News & Events
Awards and Achievements
Infographic: ALERT’s Year 5 (2017-2018) Accomplishments January 29, 2019
January 29, 2019
As we begin the New Year, we are also looking back on the previous year! Check out our newest infographic on ALERT’s Year 5 (2017-2018) Accomplishments.
ALERT Researchers Selected as IEEE Fellows January 29, 2019
January 29, 2019
Please join us in congratulating the newly elevated IEEE Fellows for the Class of 2019! We are especially proud of ALERT researchers Mario Sznaier of Northeastern University, and David Castañón and Venkatesh Saligrama of Boston University for this significant achievement. IEEE Fellow is a distinction reserved for select IEEE members whose extraordinary accomplishments in any of the IEEE fields of interest are deemed fitting of this prestigious grade elevation. The total number selected in any one year does not exceed one-tenth of one percent of the total voting IEEE membership.
Mario Sznaier is a Northeastern University ECE Professor and co-leads ALERT Project R4-A.1. Sznaier has been elevated to an IEEE Fellow for his contributions to identification of switched systems and multiobjective control. His work on Project R4-A.1 aims to substantially enhance our ability to exploit surveillance camera networks to predict and isolate threats from explosive devices in heavily crowded public spaces, and to guide complementary detection modalities, subsequent to a threat alert.
David Castañón and Venkatesh Saligrama are Boston University ECE Professors and collaborators on ALERT Project R4-A.2. Castañón has been elevated to an IEEE Fellow for his contributions to discrete-time stochastic control and information fusion. Saligrama has been elevated to an IEEE Fellow for his contributions to distributed detection and estimation of structured signals. Their work on Project R4-A.2 aims to leverage machine learning and computer vision methods for surveillance over multi-camera networks and to develop methods that are capable of real-time and forensic detection of suspicious activity.
ALERT Awarded Two New Task Orders November 29, 2018
Maturation and Validation of Dielectric Characterization Algorithms Task Order
ALERT has received a task order contract from the Department of Homeland Security (DHS) Science & Technology Directorate (S&T) to mature and operationalize the Advanced Imaging Technology material characterization (complex dielectric constant) algorithms being developed in ALERT Projects R3-A.2 and R3-B.1, led by ALERT Researchers, Dr. Carey Rappaport and Dr. Jose Martinez-Lorenzo of Northeastern University, respectively.
The task order, known as the “Maturation and Validation of Dielectric Characterization Algorithms,” will allow ALERT to use DHS owned images captured originally for the DHS S&T/TSA “Passenger Screening Algorithm Challenge.” The data for this prize competition was originally captured on the Apex Screening at Speed (SaS) High Definition – Advanced Imaging Technology (HD-AIT) laboratory prototype designed by Pacific Northwest National Lab. These images are available in several different file formats, including raw reflectivity formats. The data also includes ground truth information including relative body zone and materials for objects of interest. In the future, this data set may be augmented with additional images from future data collections. The end state for this development is an operationally functioning algorithm that is able to:
- Integrate with provided open file formats to add material characterization capabilities to existing Automatic Threat Recognition (ATR) algorithms;
- Demonstrate performance improvements (namely false alarm rate reduction while maintaining probability of detection) over current ATR algorithms;
- Run in near-real time, almost suitable for an operational environment; and
- Provide TSO-friendly output that will classify a foreign object into one of three categories (unlikely to be explosive, possible explosive threat, and undetermined).
Correlation of Luggage and Specific Passengers (CLASP) Algorithm Maturation and Deployment Task Order
ALERT has also received a DHS S&T task order contract, titled “Correlation of Luggage and Specific Passengers (CLASP) Algorithm Maturation and Deployment,” to mature algorithms developed under the ALERT CLASP Program so that the passenger-baggage tracking capability is sufficiently robust to support operational pilots and to support risk-based screening in an airport environment. DHS S&T has a variety of projects supporting the development of next-generation aviation security capabilities as a part of its Apex Screening at Speed (SaS) Program. Under the Apex SaS Program, passenger and carry-on screening requirements have necessitated adoption of a risk-based screening approach to the aviation checkpoint. In support of these risk-based screening requirements, the Apex SaS Program seeks to develop video analytics algorithms capable of associating passengers and their carry-on items as they travel through the airport checkpoint. Combined with existing TSA technologies, these algorithms will enable risk-based screening to occur on a per passenger and per item basis, improving screening efficiency and increasing overall passenger throughput. As a secondary benefit, effective video analytics will be able to identify thefts or items left behind at the checkpoint.
DHS S&T is seeking the following from the ALERT CLASP Algorithms project to further meet the needs of the Apex SaS Program:
- Algorithms capable of associating passengers and their carry-on items as they traverse the airport checkpoint that are robust to variations in lighting, passenger density, glare, camera angles, etc;
- Requirements and best practices for algorithm deployment in an operational environment (recommended hardware, configurations, etc.); and
- Algorithms capable of leveraging passenger/bag association information to identify actions at the checkpoint (such as interaction with scanning equipment, item theft, or items left behind).
ALERT Researchers Awarded Best Paper at 2018 ICDSC Conference September 27, 2018
September 27, 2018
Dr. Octavia Camps (Project R4-A.1; Northeastern University), Dr. Richard Radke (Project R4-A.3; Rensselaer Polytechnic Institute), and their research team received the Best Paper Award at the 2018 International Conference on Distributed Smart Cameras (ICDSC) in Eindhoven, Netherlands on September 3-4, 2018.
The paper, titled “Correlating Belongings with Passengers in a Simulated Airport Security Checkpoint,” is co-authored by Ashraful Islam, Yuexi Zhang, Dong Yin, Octavia Camps and Richard Radke. The research for this paper was done using data collected for CLASP (Correlating Luggage and Specific Passengers) project at ALERT’s Video Analytics Lab located at the Kostas Research Institute for Homeland Security at Northeastern University.
According to the paper’s abstract, “Automatic algorithms for tracking and associating passengers and their divested objects at an airport security screening checkpoint would have great potential for improving checkpoint efficiency, including flow analysis, theft detection, line-of-sight maintenance, and risk-based screening. In this paper, we present algorithms for these tracking and association problems and demonstrate their effectiveness in a full-scale physical simulation of an airport security screening checkpoint. Our algorithms leverage both hand-crafted and deep-learning-based approaches for passenger and bin tracking, and are able to accurately track and associate objects through a ceiling-mounted multi-camera array. We validate our algorithm on ground-truthed datasets collected at the simulated checkpoint that reflect natural passenger behavior, achieving high rates of passenger/object/transfer event detection while maintaining low false alarm and mismatch rates.”
Click here to read the paper and learn more about this research.
2018 DHS COE Summit Facilitates Collaboration and Advances DHS Mission July 31, 2018
ALERT, along with other current and emeritus DHS Centers of Excellence (COEs), hosted the 2018 Centers of Excellence Summit in Arlington, Virginia on May 30-31, 2018. The event focused on the topic of “University Research and Development to Protect the Homeland.” The DHS COE Summit provided the Centers of Excellence an opportunity to showcase their innovative solutions to homeland security challenges and facilitate collaboration across homeland security enterprise leadership and component end-users and industry participants. According to ALERT Center Director, Michael B. Silevitch,
“One of the most valuable aspects of the Summit was the teamwork needed to pull it together. It required a concerted effort by all of the COEs to organize and orchestrate the event. Going forward, this teamwork will lead to meaningful cross-center collaboration.”
The agenda for the two-day long summit was launched with a keynote address from Christopher C. Krebs, Senior Official Performing the Duties of Under Secretary, National Protection and Programs Directorate (NPPD) and included talks by various security administrators, panel discussions, student posters, and a technology showcase.
Director Silevitch moderated a panel focused on “Transportation and Critical Infrastructure” on the first day of the summit. Panelists Carl Crawford, Eva Lee, David Nicol, and Detlof VonWinterfeldt addressed four questions related to this topic:
- What are some of the grand challenges that need to be addressed to enable the next generation of Homeland Security transportation and critical infrastructure solutions?
- What research needs to be done in order to address these challenges?
- How can the research outcomes be effectively transitioned to the field?
- What metrics can be used to enable a cost-benefit analysis of the research/transition impact?
ALERT’s Transition Team made connections with end users at the technology showcase and featured some of ALERT’s latest solutions in multi-view air cargo CT scanners, effective personnel screening, video tracking at the airport security checkpoint, and K9 explosives training aids.
COEs excel in advancing the state of the art thanks in large part to their student researchers. To acknowledge this, the summit provided students with the opportunity to present their work to attendees. Katherine Graham, one of ALERT’s talented undergraduate researchers, took home the Best Poster Award for her work on “Compressive Reflector Antennas for High-Sensing Capacity Imaging Applications.” These antenna designs provide a less complex and lower cost solution for high-sensing capacity millimeter wave imaging systems. Millimeter wave imaging systems have the potential for use in several near-field imaging applications such as security screening, non-destructive testing, autonomous driving, and biotechnology. The abstracts for the COE Summit student posters are available for download on the COE Summit 2018 website.
The summit provided an all-hands-on-deck approach to addressing homeland security challenges by bringing together some of the nation’s best academic, public, and private sector leaders to discuss strategies for advancing the mission of the Department of Homeland Security. ALERT looks forward to the next DHS COE Summit, and hopes you will join us there!
ALERT Research Highlight: The Largest and Most Systematic Re-id Benchmark to Date May 30, 2018
ALERT researchers Professor Octavia Camps (Northeastern University, Project R4-A.1) and Professor Rich Radke (Rensselaer Polytechnic Institute, Project R4-A.3) and their students, Srikrishna Karanam, Mengran Gou, Ziyan Wu, and Angels Rates-Borras, were recently published in the Institute of Electrical and Electronics Engineers’ (IEEE) monthly journal, Transactions on Pattern Analysis and Machine Intelligence (download here). The paper, “A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets,” provides an extensive review and performance evaluation of existing person re-identification algorithms.
Person identification, or re-id, matches observations of individuals across multiple camera views in a network of surveillance cameras, and represents a critical task in most surveillance and security applications. For example, a police officer may want to automatically follow a person of interest tagged at a check-in counter through the branching concourses of an airport. The research team’s recent review and evaluation of re-id algorithms helps characterize what re-id algorithms are currently capable of accomplishing, as well as what is missing and what is possible in the future. In this paper, the researchers discuss insights gained from their study, as well as put forth research directions and recommendations for re-id researchers that would help develop better algorithms in the future. Both Professor Camps and Professor Radke are involved with ALERT’s Research Thrust 4, which focuses on video surveillance and the analysis of video data with novel algorithms. This publication was the result of years of research and collaboration between their respective labs.
The fundamental re-id problem is to compare a person of interest as seen in a “probe” camera view to a “gallery” of candidates captured from a camera that does not overlap with the probe camera. If a true match to the probe exists in the gallery, it should have a high matching score, or rank, compared to incorrect candidates. Since the body of research in re-id is increasing, researchers can begin to draw conclusions about the best combinations of algorithmic subcomponents. In this paper, the researchers present a careful, fair, and systematic evaluation of feature extraction, metric learning, and multi-shot ranking algorithms proposed for re-id on a wide variety of benchmark datasets. Their general evaluation framework considers hundreds of combinations of (1) feature extraction and metric learning algorithms for single-shot datasets and (2) feature extraction, metric learning, and multi-shot ranking algorithms for multi-shot datasets.
The research team evaluated 276 algorithm combinations on 10 single-shot re-id datasets and 646 algorithm combinations on 7 multi-shot re-id datasets, making the proposed study the largest and most systematic re-id benchmark to date. Approaches were evaluated using 17 datasets that mimic real world settings, including the ALERT Airport Re-Identification Dataset. As part of the evaluation, the researchers built a public code library with an easy-to-use input/output code structure and uniform algorithm parameters that includes 11 contemporary feature extraction and 22 metric learning and ranking algorithms. Both the code library and the complete benchmark results are publicly available for community use.
Student Researchers Selected for ALERT Professional Development Award November 27, 2017
November 27, 2017
Three ALERT student researchers have been selected to receive the first ALERT Professional Development Award in November 2017. The winners are Qi Feng, a Ph.D. student working with Prof. Stan Sclaroff at Boston University; Ashraful Islam, a Ph.D. student working with Prof. Richard Radke at Rensselaer Polytechnic Institute; and Abubakar Siddique, a Ph.D. student working with Prof. Henry Medeiros at Marquette University.
The ALERT Professional Development Award is intended to encourage ALERT students to participate in professional development activities throughout the year and to facilitate their future participation in networking and career development opportunities. ALERT selects up to three students each year to win a $1,500 stipend that can be used towards attendance at a professional or academic conference and/or to visit and collaborate with a lab related to their ALERT research project. This year, applications were accepted August through October 2017. More information about next year’s award cycle is forthcoming.
Rappaport Delivers IEEE Distinguished Lectures in Australia and New Zealand November 27, 2017
November 27, 2017
ALERT Deputy Director and Northeastern University Electrical and Computer Engineering Distinguished Professor, Carey Rappaport, delivered three IEEE Distinguished Lectures in Australia and New Zealand earlier this month. The IEEE Antennas and Propagation Society (AP-S) selected Professor Rappaport as a Distinguished Lecturer for 2017-2019. The IEEE AP-S Distinguished Lecturer Program sends experts, the Distinguished Lecturers, to visit active IEEE AP-S Chapters around the world and give talks on topics of interest and importance to the Antennas and Propagation community. Professor Rappaport gave the following talks during his recent visit to Australia and New Zealand:
- “Electromagnetic Sensing and Treatment of Living Things: Using Microwaves to Detect and Treat Disease in Humans and Trees” (Melbourne, Australia)
- “A High Gain Toroidal Reflector Antenna for Multistatic 3D Whole Body Millimeter-Wave Imaging” (Queenstown, New Zealand)
- “Multifocal Bootlace Lens Design Concepts” (Sydney, Australia)
On the value of being an IEEE Distinguished Lecturer, Professor Rappaport states, “The IEEE Distinguished Lecturer Program supports one of the fundamental precepts of academic research: extending the dissemination of knowledge and cutting-edge discovery to as wide an audience as possible. In presenting my team’s engineering work around the world, I have been able to help engineers extend their scientific awareness beyond their traditional themes, and occasionally outside their comfort zones. Although the travel commitment is time-consuming, it has been a great opportunity to meet people and exchange technical ideas.” Professor Rappaport will be delivering another IEEE Distinguished Lecture in January 2018 to the IEEE AP-S chapter in Orlando, Florida.
Professor Rappaport has been a Northeastern University faculty member since 1987, becoming a full professor in Electrical and Computer Engineering in July 2000, and receiving an appointment as a College of Engineering Distinguished Professor in 2011. Professor Rappaport has written over 400 technical journal articles and conference papers on various topics, including electromagnetic wave propagation and scattering computation, microwave antenna design, and bioelectromagnetics. He has also received two reflector antenna patents, two biomedical device patents, and four subsurface sensing device patents.
Student Spotlight: Elizabeth Wig September 27, 2017
Congratulations to Elizabeth Wig, a Northeastern University (NU) Electrical Engineering undergraduate conducting ALERT research, for receiving the Society of Women Engineers GE Women’s Network Scholarship! Elizabeth will receive this award, which comes with a $5,000 stipend, in October 2017 at the SWE Annual Conference in Austin, Texas. Elizabeth has been working with ALERT R3 Thrust Leader, Professor Carey Rappaport since Summer 2016, conducting research on “Computational Models & Algorithms for Millimeter Wave Whole Body Scanning for AIT,” in collaboration with Smiths Detection (Project R3-A.2). When asked how Elizabeth got involved with the project so early on in her undergraduate career, she explained that she met Professor Rappaport at a NU-sponsored ski event and found out about his research while riding up the mountain on a chairlift. However, Elizabeth explained that her interest in this research began much earlier, “When my high school physics class did its electricity and magnetism unit, the symmetry was strikingly beautiful. I loved the way relatively few equations could describe so much of what makes up our world, from why sunrises are so beautiful to the way molecules hold together to Wi-Fi.” The aspect of her research that she is most passionate about is math, and learning about the different ways mathematics can be used to describe and explain our world. This fits in well with her role on the project, which involves developing the model used to detect and characterize potential explosives threats and eliminate false alarms using a millimeter-wave body scanner. She has been working to make and refine the model to improve the accuracy in characterization.
Beyond her recent award, Elizabeth has also published a paper on her work with Mahdiar Sadeghi, a Northeastern graduate student, and Professor Rappaport, and is currently working on her second paper. She and Mahdiar were also asked to present their work at the ADSA15 (Advanced Development for Security Applications) Workshop in November 2016.
Elizabeth has already gained valuable work experience through her Spring 2017 co-op position at Draper Laboratories in Cambridge, MA. There she worked on electrical engineering projects in their Sensors and Imaging Systems group. As for her future career, she hopes to continue her education and complete a Ph.D. program, and if possible, get the opportunity to travel more internationally and work with NASA!
ALERT Researcher Awards & Accomplishments September 27, 2017
September 26, 2017
Professor Bouman Nominated for ACM Gordon Bell Prize
Professor Charles Bouman of Purdue University has been nominated for an ACM (Association for Computing Machinery) Gordon Bell Prize. Professor Bouman co-leads research on the ALERT project, “Toward Advanced Baggage Screening: Reconstruction and Automatic Target Recognition (ATR)” (Project R4-B.1), with the overarching goal of finding the best mapping method from X-ray data to a decision on the relative safety of individual bags in security settings, such as airport checkpoints. Professor Bouman and his research team study the reconstruction problem with the end goal of detection, while also designing algorithms for image analysis that can best exploit the improved image quality in iterative methods. Their aim is to reduce the false alarm rate without sensitivity loss in detection. They hope to eventually reduce security costs to the transportation industry.
The Gordon Bell Prize is awarded each year to recognize outstanding achievement in high-performance computing. The purpose of the award is to track the progress over time of parallel computing, with particular emphasis on rewarding innovation in applying high-performance computing to applications in science, engineering, and large-scale data analytics. Prizes may be awarded for peak performance or special achievements in scalability and time-to-solution on important science and engineering problems.
Professor Jose Martinez-Lorenzo Awarded $546K DOE Grant
Professor Jose Martinez-Lorenzo of Northeastern University was awarded a $546K grant from the Department of Energy (DOE) for “Fusing Thermoacoustic, Electromagnetic and Acoustic/Seismic Wave Fields for Subsurface Characterization and Imaging of Flow Transport.” According to the DOE, “The overarching goal of this research program is to gain knowledge on the theory and experimental validation of a new unified sensing and imaging methodology for coupling Electromagnetic (EM), Acoustic/Seismic (AC/S), and novel Thermoacoustic (TA) physical fields, which will be applicable to multi-physics and multi-scale material characterization and underground imaging of fluid flow in porous media.” This research will help Professor Martinez-Lorenzo build upon his work with ALERT, specifically Project R3-B.1 and Project R3-B.2.
Professor Otto Gregory Awarded Patent for Gas Sensor System
Professor Otto Gregory of the University of Rhode Island was awarded a patent for “Systems and Methods for the Detection of Compounds” on September 12, 2017. Triacetone-Triperoxide (TATP) is an explosive commonly used in improvised explosive devices (IEDs) and is very difficult to detect using conventional explosives detection techniques, because most of these techniques were developed for nitrogen-based chemistries, not peroxide-based chemistries. In addition, TATP readily sublimes at room temperature, meaning that it can only be found in relatively high concentrations in the vapor phase compared to other commonly found explosives used in IEDs. Professor Gregory’s invention provides a gas sensor system for detection of a compound that decomposes upon exposure to a metal oxide catalyst, and incorporates the exposure of the compound to a microheater, which allows accurate detection to occur at smaller concentrations. For more information on Professor Gregory’s research with ALERT, see Project R2-B.1.