Platforms (MAPs). With SDLabs, users can deploy AI on the same day to solve multi-objective optimization problems with multiple parameters, including categorical variables and non-linear constraints.