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DARPA page explicitly states 'This program is now complete' and content is for reference purposes only.
Symbiotic Design for Cyber Physical Systems (CPS) is a DARPA research program that funds the development of AI-based approaches to enable correct-by-construction design of military-relevant cyber-physical systems including unmanned vehicles, weapon systems, and mission platforms.
The program aims to reduce CPS development timelines from years to months by addressing three core challenges: predictability of design decisions, convergence of federated design teams, and design space exploration. Total program funding is approximately $5. 6 million awarded to research teams.
Eligible applicants are research teams including academic institutions and other organizations with multidisciplinary expertise in AI, software, control systems, mechanical engineering, and related domains.
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Symbiotic Design for Cyber Physical Systems Department of War organization. SDCPS: Symbiotic Design For Cyber Physical Systems SDCPS: Symbiotic Design for Cyber Physical Systems Cyber physical systems (CPS) are instrumental to current and future Department of Defense (DoD) mission needs – unmanned vehicles, weapon systems, and mission platforms are all examples of military-relevant CPS.
These systems and platforms integrate cyber and physical subsystems, and the enormous complexity of the resulting CPS has made their engineering design a daunting challenge. An immediate consequence of this complexity is development cycles with prolonged timelines that challenge DoD’s ability to counter emerging threats.
CPS design is a complex endeavor that involves many domains – from cyber (e.g., software, control, computing, and communication) to physical (e.g., structural, mechanical, thermal, etc.) to manufacturing – and upwards of hundreds of domain-specific tools orchestrated by large teams of engineers with extensive domain knowledge and subject matter expertise.
Current engineering design processes start with requirements-driven decomposition into discipline-specific design flows that, at their core, are concurrently running sequential decision-making processes that involve generating candidate architectures; evaluating, selecting, and refining options; and integrating the design until requirements are satisfied.
The goal of the Symbiotic Design for CPS (SDCPS) program is to develop AI-based approaches to enable correct-by-construction design of military-relevant CPS. SDCPS seeks to reduce the time from CPS inception to deployment from years to months, and enhance innovation in design.
To accomplish this, SDCPS will address the following three intrinsic challenges: Predictability – The soundness of design decisions relies on accurate predictions of performance prior to the implementation of software and physical components. However, accurate predictions require high-fidelity models that are cost- and time-prohibitive to produce. Cost-effective modeling processes produce results with substantial uncertainty.
Convergence – Design teams are federated according to discipline boundaries. However, separation of concerns within a complex system neglects the interdependence of design decisions, rendering rapid convergence to a viable integrated solution practically impossible. Exploration – Limited by time and resources, engineers have to make tradeoffs that constrain the exploration of the design space to the familiar and known-feasible.
This leaves vast areas of design space unexplored, which may contain unconventional but highly performant solutions.
The vision of the program is to vastly expand coverage and accelerate exploration of CPS design spaces with the symbiosis of two very different kinds of agents: humans with their uncanny ability to create intuitive associations across design domains, and machines with their ability to recognize statistical patterns from data and navigate vast search spaces for optimal solutions.
The program aims to realize this vision by transforming the human-focused model-based design flows used today into a symbiotic process of collaborative discovery by humans and continuously learning AI-based co-designers. For more information, please see the Symbiotic Design for Cyber Physical Systems Proposers Day Announcement and the Symbiotic Design for Cyber Physical Systems BAA .
Information Innovation Office This program is now complete This content is available for reference purposes. This page is no longer maintained. Symbiotic Design for Cyber Physical Systems Meeting
Based on current listing details, eligibility includes: Research teams, including academic institutions and potentially other organizations, collaborating on AI-based approaches for cyber-physical systems. Applicants should confirm final requirements in the official notice before submission.
Current published award information indicates Total $5.6 million awarded to a team, with individual sub-awards (e.g., $437,023 for Penn State lead) Always verify allowable costs, matching requirements, and funding caps directly in the sponsor documentation.
The current target date is rolling deadlines or periodic funding windows. Build your timeline backwards from this date to cover registrations, approvals, attachments, and final submission checks.
Federal grant success rates typically range from 10-30%, varying by agency and program. Build a strong proposal with clear objectives, measurable outcomes, and a well-justified budget to improve your chances.
Requirements vary by sponsor, but typically include a project narrative, budget justification, organizational capability statement, and key personnel CVs. Check the official notice for the complete list of required attachments.
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The OCRP Outcomes Consortium Development Award supports a multi-institutional research effort conducted by leading ovarian cancer researchers and consumer advocates that specifically focuses on identifying and understanding predictors of disease outcomes in ovarian cancer patients. This effort will be executed through a two-stage approach using two separate award mechanisms: this FY12 Outcomes Consortium Development Award, which will enable the consortium to lay the groundwork for the research project, including proof of concept, and the FY14 Outcomes Consortium Award, which will support the execution of the full research project. Funding Opportunity Number: W81XWH-12-OCRP-OCDA. Assistance Listing: 12.420. Funding Instrument: CA,G. Category: ST. Award Amount: $1.3M total program funding.
Small Business Innovation Research (SBIR) Program 25.1 Solicitation is sponsored by Department of Homeland Security (DHS) Science and Technology Directorate (S&T). The DHS SBIR Program invites U.S. small businesses to submit research proposals addressing technology needs in fentanyl source profiling, data analysis tools, digital injection attack prevention, and wired interconnection cables or adapters.
Operation Stonegarden (OPSG) is a federal grant program administered by FEMA through the Office of the Governor's Public Safety Office that funds enhanced border security cooperation among Customs and Border Protection (CBP), U.S. Border Patrol, and state, local, tribal, and territorial law enforcement agencies. The program supports joint operations to secure land and water border routes, improve intelligence sharing, and expand 287(g) screening operations within correctional facilities. In 2025, the national priority is Supporting Border Crisis Response and Enforcement, covering training, operational coordination, and risk management. Eligible expenses include operational overtime costs, staffing support for screening activities, and training programs in immigration law, civil rights protections, and 287(g) procedures.