Feiran Huang

Feiran Huang has a wealth of experience in data science and research. In 2021, they began working as Manager of Innovation & Data Science at Innowatts, where they lead and manages a high-performance data science team to develop and improve forecasting models for solar power generation and electricity demand with machine learning and advanced analytical methodologies. Feiran also provides data insights for reducing carbon emissions and increasing energy efficiency, as well as building product QC tools and ml lifecycle platform. Additionally, they provide thought leadership for business impact with new products and electrification research. Prior to this role, they worked as a Senior Seismic Data Scientist and Geophysicist at CGG from 2011 to 2021, where they developed end-to-end production pipelines and testing workflows for 3D seismic image reconstruction. Feiran also built 3D image models with tomography and Full-wave Inversion using gradient descent, optimization, regularization, and learning rate tuning. From 2009 to 2011, they worked as a Postdoctoral Research Fellow at Rice University, where they investigated targeting drug delivery systems for curing cancer with minimal side-effects. Feiran also conducted live imaging intra-cellular cancer therapeutic trafficking with laser scanning confocal microscopes and developed particle tracking techniques for interpreting intra-cellular nanoparticle movement. From 2004 to 2009, they worked as a Postdoctoral Research Associate at the University of South Florida in Biophysics.

Feiran Huang obtained a Doctor of Philosophy in Condensed Matter and Optical Physics from Rensselaer Polytechnic Institute between 1998 and 2003. Feiran also holds certifications in AI for Medicine Specialization from Coursera (obtained in June 2020), Advanced Machine Learning on Google Cloud Specialization from Coursera (obtained in May 2019), Machine Learning with TensorFlow on Google Cloud Platform Specialization from Coursera (obtained in November 2018), Deep Learning Specialization from Coursera (obtained in May 2018), Data Science in Python Pandas, Scikit-learn, Numpy, Matplotlib from Udemy, and Machine Learning from Coursera.