Charles Yang Email & Phone Number

Washington, Dc, Us

Washington, Dc, Us

Co-lead author on AI for Energy report: https://www.energy.gov/cet/articles/ai-energyLed engagement strategy for DOE's Frontiers in AI for Science, Security, and Technology (FASST) initiative: https://www.energy.gov/fasstCo-lead for interagency Material Genome Initiative workshop on self-driving labs: https://www.mgi.gov/sites/default/files/documents/MGI_Autonomous_Materials_Innovation_Infrastructure_Workshop_Report.pdf

Washington, District Of Columbia, Us

Led supply chain portfolio strategy for $10B 48C investment tax credit across clean energy manufacturing and critical materialsSupported 45X tax credit implementation for critical materialsLaunched new clean energy manufacturing RFI to support internal supply chain analysis: https://www.energy.gov/mesc/articles/request-information-clean-energy-supply-chainsSpearheaded implementation of new demand-side battery materials processing grant

Washington, District Of Columbia, Us

ORISE fellowship with the Office of Manufacturing and Energy Supply Chains in the Department of EnergyDeveloped supply chain portfolio strategy for $10B 48C investment tax credit across clean energy manufacturing sectorsLead contributing author on MESC Supply Chain Progress Report: https://www.energy.gov/sites/default/files/2023-08/Supply%20Chain%20Progress%20Report%20-%20August%202023.pdf

Palo Alto, Ca, Us

Developed time series deep learning AI models for enterprise offerings, with a focus on financial applicationsCoordinated multi-functional technical teams across the compiler stack to bring new AI models as Sambanova product offeringsDeveloped multi-lingual 150B GPT language models, including dataset pipelining and model fine-tuning

New York City, Us

Helping advocate for durable negative carbon removal policies and technology. I also host the Carbon Dioxide Removal Horizons Seminar Series: https://www.youtube.com/watch?v=A8ehUpC0VZQ&list=PL1je2pACUAbKvdd-gu4uTIw8VqHTMh7Tr

Developed system-level expertise for mass timber supply chains, sustainable urbanism, and carbon dioxide removal measurement and verification. Experienced in exploring, ideating, and designing DARPA-stype programs for climate.

Washington, Dc, Us

- Technical Deep Dive into the fundamentals of quantum computing- Interviewed quantum computing experts in industry and academia to better understand the opportunities and challenges of quantum computing- Conducted market assessment of quantum computing technologies and evaluation of the technical barriers to commercialization- Developed prototype ARPA-E program for accelerating quantum computing adoption

Berkeley, Ca, Us

- Developing interpretable and explainable machine learning algorithms for the inverse design of nanoscale optical systems- Worked on interdisciplinary team of scientists, engineers, and computer scientists; helped secure multimillion dollar ARPA-E grant to develop AI-powered inverse design algorithms to find better designs for optical metamaterials

- Applying machine learning to finite-element problems, with a focus on composite materials

- Applied dynamical control theory to improve RNN stability- worked on developing benchmark datasets for physical sciences and machine learning- developed data-free methods for detecting backdoored neural network models as part of the TrojAI IARPA competition

- worked on interdisciplinary team to outline M&A strategy for large renewable energy services company- identified organizational integration strategies for after M&A

Santa Clara, Ca, Us

- developed novel time-series anomaly detection methods on large-scale datasets- used parallelization methods to significantly speed up model training

El Segundo, California, Us

-Applied machine learning to additive manufacturing quality control. Used dimensionality reduction techniques for in-situ non-destructive characterization of alloyed samples. Created Custom bagging models to combat class imbalances.-Used Time-series neural networks for anomaly detection in satellite battery telemetry -Developed jupyter notebooks tutorials on deep learning to build up in-house and domain-specific AI expertise

Alameda, California, Us

- Developed streamlined data pipelines for data querying, processing and filtering, modelling and analysis, and visualization. Used SQL, AWS S3, and Python- Applied machine learning techniques to a variety of problems, including image classification for defect detection in pilot-scale manufacturing line, time-resolved model prediction controller, and non destructive spectroscopic characterization. Used Python's Keras, scikit-learn, pandas and numpy libraries, and AWS EC2 instances for Big Data compute.- Implemented models with GUI's and in embedded firmware in our final product, manufacturing line, and research labs.

Richmond, Virginia, Us

-Created generative models for wind profile and load profile data to increase network sizes of power grids for improved modelling results-Investigated power grid phenomena such as islanding, micro-grids, renewable energy integration, and forecasting-Developed novel evolutionary algorithms to optimize the sizing and location of Distributed Generation Photovoltaics in power grids using real-world, highly time-resolved data

Richmond, Virginia, Us

-Understanding formation mechanism of Metal Organic Frameworks(MOF) with an application focus on toxic gas capture and storage; photocatalysis; and filtration.-Designing novel synthesis procedures for MOF derived porous carbons, for toxic gas capture, energy storage, and photocatalytic reduction reactions-Experienced in aerosol processing via high-temp tube furnace, electrospinning, as well as in wet chemistry methods.

Master Of Arts - Ma, Theology/Theological Studies

Master Of Science - Ms, Electrical Engineering And Computer Science

Bachelor'S Degree, Electrical Engineering And Computer Science