Category Archives: IARPA

Intelligence Advanced Research Projects Activity

IARPA Amon-Hen BAA

The Intelligence Advanced Research Projects Activity (IARPA) has released the Amon-Hen BAA, IARPA-BAA-17-02.  The Amon-Hen program seeks innovative, low-cost approaches for passive, ground-based interferometric imaging of GEO satellites.

“The Intelligence Community (IC) needs to ensure Space Situational Awareness (SSA) and monitor the operational status of US Government satellites in geosynchronous earth orbit (GEO). Capabilities that enhance our ability to visually monitor these satellites, particularly through passive, ground-based observation, will help address this need. These capabilities become more relevant as the total number of GEO satellites and the number of related objects (like spent fuel tanks and other debris) continue to grow and as existing GEO satellites approach the end of their operational lifetimes.

The IARPA Amon-Hen program seeks novel interferometric approaches that enable the development of low-cost imaging systems (overall system cost reductions of greater than one order of magnitude) without significantly impacting other performance capabilities when compared to existing designs.

The Amon-Hen program is envisioned as a 33-month effort that is intended to begin by March 2018. Phase 1 will last for a period of 15 months and will focus on the development of component technologies, the development of physics-based system modeling capabilities, and the development of image reconstruction algorithms. Phase 2 will be 18 months and will focus on further maturation of component technologies and subsystems to bread board capabilities enabling an end-of-phase, open sky measurement. Following the conclusion of Phase 1, down selection is possible for a variety of reasons including but not limited to underperformance. Program progress will be periodically assessed to justify program continuation. Successful completion of Phase 2 efforts may result in an additional funding opportunity to advance the results of Phase 2 to a full demonstration. The actual goals and metrics for this potential full demonstration effort will be determined at that time.”

Multiple awards are anticipated. Proposals are due August 11, 2017.  Merrick DeWitt is the Program Manager.

 

 

IARPA DNAtoFace RFI

IARPA has released a RFI titled “DNAtoFace”, IARPA-RFI-17-01.

Advancements in genetic phenotyping suggests the possibility of predicting a human’s facial structure or other attributes from DNA sequences. IARPA is interested in knowing whether single nucleotide polymorphisms (SNP) yield sufficient information for making such prediction or if the whole genome sequence is required.

Responses to this RFI should answer any or all of the following questions:

  1. What is the maturity and level of accuracy of genetic phenotyping outside of gender and genetic ancestry? Is additional information required to phenotype specific characteristics (e.g., height, eye color, skin tone, face structure, etc.)?
  2. Who are the major government, industry, and academic leaders in the field of genetic phenotyping?
  3. Compare and contrast the leading approaches and techniques for genetic phenotyping. Are any commercial capabilities available?
  4. What level of confidence are geneticists, scientists, or researchers able to predict major phenotype information (e.g., height, eye color, skin tone, face structure, etc.) from a whole DNA sequence? Is additional information outside the whole DNA sequence required?
  5. What is the impact of utilizing SNP as opposed to whole genome sequencing for predicting genotype to phenotype? Specifically, can facial structure prediction (phenotyping) be achieved with using just SNP? Will (and how will) this limit the accuracy of the predictions? Does the number of SNP collected (e.g., 500,000, 1,000,000, or 5,000,000) impact ability to predict a phenotype from genotype? Which specific SNP should be captured for a face structure phenotype prediction?
  6. How many subjects are needed to train a model to predict facial structure and appearance from both SNP and whole genome sequences? Is the required sample size different for SNP versus whole genome sequencing? Does ethnicity, age, or gender impact the required number of subjects?
  7. What large-scale SNP or whole genome sequence databases are available in government, academia, and industry? Do they contain corresponding face images? What are the terms of use for such databases?
  8. How will epigenetic factors play into any resulting analysis of attributes? What types of epigenetic tests and methodology should be considered?
  9. What types of statistical analysis have been done utilizing methods such as power analysis to determine how many subjects are needed to analyze non-disease based phenotypes? Please identify any research (peer reviewed or otherwise) that addresses the sampling needs from a theoretical or quantitative perspective.
  10. What other issues do you feel are important to being able to predict non-disease phenotypes from genetic information?

Responses to the RFI are due December 16, 2016.

IARPA Virtuous User Environment (VirtUE) Phase 1 BAA

IARPA has released the Virtuous User Environment (VirtUE) Phase 1 BAA, IARPA-BAA-16-12.  The goal of VirtUE is to “creatively define and develop new, inherently secure, virtual user environments.”

VirtUE seeks to “leverage the federal government’s impending migration to commercial cloud-based information Technology (IT) infrastructures and the current explosion of new virtualization and operating system (OS) concepts to create and demonstrate a more secure interactive user computing environment (UCE) than the government has had in the past or likely to have in the near future. Currently the government UCE is represented by a general purpose Windows desktop OS running multiple installed applications hosted on either a dedicated physical computer or on a shared virtualized platform. When a desktop OS is hosted on a shared virtualized platform, it is called a virtualized desktop interface or VDI.

In Phase 1, VirtUE seeks to deliver an interactive UCE designed from the outset to be a more secure, capable sensor and defender in the cloud environment than the current government UCE solution. To be acceptable to potential government consumers, the new UCE must still offer functionality and performance characteristics comparable to the current government UCE. Phase 1 performers shall create a UCE that mitigates the exploitation of legacy and cloud-based vulnerabilities and/or provides numerous logging and protection options for future external security logic to do so.

In Phase 2, performers shall take the technologies and/or concepts developed in Phase 1 and create novel external analytics and security controls that leverage them. The purpose of this analytics/control effort is to create dynamic detection and protection capabilities that make the VirtUE user environment more resistant to attacks expected in the commercial cloud while minimizing the costs associated with these capabilities.”

Proposals are due December 12, 2016.  The Program Manager is Kerry Long.

iarpa-virtue-concept

IARPA Virtue Concept.

IARPA Deep Intermodal Video Analytics (DIVA) BAA

IARPA has released the Intermodal Video Analytics (DIVA) BAA, IARPA-BAA-16-13.  The DIVA program seeks to develop robust automatic activity detection for a multi-camera streaming video environment. Activities will be enriched by person and object detection. DIVA will address activity detection for both forensic applications and for real-time alerting.

“The volume of video data collected from ground-based video cameras has grown dramatically in recent years. For mounted cameras with rigid motion, such as pan-tilt-zoom, the video data is predominantly collected for security, public safety, transportation and infrastructure monitoring, and primarily used for forensic, legal and insurance purposes. The need to guard against theft, crime or attacks continues to rise. However, there has not been a commensurate increase in the usage of intelligent analytics for real-time alerting or triaging video. In many cases, security personnel or operators of camera networks are overwhelmed with the volume of video they must monitor, and cannot afford to view or analyze even a small fraction of their video footage. Yet, the task of monitoring video in airports, at border crossings, or at government facilities becomes increasingly critical each year. In addition, when incidents do occur and officials are tasked with forensically analyzing large volumes of video, it is manually intensive, to identify relevant activities and the subjects of those activities. DIVA aims to develop technology to automate much of this analysis.”

DIVA will “significantly push the state-of-the-art in three areas:

  • Automatic detection of activities, as well as persons and objects, in cluttered scenes,
  • Temporal reasoning of video to greatly improve activity detection,
  • Activity detection and scene understanding from overlapping and non-overlapping camera viewpoints.”

The Proposers Day was July 12, 2016.  Proposals are due November 7, 2016.  The Program Manger is Terrence Adams.

IARPA Multimodal Objective Sensing to Assess Individuals with Context (MOSAIC) BAA

IARPA has released the Multimodal Objective Sensing to Assess Individuals with Context (MOSAIC) BAA, IARPA-BAA-16-10.  The MOSAIC program “seeks innovative approaches to unobtrusive, passive, and persistent measurement to predict an individual’s job performance.”

“Current tools to evaluate the workforce, such as interviews, cognitive assessments, and questionnaires, while often highly predictive of job performance, may only provide a snapshot of an individual in a controlled testing environment. As such, they may not capture more dynamic or context-dependent aspects of an individual. Traditional tools may suffer other limitations, such as lengthy administration times or susceptibility to measurement artifacts (e.g., practice effects, impression management, test anxiety).

To address such limitations, the MOSAIC program seeks to fund rigorous, high-quality research to develop and validate unobtrusive, passive, and persistent sensor-based methods to assess stable and dynamic psychological, cognitive, and physiological aspects of an individual. The research will take advantage of advancements in sensors, data collection architectures, feature extraction methods, data fusion techniques, as well as the modeling and analysis of rich spatiotemporal data generated from the collection of an individual’s daily actions and responses. Performers will employ a variety of sensors (mobile, worn, and carried sensors, social media applications, etc.) to measure individuals and the environment around them (e.g., time, light, temperature, sound, interpersonal interactions) to develop personalized and contextualized assessments of an individual over time.”

Proposals are due November 10, 2016.  The program manager is Dr. Alexis Jeannotte.

IARPA Functional Genomic and Computational Assessment of Threats (Fun GCAT) BAA

IARPA has released the Functional Genomic and Computational Assessment of Threats (Fun GCAT) BAA, IARPA-BAA-16-08.

The Functional Genomic and Computational Assessment of Threats (Fun GCAT) program “intends to develop new approaches and tools for the screening of nucleic acid sequences, and for the functional annotation and characterization of genes of concern, with the goal of preventing the accidental or intentional creation of a biological threat. Advances in biotechnology and synthetic biology over the past decade have the potential to address important societal challenges in food, energy, and medicine. Despite the promising advances these technologies might enable, the potential for their deliberate or accidental misuse exists, warranting the development of approaches to help prevent the creation of biothreats.”

“In order to better address biosecurity concerns, the Fun GCAT program intends to develop next-generation computational and bioinformatics tools to improve DNA sequence screening, to augment biodefense capabilities through the characterization of threats based on function, and to advance our understanding of the relative risks posed by unknown nucleic acid sequences.”

The Fun GCAT Program is anticipated to have three phases over 3.5 years. All Phases will have two thrusts:

  • Thrust 1: Develop bioinformatic and computational tools and approaches that allow faster sequence comparison and assess threat potential. Various approaches are anticipated, and could include prediction of protein structure and/or function for both known and uncharacterized sequences.
  • Thrust 2: Significantly advance experimental methods for the characterization of genetic sequence function. Performers will choose sequences from model systems (e.g. bacteria, viruses, and toxins), or host elements involved in pathogenesis or the response to infection.

Proposals are due November 8, 2016.  Multiple awards are anticipated.  The program manager is Dr. John Julias.

IARPA Nail to Nail (N2N) Participants Day Webex

IARPA has announced the Participants Day for the Nail to Nail (N2N) Fingerprint Grand Prize Challenge on Thursday, October 13, 2016.  The purpose of the WebEx will be to provide information about the challenge in anticipation of its release, allowing potential participants to ask questions and receive community feedback.

The goal of the N2N Fingerprint Grand Prize Challenge is to “improve live and forensic biometric fingerprint recognition by improving N2N fingerprint enrollment capture technology and the elimination of a human operator to roll the fingerprints. N2N fingerprint, sometimes referred to as ‘rolled’, captures the entire fingerprint from one edge of the fingerprint nail bed to the other. The existing N2N enrollment standard utilizes a skilled operator who holds and physically ‘rolls’ the subjects fingerprints over a surface in order to capture the sides and bottom of the fingerprint.”

The objectives of the prize challenge “is to produce an automated capture technology that can eliminate a human operator physically interacting with the subject (such as rolling their prints) for N2N capture. Additionally, the automated capture technology must collect fingerprint data that performs as good as or better than the traditional rolled biometric gold standard. A human may be present and provide basic verbal instructions, but there should be no physical contact between the human collector and the fingerprint collection subject.

It is anticipated that there will be three smaller prizes and one Grand Challenge Prize with a total prize purse of $175,000.”  Registration for the WebEx is available at http://eventmanagement.cvent.com/events/iarpa-nail-to-nail-n2n-fingerprint-grand-prize-challengewebex/event-summary-ee4bd1bc430847808f5badeb95e9a019.aspx.

 

 

IARPA Hybrid Forecasting Competition (HFC) BAA

IARPA has released the Hybrid Forecasting Competition (HFC) BAA, IARPA-BAA-16-02.

The HFC program seeks to “develop and test hybrid geopolitical forecasting systems. These systems will integrate human and machine forecasting components to create maximally accurate, flexible, and scalable forecasting capabilities. Human-generated forecasts may be subject to cognitive biases and/or scalability limits. Machine-generated (i.e., statistical, computational) forecasting approaches may be more scalable and data-driven, but are often ill-suited to render forecasts for idiosyncratic or newly emerging geopolitical issues. Hybrid approaches hold promise for combining the strengths of these two approaches while mitigating their individual weaknesses. Performers will develop systems that will integrate human and machine forecasting contributions in novel ways. These systems will compete in a multiyear competition to identify approaches that may enable the Intelligence Community (IC) to radically improve the accuracy and timeliness of geopolitical forecasts.”

Proposals are dueNovember 14, 2016.  The Program Manager is Seth Goldstein.

IARPA Proposers’ Day for Machine Translation for English Retrieval of Information in Any Language (MATERIAL) Program

IARPA has announced the Proposers’ Day for the Machine Translation for English Retrieval of Information in Any Language (MATERIAL) program, IARPA-BAA-16-11, on September 27, 2016.

The MATERIAL program “will develop an “English-in, English-out” information retrieval system that, given a domain-sensitive English query, will retrieve relevant data from a large multilingual repository and display the retrieved information in English as query-biased summaries. MATERIAL queries will consist of two parts: a domain specification and an English word (or string of words) that capture the information need of an English-speaking user, e.g., “zika virus” in the domain of GOVERNMENT vs. “zika virus” in the domain of HEALTH, or “asperger’s syndrome” in the domain of EDUCATION vs. “asperger’s syndrome” in the domain of SCIENCE. The English summaries produced by the system should convey the relevance of the retrieved information to the domain-limited query to enable an English-speaking user to determine whether the document meets the information needs of the query.

Current methods to produce similar technologies require a substantial investment in training data and/or language specific development and expertise, entailing many months or years of development. A goal of this program is to drastically decrease the time and data needed to field systems capable of fulfilling an English-in, English out task.”

Registration is required no later than 5:00PM EDT on September 20, 2016, at https://eventmanagement.cvent.com/MATERIALPDREGISTRATION. No walk-in registrations will be allowed. Due to space limitations, attendance will be limited to the first 150 registrants.

IARPA SuperTools BAA

IARPA has released the SuperTools BAA, IARPA-BAA-16-03SuperTools seeks to develop a superconducting circuit design flow with a comprehensive set of Electronic Design Automation (EDA) and Technology Computer Aided Design (TCAD) tools for Very-Large-Scale Integration (VLSI) design of Superconducting Electronics (SCE).

“The overarching goal of the SuperTools program is the creation of a full suite of design tools that will facilitate the design of an SCE central processing unit (CPU) as well as other complex SCE circuits. The art of digital design for SCE has seen very simple handcrafted circuits run with clock speeds in excess of 500 GHz. However, even modestly sized handcrafted circuits sometimes fail to work at all. Whether very fast and low power complex SCE circuits can be designed with suitable modified Computer Aided Design (CAD) tools is the challenge that the SuperTools program must address.

IARPA’s SuperTools program is closely coordinated with other IARPA programs in SCE, and in particular with the C3 program. It is expected that software developed for the SuperTools program will be made available to the C3 program for use in that program’s Logic Design thrust.

Multiple awards are anticipated. Proposals are due August 1, 2016. The Program Manager is Mark Heiligman.