Dr. Jason Matheny, IARPA Director
Dr. Jason Matheny became IARPA's director in 2015, after serving as a program manager, associate office director, and office director. Before IARPA, he worked at Oxford University, the World Bank, the Applied Physics Laboratory, the Center for Biosecurity and Princeton University, and is the co-founder of two biotechnology companies. Dr. Matheny holds a Ph.D. in applied economics from Johns Hopkins University, an M.P.H. from Johns Hopkins University, an M.B.A. from Duke University and a B.A. from the University of Chicago. He received the Intelligence Community's Award for Individual Achievement in Science and Technology.
Dr. Stacey Dixon, IARPA Deputy Director
Dr. Stacey Dixon joined IARPA as its Deputy Director in January 2016. Dr. Dixon joins us from the National Geospatial-Intelligence Agency (NGA) where she most recently served as Deputy Director of InnoVision and oversaw geospatial intelligence research and development. Prior to InnoVision, she served as NGA’s Chief of Congressional and Intergovernmental Affairs. From 2007 to 2010 she worked on the House Permanent Select Committee on Intelligence (HPSCI) staff, and for the Central Intelligence Agency (CIA) assigned to the National Reconnaissance Office (NRO)’s Advanced Systems and Technology Directorate from 2003 to 2007. Dr. Dixon holds doctorate and master’s degrees in mechanical engineering from the Georgia Institute of Technology, and a bachelor’s degree in mechanical engineering from Stanford University. She was a chemical engineering postdoctoral fellow at the University of Minnesota. Dr. Dixon is a native Washingtonian and currently resides in the District of Columbia.
Dr. William Vanderlinde, Chief Scientist
Dr. William Vanderlinde is IARPA’s Chief Scientist. He was a program manager from 2009 to 2012, leading the CAT and ATHENA programs. He re-joined IARPA in March 2015 as an office director, and became chief scientist in 2016. Dr. Vanderlinde’s work has focused on microelectronics and advanced microscopy, with applications to supply-chain assurance and high-performance computing. He hold two patents for high-resolution electron imaging and has published numerous peer-reviewed papers and book chapters. His previous positions include Technical Director of the DOD Microelectronics Research Laboratory and as Team Leader for Nanotechnology at the Laboratory for Physical Sciences. He was General Chair of the International Symposium for Testing and Failure Analysis in 2010 and serves on the Electron Device Failure Analysis Society Board of Directors. He holds a Ph.D. in materials science and engineering from Cornell University, an M.S. in electrical engineering from Johns Hopkins University and a B.S. in physics from the University of Virginia. He is a DNI Fellow and an elected Fellow of ASM International.
Dr. Paul Lehner, Chief of Testing and Evaluation
Dr. Paul Lehner is IARPA’s chief of testing and evaluation. He joined IARPA in 2015 as a program manager for the Scientific advances to Continuous Insider Threat Evaluation (SCITE) program, and became chief of testing and evaluation in 2016. Prior to IARPA, he worked at MITRE and served in several roles, including chief engineer for the Information Technology Division and the Internal Revenue Service Federally Funded Research and Development Center. Before MITRE, he was an associate professor of system engineering at George Mason University and the technical director for the Decision Systems Group at PAR Technology Corporation. Paul holds a bachelor’s degree in psychology from Bethany College in West Virginia. He has masters’ degrees in mathematics and psychology, and a doctorate in mathematical psychology from the University of Michigan. His doctoral dissertation focused on automated reasoning and strategic planning in the oriental game of Go.
Ms. Marianne Kramer, Chief of Technology Transition
Marianne Kramer is IARPA’s chief of technology transition. She joined IARPA in December 2017 from the National Geospatial-Intelligence Agency where she held the position of Technology Transition Lead for NGA Research. Prior to that, Ms. Kramer served as the Division Chief for Planning and Transition in InnoVision at NGA. Ms. Kramer represented NGA or its predecessor organizations (National Imagery and Mapping Agency and Defense Mapping Agency) by supporting geospatial intelligence and research efforts while stationed at Wright-Patterson Air Force Base in Ohio from 1995 – 2015. During that span, she spent two years with the Defense Intelligence Agency’s Central Measurement and Signature Intelligence Office. Ms. Kramer holds a master’s in analytical geography from Binghamton University and a master’s in leadership and change from Antioch University. She received her bachelor’s in humanities and anthropology from Providence College. Currently she is pursuing a doctoral degree in leadership and change at Antioch University. In 2017, she received the Sharon Parish Leader Award from NGA and she was party to an Intelligence Community Science and Technology team award in 2013.
IARPA was created in 2006 to conduct cross-community research, target new opportunities and innovations, and generate revolutionary capabilities, while drawing upon the technical and operational expertise that resides within the intelligence agencies. IARPA’s structure was modeled on that of the Defense Advanced Research Projects Agency. IARPA’s programs are uniquely designed to anticipate the long-term needs of, and provide research and technical capabilities for, the Intelligence Community. Agility is key in the IC and IARPA’s approach is to always look for, and seek out, new innovative ideas and perspectives.
Computing focuses on the IC's ability to operate freely and effectively in an often hostile and increasingly interdependent and resource-constrained environment. Key research focus areas include information assurance, advanced computing technologies and architectures, quantum information science and technology, and threat detection and mitigation.
Current Research | View Past Research
|Program||Research Area||Program Manager|
|C3||Advanced/alternative computing technologies, superconducting microelectronics||ManheimerMarc Manheimer|
|HECTOR||Secure multiparty computation, homomorphic encryption, verifiable computing, compilers, programming languages, automated security analysis||HeiligmanMark Heiligman|
|LogiQ||Advanced/alternative computing platforms, quantum information sciences, qubit systems||BlakestadBrad Blakestad|
|MICrONS||Theoretical neuroscience, computational neuroscience, machine learning, connectomics, brain activity mapping||MarkowitzDavid Markowitz|
|MIST||Polymer science, synthetic biology, synthesis technology, sequencing technology, storage controller technology, error-correcting codes||MarkowitzDavid Markowitz|
|QEO||Quantum annealing, combinatorial optimization, quantum error correction, non-stoquastic quantum interactions, multi-spin entanglement, classical annealing, Quantum Monte Carlo, population annealing, parallel tempering, adaptive annealing schedules with measurement feedback||VanderlindeBill Vanderlinde|
|RAVEN||Microelectronics, nondestructive analysis, nanoscale imaging, hardware assurance||McCantsCarl McCants|
|SuperCables||Superconducting electronics, photonics, cryogenics, optical communications||ManheimerMarc Manheimer|
|SuperTools||Superconducting electronics, advancements/alternatives to semiconductor-based exo-scale computing, cryogenic computing||HeiligmanMark Heiligman|
|TIC||Cybersecurity and information assurance, hardware assurance, microelectronics||McCantsCarl McCants|
|VirtUE||Computer virtualization, operating systems, cyber security, vulnerability analysis, insider threat remediation and detection, active defense, big data analytics, sensor fusion, user interfaces, anomalous event detection||LongKerry Long|
|CAT||Cybersecurity and information assurance, hardware assurance, microelectronics|
|CSQ||Advanced/alternative computing platforms, quantum coherence, coherent qubit, quantum information sciences|
|MQCO||Advanced/alternative computing platforms, quantum information sciences, qubit systems|
|QCS||Quantum information sciences|
|SPAR||Secure multiparty computation, private information retrieval, privacy and civil liberties protections|
|STONESOUP||Cybersecurity and information assurance, software assurance, vulnerability detection and mitigation|
The goal of collections research is to dramatically improve the value of collected data from all sources by developing new sensor and transmission technologies, new collection techniques that more precisely target desired information, and means for collecting information from previously inaccessible sources. In addition, IARPA pursues new mechanisms for combining information gathered from multiple sources to enhance the quality, reliability, and utility of collected information.
Areas of interest include:
- Innovative methods or tools for identifying and/or creating novel sources of new information
- Sensor technologies that dramatically improve the reach, sensitivity, size, weight, and power for collection of broad signal or signature types
- Methods for combining different measures and/or sensors to improve performance and accuracy of systems
- Approaches for assessing and quantifying the ecological-validity of behavioral, neuro- and social science research
- Secure communication to and from collection points
- Innovative approaches to gain access to denied environments
- Tagging, tracking, and location techniques
- Electrically small antennas and other advanced radio frequency (RF) concepts
- Agile architectures that intelligently distill useful information at the point of collection
- Innovative means and methods to ensure the veracity of data collected from a variety of sources
- Automated methods for sensor data fusion without predefined interface descriptions
- Approaches to enable signal collection systems to conduct more effective targeted information acquisition rather than bulk collection
- Tools to identify and mask signal streams and records that contain personal information to avoid unauthorized collection and dissemination.
Current Research | View Past Research
|Program||Research Area||Program Manager|
|Amon-Hen||Space situational awareness, optical interferometry, fiber optics, image reconstruction, computational imaging, small aperture telescopes, adaptive optics, astrometry, astronomy, optical sensors, optics, optical design||DeWitt;DeWittMerrick J. DeWitt|
|FELIX||Biological detection, systems biology, synthetic biology, genome editing, bioinformatics, evolutionary biology||Dion-SchultzAmanda Dion-Schultz|
|Fun GCAT||Bioinformatics, DNA sequence screening, functional genomics, systems biology, infectious disease, and synthetic biology||JuliasJohn Julias|
|HFGeo||Communication systems, ionosphere, antennas, geolocation, electromagnetics, radio frequency||CreekmoreTorreon Creekmore|
|Ithildin||Sorbent chemistry, polymer chemistry, encapsulation, nanotechnology, micro-engineered materials, reaction kinetics, chemical analysis techniques||Kristy DeWitt|
|LHO||Low acoustic small UAV aircraft, novel access, acoustic perception & minimum infrastructure||Sam Wilson|
|MAEGLIN||Chemical detection and identification (including standoff, remote, and ultra-compact/low power approaches), spectroscopy/spectrometry/chromatography, optical sensors, novel laser designs, frequency combs, nonlinear optics, fiber optic sensors/lasers/devices||DeWittKristy DeWitt|
|MOSAIC||Behavioral science, cognitive psychology, human performance, mobile computing, context sensing, signal processing, data fusion, machine learning, data privacy and security||JeannotteAlexis Jeannotte|
|Odin||Biometrics, presentation attack, machine learning, computer vision||BoehnenChris Boehnen|
|Proteos||Proteomics, single amino acid polymorphisms, genetically variable peptides, genomics, statistical analysis, molecular biology, human identification, forensic analysis, trace evidence samples||JordanKristen Jordan|
|SHARP||Cognition, psychometrics, fluid reasoning and intelligence, neuroscience, human performance||JeannotteAlexis Jeannotte|
|SILMARILS||Chemical detection and identification (including standoff, remote, and ultra-compact/low power approaches), spectroscopy/spectrometry/chromatography, optical sensors, novel laser designs, frequency combs, nonlinear optics, fiber optic sensors/lasers/devices||DeWittKristy DeWitt|
|BEST||Biometrics, facial recognition, sensors, perception|
|BIC||Weapons of mass destruction, chemical/biological warfare, human biomarkers, emerging biotechnologies|
|GHO||Low acoustic aircraft propulsion, low acoustic power generators, novel access, sensors, perception|
|SLiCE||Communication systemts, geolocation, electromagnetics, radio frequency|
|TRUST||Interpersonal trust, neurophysiology, behavioral science, advanced data analytics, social science|
Anticipatory intelligence focuses on characterizing and reducing uncertainty by providing decision makers with timely and accurate forecasts of significant global events. This research explores or demonstrates the feasibility of revolutionary concepts that may deliver real-time indications and warning, in context, to support rapid, nuanced understanding by intelligence consumers.
Our programs are technically diverse, but each program:
- Develops technologies to generate timely forecasts for well-defined events and their characteristics (e.g., who, what, when, where, and how).
- Uses a rigorous, open and ongoing test and evaluation process.
- Has metrics that include lead time, accuracy, false positive and false negative rates, and are calculated by comparing forecasts to real-world events.
- Communicates forecasts in context.
Key research areas include forecasting events related to science and technology (S&T); social, political, and economic crises; epidemiology and biosecurity; counterintelligence; and cybersecurity.
Current Research | View Past Research
|Program||Research Area||Program Manager|
|CAUSE||Cybersecurity, cyber-event forecasting, cyber-actor behavior and cultural understanding, threat intelligence, threat modeling, cyber-event coding, cyber-kinetic event detection||RahmerRobert Rahmer|
|CREATE||Forecasting, logic and critical thinking, human judgment||RieberSteven Rieber|
|FUSE||Technical emergence, text analytics, knowledge discovery, big data, social network analysis, natural language processing, forecasting, machine learning||RahmerRobert Rahmer|
|FOCUS||Counterfactual reasoning, evidence-based approaches to lessons-learned analyses, analytic tradecraft, cognitive biases||LehnerPaul Lehner|
|HFC||Forecasting, human judgment, machine learning, decision making, human/machine interfaces, text analysis||GoldsteinSeth Goldstein|
|Mercury||SIGINT analytics, event forecasting, machine learning, streaming data, data fusion, weapons of mass destruction, chemical/biological warfare, human biomarkers, emerging biotechnologies||JordanKristen Jordan|
|SCITE||Engineering enterprises that detect low probability events with low accuracy sensors, innovative research methods to evaluate analytic and forecasting tradecraft, innovative statistical methods to estimate performance of systems addressing complex analysis and forecasting problems, scientific research on organizational lessons-learned methods, evidence-based forecasting methods, inductive logic, probabilistic reasoning and its application to analytic tradecraft||LehnerPaul Lehner|
|ACE||Forecasting, human judgment, machine learning, logic, critical thinking|
|ForeST||Forecasting, human judgment, machine learning, technical emergence, text analytics, big data, natural language processing|
|OSI||Large/errorful data sets, forecasting, public health, machine learning|
Analysis focuses on maximizing insights from the massive, disparate, unreliable and dynamic data that are—or could be—available to analysts, in a timely manner. We are pursuing new sources of information from existing and novel data, and we are investigating innovative techniques that can be utilized in the processes of analysis. Our programs are in diverse technical disciplines but have common features:
- Involve potential transition partners at all stages, beginning with the definition of success;
- Create technologies that can earn the trust of the analyst
user by providing the reasoning for results;
- Address uncertainty and data provenance explicitly.
Current Research | View Past Research
|Program||Research Area||Program Manager|
|BETTER||Human language technology, natural language processing, information extraction, information retrieval, active learning, multilingual processing||BeielerJohn Beieler|
|CORE3D||Mulit-view satellite image processing, multi-modal information fusion, deep learning, remote sensing, photogrammetry, image segmentation and classification, multispectral imagery processing, and geospatial volumetric 3D data representation methods||KimHakjae Kim|
|DIVA||Machine learning, deep learning or hierarchical modeling, artificial intelligence, object detection, recognition, person detection and re-identification, person action recognition, video activity detection, tracking across multiple non-overlapping camera viewpoints, 3D reconstruction from video, super-resolution, stabilization, statistics, probability and mathematics||AdamsTerry Adams|
|Janus||Computer vision, image processing, pattern recognition, biometrics, facial recognition, identity intelligence, computer graphics||BoehnenChris Boehnen|
|MATERIAL||Natural language processing, machine translation, cross-lingual information retrieval, domain recognition and adaptation, multilingual ontologies, Multilingual speech recognition, cross-lingual summarization, keyword search algorithms, low resource languages, automatic language identification, machine learning, rapid adaptation to new languages, domains and genres||RubinoCarl Rubino|
|Aladdin Video||Image, photgraph, video, multimedia, computer vision, natural language processing, image processing, big data, video analytics, machine learning, speech processing|
|Babel||Multilingual/multidialectal speech recognition, keyword search algorithms, speech recogntion in noisy environments, low resource languages, rapid adaptation to new languages and evironments, machine learning|
|Finder||Geolocation, localization, geospatial fusion, data fusion, machine learning, big data, image processing, image, photograph, video, multimedia, computer vision, natural language processing|
|ICArUS||Knowledge discovery, brain, neuroscience, artificial intelligence, cognitive bias, judgment, decision making, behavioral science, human factors, training, tradecraft, data sense-making|
|KDD||Ontologies, alignment, information extraction, clustering, natural language processing, social network analysis, summarization, query expansion, document similarity, machine learning|
|KRNS||Knowledge discovery, brain, neuroscience, artificial intelligence, cognitive bias, judgment, decision making, behavioral science, human factors, training, tradecraft, data sense-making, linguistics, language, semantics, culture|
|Metaphor||Natural language processing, cognitive science, cognitive linguistics, conceptual metaphors, metaphors, culture, automatic cultural insights from metaphors|
|Reynard||Social media, online games, virtual worlds, socio-cultural and linguistic factors|
|Sirius||Analytic insight and productivity, serious games, judgment, decision making|
|SCIL||Natural language processing, sociology of groups, sociolinguistics, group behavior, social groups, online interaction, social roles|
|SHO||Usability of analytic products, visualization|
2017 Year in Review
2017 was another banner year for IARPA. Here are the highlights:
- 9 new multi-year research programs covering diverse technical fields, including biosecurity, event forecasting, space situational awareness, homomorphic encryption, human identification, and superconducting electronics
- 13 single-year seedling studies researching topics, such as Bloom filters, a dual comb spectrometer, and infra-red imaging sensors
- 4 new public prize challenges offering cash awards to innovators across the globe
- 48 technical workshops with over 3,000 attendees
- Over 190 peer-reviewed publications from IARPA-funded research
- 34 transition agreements to transfer IARPA-funded technologies to other government agencies
- Over 250 research publications from current and past IARPA programs, uploaded to the Defense Technical Information Center registered user site. This includes more than 70 publications available to the public through DTIC’s public user site
IARPA-funded research highlights:
The Babel program has become a goldmine for speech scientists, with over 50 scientific publications citing use of Babel data in 2017 alone. A total of 757 Babel speech data sets have been distributed to 136 different organizations with a goal to continue to advance speech technology research under low-training conditions.
The SILMARILS program demonstrated trace explosive detection capabilities beyond the program’s difficult targets. Phase 1 of the program developed record-setting component technologies for hypercube acquisition speed and power, as well as wavelength coverage and flatness for infrared supercontinuum sources. For this breakthrough, and others, the SILMARILS PM, Dr. Kristy DeWitt, was awarded the Intelligence Community’s Award for Individual Achievement in Science and Technology.
One of the FUSE program’s software and models for prediction of emerging technologies is now available to the public. Meta is a tool that helps researchers understand what is happening globally in science and shows them where science is headed.
The MORGOTH’S CROWN prize challenge used machine-learning approaches to develop algorithms that improve chemical detection on complex surfaces and in cluttered environments.
The QEO program demonstrated the feasibility of quantum machine learning by using a quantum annealing system to train multiple classes of artificial neural networks for image recognition and reconstruction tasks.
The N2N prize challenge collected fingerprint data from 354 human subjects during a week-long event, producing over 40,000 rolled fingerprint images and 30,000 black powder and chemically processed latent fingerprint lifts. In addition to facilitating evaluation of challenge prototypes, this data will be made available to the research community to improve latent fingerprint matching.
The EMBERS event forecasting system, developed under the OSI program, is now a commercial offering of Virginia Tech Applied Research Corporation. Organization can now purchase the system’s daily forecasts for a particular set of countries.
The fMoW prize challenge provides a satellite imagery dataset with one million points of interest annotated to researchers and entrepreneurs, enabling them to better understand satellite imagery through novel learning frameworks and multi-modal fusion techniques.
The interagency team of IARPA’s Finder and NGA’s HUNTER programs won the Intelligence Community Science and Technology team award. The IARPA/NGA team developed a revolutionary approach to geolocation of arbitrary ground level images. The application has been successful world-wide.
The Janus program has made significant advances in face recognition. The technology is now capable of finding the correct subject (rank 1) 95% of the time on a challenging gallery with over 1 million subjects.
The MICrONS program delivered the largest-ever maps of neocortical circuit structure and function to inform the development of next-generation machine learning algorithms. In parallel with this work, MICrONS performers launched seven startup companies with over $30M of private funding to commercialize technologies developed through the program.
The HFGeo program has advanced ionospheric modeling by developing and applying new assimilation algorithms. Ionospheric data assimilation is a technique to evaluate the 3-D time-varying distribution of free electron density, using a combination of physics-based modeling and observations.
The LogiQ program’s efforts to achieve an error-corrected quantum bit (aka, a qubit) helped to advance quantum computing technology. This led to new quantum-algorithm demonstrations, an improved understanding of noise and errors in these systems, and realization of systems with more than 15 qubits.
Research data sets from ACE and OSI programs have been posted to Harvard University’s Dataverse Project. This information is now publically searchable and easily citable in the world’s largest collection of social science research, and has been downloaded over 700 times. Two papers authored by researchers not part of the original IARPA-funded program were published in 2018 using this data.
IARPA media highlights: