Teaming Partners

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Investigator Name 
Organization Type 
Area of Expertise 
Background, Interest,
and Capabilities
Contact Information 
 Brookline Chemical Co-operationDavid Levy Small Business Other Energy Technologies Revolutionary method,including eqippment technology and products to drastically reduce energy requirements in textile processing .The system replaces high energy consumption that requires burning large amounts of gas or oil that are used to create the heat necessary to fix colours on textile,Our system reqires less than 1 sec.exposure to a unique light source of modified ultra violet light by reducing the energy requirements by approximately 90%.Large amounts of oil or gas are saved as well as eliminating Carbon Dioxide,Carbon Monoxide and Carbon Patriculates immission to the atmosphere,therefore drastically reducing energy consumptions, cost and provides clean air.


Phone: 301-7671177

Address: 9817 Inglemere Drv, Bethesda, MD, 20817, United States
 Columbia UniversityAlexander Urban Academic Other Energy Technologies Assistant professor in chemical engineering and founding member of the Columbia Electrochemical Energy Center (CEEC, Many years of experience in the atomic-scale modeling of inorganic materials, especially materials for Li-ion batteries, with first principles methods and coarse-grained techniques. Current research focus lies on understanding and overcoming degradation in batteries, fuel cells, and other electrochemical energy storage and conversion devices. We use machine learning to accelerate and to bypass conventional modeling. We make extensive use of databases, for example, for the storage and analysis of data generated by automated (high-throughput) calculations.


Phone: 212-854-0105

Address: 812 Mudd Building, 500 W120th Street, New York, NY, 10027, United States
 Michigan State UniversityKalyanmoy Deb Academic Building Efficiency My research interest in development and application of efficient machine learning based optimal design and knowledge extraction methodologies. I have proposed efficient multi-criterion optimization methodologies which are extremely popular (in public domain) and has been commercialized by entrepreneurs. I work very closely with industries in design optimization activities including robust and reliable design, surrogate-assisted design, dynamically changed system design, hierarchical (multi-level) system design, exa-scale design optimization involving millions to billions of integer variables, and others. My machine learning based design activities developed nonlinear decision trees and random forests for classifier and regressor identification using feature relationships separating good from bad designs, deep neural networks for classifying images and identifying objects, and multi-reward function based reinforcement learning for process optimization tasks. We are pursuing current industry projects in the area of Explainable and interpretable AI.


Phone: 5179300846

Address: 428 S. Shaw Lane, 2120 EB, East Lansing, MI, 48864, United States
 Kebotix, Inc.Semion Saikin Small Business Other Energy Technologies Kebotix, Inc. develops an integrated autonomous platform (Self-Driving Lab) for the accelerated discovery of molecules with targeted properties. The company is a spin-off from the Aspuru-Guzik Lab at the Department of Chemistry and Chemical Biology, Harvard University. Our technology combines generative machine-learning models for prediction of molecules with specific properties, conventional physical models, and robotic synthesis. This AI/Robotics feedback loop accelerates the discovery of new materials by more efficiently processing complex data and making better decisions. The approach is generic as it benefits a broad range of applications including materials for renewable and sustainable energy, energy storage, and energy efficient buildings.


Phone: +1(619)212-6649

Address: 501 Massachusetts Ave., Cambridge, MA, 02139, United States
 University of VermontSafwan Wshah Academic Other Energy Technologies Computer science Assistant Professor with broader expertise and interests in deep learning, reinforcement learning, machine learning for power grids, computer vision, data analytics, and image processing. Experience in applying machine learning techniques to generate Molecules hypothesis using generative adversarial networks (GAN’s).
Dr. Wshah and his students are capable and interested in applying machine learning technique to many of the addressed research problems in this FOA. Specifically, we are interested in any of the design challenge problem such as hypothesis generation for electrical circuits and/or Materials/Molecules. In addition to any of the Hypothesis Evaluation.


Phone: 802-656-8086

Address: 210 colchester ave, burlington, VT, 05405, United States
 University of IowaAndrew Kusiak Academic Power Generation: Renewable Research in systems engineering, smart systems, modeling, machine learning, and optimization.
Experience in development of models, algorithms, and solutions applied in energy generation, energy management, manufacturing, innovation.


Phone: 319-3355934

Address: 4627 Seamans Center, Iowa City, IA, 52242, United States
 Carnegie Mellon UniversityHaibo Zhai Academic Power Generation and Energy Production: Fossil/Nuclear Dr. Zhai conducts systems research in carbon capture technology, including process simulation and techno-economic analysis. Dr. Zhai would like to combine computational systems research with machine learning to explore advanced materials (e.g. high-performance polymeric membranes) for CO2 separation, which will help to meet the U.S. DoE's proposed cost target of CO2 capture for new-generation carbon capture technology. I am looking for collaboration with material scientists and AI experts.


Phone: 4122683757

Address: 5000 Forbes Ave, PITTSBURGH, PA, 15213, United States
 Wayne State UniversityYanchao Liu Academic Transportation We have expertise in using optimization and machine learning techniques to solve complex planning, operation and decision making problems. Our experience include preventive/corrective AC optimal power flow problems with security constraints, stochastic optimization in infrastructure planning, data-driven analysis and pricing of renewable generation resources, smart meter data mining and customer analytics.
Expertise include: Mathematical programming and optimization algorithms development using GAMS, R and Python.
We are a participant in the Grid Optimization Challenge organized by ARPA-E.
Our research has been published in IEEE Transactions in Power Systems, Energy Policy, The Electricity Journal, Transportation Science, Optimization Methods and Software, etc.


Phone: 3135773301

Address: 4815 4th Street Rm 2169, Detroit, MI, 48201, United States
 Pandata Tech IncGustavo Sanchez Small Business Other Energy Technologies Pandata Tech is a Houston-based data analytics company that specializes in data quality solutions for the energy industry. We've developed a data quality platform that uses machine learning (ML) and artificial intelligence (AI) to make digital maintenance, optimization, and automation more reliable.

Companies have invested millions in data acquisition and streaming. This creates data chaos and historians. Millions of data point over thousands of signals need to be validated to make sure any future modeling and work returns benefit. Our machine learning tags, validates, and characterizes all this data at scale, allowing to bridge the real world with the digital world for better processes.

Our solution reduces false positives, false negatives, and time spent cleaning and validating data. Pandata's data quality checks reduce the amount of time it takes to clean data by at least 50%. This translates into data driven solutions that are cost saving, increase productivity, and increase team collaboration. Our data quality checks attribute to:
▸ decreasing downtime by 25% ▸ decreasing maintenance by 35% Pandata's data quality platform serves companies that include O&G exploration and production, power generation, IIoT, aerospace, and logistics.

These companies typically: ▸ process thousands of signals ▸ use digital maintenance / optimization / automation ▸ have pressure from operators to be digital ▸ have pressure to meet ISO reporting standards


Phone: 4847649502

Address: 1301 Fannin St #2440, Houston, TX, 77002, United States
 University of South CarolinaJochen Lauterbach Academic Other Energy Technologies High-throughput screening in combination with machine learning and statistical methods for discovery and optimization of novel catalysts. Knowledge extraction from experimental datasets. Rapid spectroscopic screening.


Phone: 8037777904

Address: 541 Main Street, Columbia, SC, 29208, United States
 Imagars LLCBaldur Steingrimsson Small Business Other Energy Technologies Imagars LLC provides engineering design software and services aimed primarily at mechanical design. Our patented Ecosystem is being used by mechanical engineering (ME) student design teams, in the US and Korea, both capstone, Formula and BAJA SAE teams. To companies in the automotive or aerospace industry, we offer software for requirement assessment and tracking, along with R&D services. In Phase II of our Small Business Innovative Research project with the National Science Foundation, we are developing a generic design framework capable of automatic verification of structured engineering requirements as well as improving design decision fidelity through application of big data analytics to repositories of known, good designs. The team behind Imagars consists of ME faculties from Portland State University, also with significant industry experience. Our distinguished software architect is a doctor from University of Minnesota with several awards from Intel for engineering excellence.


Phone: 7634396905

Address: 2062 NW Thorncroft Drive, Suite 1214, Hillsboro, OR, 97124, United States
 Cornell UniversityLang Tong Academic Grid Background:
machine learning---statistical inference, deep learning neural networks, reinforcement learning, signal processing
Optimization---stochastic and dynamic optimization. Markov decision processes.

Applying AI, machine learning, and data analytic tools in energy and power systems, large scale charging of electric vehicles, and smart grids.

-Online learning techniques for probabilistic forecasting of power systems and market operations.
-Deep learning and data-driven approaches in wide-area situation awareness: state estimation, online stability assessment, and quickest detection of voltage instability.


Phone: 6072553900

Address: ECE, Cornell University, ithaca, NY, 14853, United States
 IPS, Inc.Chris Franz Small Business Other Energy Technologies Secure Cloud Transitions
IPS and our commercial division, To t e m , have developed private, hybrid and public cloud architectures for customers ranging from the US Government to private Financial Technology companies. These systems provide scalability, cost efficiency and future readiness with security ranging from SEC/FINRA financial data to air-gap privacy at the top level. We help transition legacy architectures and applications into sustainable systems with a lower TCO.

Data Dominance
Data is the fuel source for business. Being able to organize what you have, collect what you want and stage the data for use is what
keeps you ahead. We prefer to layer data technologies to get you the best performance for the least risk. We use machine learning, blockchain,
tensors and artificial intelligence to get the most out of your data and ensure security. We turn data into decisions.

Custom Systems Engineering
We like the tough problems. From developing the first HD digital night vision system to architecting billion dollar satellite constellations, we pride ourselves on leveraging our expertise and the latest technology to make our customers more productive and profitable.

We specialize in enabling your company to flex with the ever-changing design or contractual requirements through Teaming and Subcontractor agreements.


Phone: 7193517020

Address: 4010 Hidden Rock Rd, Colorado Springs, CO, 80908, United States
 University of South CarolinaJianjun Hu Academic Other Energy Technologies Dr. Hu's research interests are in the area of machine learning, deep learning, data mining, big data, evolutionary computation and their applications in material informatics, bioinformatics and health informatics. Currently, his major research focus is developing deep learning algorithms for solving challenging application problems such as: intelligent audio/sound processing, data-driven material discovery, medical image analysis, genomics based disease gene discovery, protein-peptide binding prediction for drug design and protein design, big data driven analytics for prevention of HIVs, fault diagnosis and text mining. His research has been sponsored by NSF, NIH, Nvidia and Department of Transportation of South Carolina.

Interests: deep learning, machine learning, big data, and materials informatics

Capability: data driven predictive modeling, deep learning models for materials property prediction and screening, global optimization via genetic algorithm, open-ended design using genetic programming, bioinformatics.


Phone: 8037777304

Address: 550 Assembly Street, Storey Innov. Center, Columbia, SC, 29201, United States
 The University of UtahPania Newell Academic Power Generation and Energy Production: Fossil/Nuclear I have several years of experience working at DOE labs before starting my academic position. I have led several DOE projects through different offices such as Office of Basic Sciences and Fossil Energy. I am currently a PI on an EFRCs (MUSE).

My research interest lies at the intersect of theoretical, numerical, and experimental study of porous media. Topic such as:

• Multi-physics modeling and experimental study of porous media
• Computational modeling of fracture in porous media
• Multi-scale modeling of heterogenous porous systems
• Homogenization methods
• Physics-based machine learning techniques

• State-of-the-art nano-fab user facility
• Physics-based modeling tools


Phone: 801-213-3635

Address: 1495 East 100 South, Salt Lake City, UT, 84112, United States
 CrossnoKayeThomas Foley Small Business Other Energy Technologies CrossnoKaye was founded in 2017 by two Harvard applied physics Ph.D.s, soon joined by another physics Ph.D. in early 2018. As it's grown, CrossnoKaye's combined backgrounds and experiences now span a vast range of subjects. We are broadly interested in controls & automation, energy, and optimization. They develop and deploy high-level (control) strategies for industrial automation, with an emphasis on using bottom-up, physics-based modeling to inform and implement the strategies.

Our capabilities and expertise include:
-Thermodynamics and statistical mechanics
-Numerical optimization, including stochastic methods and convex
-Bayesian inference and statistics
-Physics-based modeling
-Controls theory and automation
-Machine learning
-Software development, from cloud-based optimization to PLCs
-Energy markets
-Industrial refrigeration
-Water treatment

CrossnoKaye creates and deploys high-level control strategies for large industrial facilities while employing modern software engineering practices and state-of-the-art modeling, inference, and machine learning techniques. By employing facility-level, energy-centric, and physics-based models of processes and their electricity usage, CrossnoKaye can transform facilities into on-demand virtual batteries and load-balancing assets. This transformation of energy-intensive industrial facilities helps balance the grid and improves system energy efficiency, all while saving operators money.

Through their partnership with Lineage Logistics, the largest cold storage company in the world, they conceived, developed, and deployed a strategy named 'thermal flywheeling’. Thermal flywheeling treats the contents of a facility as a large thermal battery, with the ability to ‘charge’ by over-cooling when electricity is cheap and ‘discharging’ (reducing electricity usage) when electricity is more expensive. By load-shifting in this manner, such facilities not only save operators’ money on energy spend but also help California overcome the so-called ‘duck-curve’ problem, which has otherwise hindered the adoption of renewables.


Phone: 5306323028

Address: 1129 State Street, Suite 1, Santa Barbara, CA, 93101, United States
 Hitachi America LTDBo Yang Large Business Grid Background: new product development in the area of T&D, renewable integration, distribution planning and operation

Interests: work with AI experts and data scientist to explore new solutions boosting model based grid analysis

Capabilities: We have a team with energy modeling, data analytics and software development capabilities


Phone: 6692619318

Address: 2535 Augustine Dr. 3rd floor, Santa Clara, CA, 95054, United States
 Vishwamitra Research InstituteUrmila Diwekar Non-Profit Power Generation and Energy Production: Fossil/Nuclear We work in the area of optimization under uncertainty with applications to fossil, nuclear power systems as well as renewable energy systems like solar and bioenenrgy. We have capability to model, optimize, and control of these systems in the face of uncertainties.


Phone: 6308863047

Address: 2714 Crystal Way, Crystal Lake, Crystal Lake, IL, 60012, United States
 analog photonicsEhsan Hosseini Small Business Other Energy Technologies Analog Photonics developed proprietary and patented integrated photonics technology on a CMOS-compatible 12” integrated photonics platform. Using a combination of silicon and silicon nitride as core waveguide layers our silicon photonics platform is low loss and can handle high optical power in the visible and near-infrared region of the electromagnetic spectrum. Having the capability to achieve both high, medium and low index contrast is at the basis of our state-of-the-art photonic components while maintaining a low footprint. The large temperature dependent refractive index of silicon enables highly efficient thermal tuning while the low temperature dependent refractive of silicon nitride enables temperature independent operation.


Phone: 4042909198

Address: suite 205, Boston, MA, 02210, United States
 DiakontTyler Powell Small Business Other Energy Technologies We specialize in robotic non-destructive examination (NDE) of pipelines and oil & gas storage tanks. We would like to use machine learning to reduce the amount of time required to analyze data and provide asset status information to the operators in a more timely manner. Our goal is to provide full reports to asset owners within 24 hours of completing the inspection (currently 30-60 days).

As part of our inspections, we collect large amounts of ultrasonic (UT) and electromagnetic acoustic (EMAT) data, then analyze it to determine metal thickness. We would like to use machine learning to correctly process the A-scan to measure the coating & metal thicknesses and then identify, classify & measure defects.


Phone: 8585515551

Address: 3193 Lionshead Ave, Carlsbad, CA, 92010, United States
 Michigan State UniversityJohn R. Dorgan Academic Bioenergy Broad expertise from 25 years of experience with biorefining issues. Former Site Director of the Colorado Center for Biorefining and Biofuels (C2B2), a consortium of three State Universities an the NREL DOE Lab. Knowledgeable in polymer membrane based separations.

Specialized deep expertise in polymer materials science with an emphasis on bioderived polymers and resins. Have developed renewable resin systems suited for manufacturing wind turbines. Active in IACMI and REMADE NNMIs.

Developed and maintained suite of molecular simulation codes for polymer materials discovery that are orders of magnitude faster than traditional MD methods. Interested in combining these codes with machine learning algorithms to design new biobased polymers, lubricants, and surfactants.


Phone: 3039565767

Address: 428 S. Shaw Lane, East Lansing, MI, 48824, United States
 San Diego State UniversityChris Mi Academic Transportation Has extensive experience in electric vehicle technology, including powertrain optimization, electric machines, power electronics, wireless charging, battery management.

Have taken on three ARPA_e projects and multiple EERE projects including the GATE center.


Phone: 7347658321

Address: 5500 Campanile Drive, E-426, San Diego, CA, 92130, United States
 EnPower, Inc.Adrian Yao Small Business Other Energy Technologies EnPower is developing next-generation Li-ion cells featuring advanced electrode architectures that enable significantly faster charging speeds, longer cycle life, and safety. EnPower has setup a pilot manufacturing and R&D facility in Phoenix, AZ capable of producing large capacity pouch cells from powder to product. EnPower is also integrating its cell technologies into advanced battery pack systems for various application industries, and has started using machine learning techniques for the optimization of real-cell performance in charge, discharge, and SOC estimation.


Phone: 8326933570

Address: 777 W Pinnacle Peak Rd. Ste B-109, Phoenix, AZ, 85027, United States
 U.C. BerkeleyAvideh Zakhor Academic Building Efficiency * Faculty member in EECS at UC Berkeley with expertise in machine learning
* Have led multiple ARPA-E projects in use of machine learning in building energy efficiency.


Phone: 5103843272

Address: University Of California, Berkeley, CA, 94720-0001, United States
 Kansas State UniversityChuancheng Duan Academic Power Generation: Renewable Keywords: Fuel cell, electrolyzer, materials design and evaluation.

Dr. Duan is an Assitant Professor at Kansas State University. His research focuses on fuel cells, electrolyzers, reversible fuel cells. His previous work on fuel cells and electrolyzers has been published in Nature, Science, and Nature Energy. He is emerging as the international/national leader in the field of intermediate-temperature protonic ceramic fuel cells (PCFCs) and protonic ceramic electrolysis cells (PCECs).

Expertise in materials design, fabrication, and characterizaiton.
Expertise in fuel cells, electrolyzers, and reversible fuel cells.

5+ years of experience of working on ARPA-E projects (REBELS and REFUEL)


Phone: 720-648-7886

Address: 1701A Platt St, Manhattan, KS, 66506, United States
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