Summer internships at the Army Research Lab in MD

The Army Research Laboratory (ARL) is the U.S. Army’s corporate research laboratory and is headquartered at the Adelphi Laboratory Center in Adelphi, Maryland.

Summer internships at the Army Research Lab for undergraduate and graduate students

The Army Research Lab (ARL) is offering approx. 12 paid summer team intern projects for UMBC and University of Maryland students. You will work on-site at ARL in teams of 3-5 interns with a mentor for 10 weeks over the summer of 2022, tentatively from June 6 thru August 12, 2022.

Internship opportunities are offered in the six topics that are described below. ARL will create specific projects within each topic that leverage the skills and experience of the students that are selected for the topic. Multiple teams may be selected for a single topic and some topics may not be supported if there is insufficient interest from applicants.

Both undergraduate and graduate engineering and science students are encouraged to apply, including Freshman, Sophomore, Junior, Senior, Masters Candidates, and Ph.D. Candidates. Interns will be paid a fixed stipend for the 10-week internships of $9,000 for undergraduate students and $12,000 for graduate students. No additional funding for travel or lodging is available.  Interns will work on Army sites and hence are limited to U.S. citizens and will be required to comply with Army COVID-19 requirements and provide proof of COVID-19 vaccination.

APPLY via UMBCworks RIGHT AWAY, position 9336592

If you don’t have an approved resume on UMBCworks, upload one and send Christine Routzahn () an email message. She will approve it so you can apply ASAP.

Applicants should submit a one-page resume and 1-2 page cover letter that describe relevant education, projects, and work experience. Include your GPA in your resume or cover letter, a statement of your goals for the internship, and identify up to three topics that are of interest to you. ARL prefers candidates with a GPA of 3.0 or better.

Applications will be sent to the Army Research Lab every Friday. Each week selected applicants will be contacted to schedule a short virtual interview and conditional offers will be made to successful applicants on a rolling basis.  We will stop accepting applications when we reach 36 so it is to your advantage to apply early.   Applicants with conditional offers will need to successfully complete a background check prior to obtaining their final offer.


  • 2022A – Biotechnology and Synthetic Biology
  • 2022B – Ground & Air Robotics & Autonomy
  • 2022C – Image Understanding for UAVs
  • 2022D – Novel New Energy Sources
  • 2022E – Quantum Information and Sensing
  • 2022F – Co-design of Structural Materials and Components 

Topic 2022A – Biotechnology and Synthetic Biology Topic Area

Locations: Adelphi, MD and potentially fieldwork at Aberdeen Proving Ground, MD 

With the advent of synthetic biology, it becomes possible to not only harness the natural world but evolve and reprogram biological systems ushering in a new wave of biotechnological advances.  In this student research experience, teams working in the biotechnology and synthetic biology research topic area will undertake multidisciplinary research to impact a variety of Army materials, from the assembly of novel biohybrid systems and biocomposites, to material maintenance and protection, and finally, the introduction of degradative processes.  This work will require students to customize and optimize natural biological systems for material applications by developing strategies to access, understand, and tailor biological components from the environment through informatics and performance screening, genetic engineering, and bio/abio integration.  Through this work, students will learn how to apply diverse skillsets in microbiology, biomolecular, chemical, material and engineering sciences, integrated with bioinformatics, modeling, and a creative mentality toward designing and engineering biology across molecular, organismal, and biosystem levels for the advancement Army material technologies.

Skills desired:  students with bioengineering interest – chemical or biomolecular lab experience will be helpful. Potential specific research areas:

  • Genetically-programmed functional biohybrid systems: Students will gain experience in implementing bioengineering approaches to tailor both organisms and device infrastructure.
  • Bioprospecting for novel enzymes towards polymer degradation: Students will gain experience in identifying and isolating novel organisms and metabolic pathways that have naturally evolved to degrade different type of polymers from contaminated soils and water.
  • Building synergistic relationships to inhibit corrosive bacteria: Students will gain experience in identifying naturally and designer microbial communities that controls the rate of corrosion.
  • Microfluidic High-Throughput Screening (HTS) Tools for Synthetic Biology: Students will gain experience in performing high-throughput DNA transfer using droplet fluidics to engineer military-relevant microbes, and development of continuous-flow devices.
  • Bacterial Melanin for Advanced Protection:  Students will gain experience in the development of surface modification workflows, chemical characterization, analysis of effects on miscibility within polymer matrices, and testing the resulting properties of the melanized composites. 

Topic 2022B – Ground & Air Robotics & Autonomy   

Locations: Adelphi, MD and fieldwork at Middle River, MD

While state-of-the-art autonomous vehicle navigation techniques can sometimes allow autonomous vehicles to perform particular styles of navigation in particular environments, they are typically only able to do so after a time-consuming process of experimentation and manual tuning by skilled roboticists. These existing approaches may not scale to situations where environments and desirable navigation styles may not be known in advance and skilled roboticists and/or tuning time may not be available. ARL’s research aims to fill a broad set of knowledge gaps to move air and ground autonomy towards more robust, less brittle, autonomy.

Skills desired:  students with interest and some experience in autonomous ground and air systems. Potential specific research areas:

  • Conduct experiments on state-of-the-art, off-road autonomy algorithms; 2) implement and test software components in the ARL Ground Autonomy Software Stack; and 3) design, integrate, and test novel hardware solutions on ARL’s experimental, wheeled robots.
  • Perform target recognition onboard a UAV while simultaneously tracking and determining the geospatial coordinates of objects of interest during the course of a flight.
  • Explore information gathering problem variants where one or more mobile object (or objects) move(s) around the environment, while one or more quad-rotor agents attempt to gather information about the moving object.
  • Develop efficient semantic representations of LiDAR point cloud data for use in distributed multi-agent Simultaneous Localization and Mapping (SLAM) 

Topic 2022C – Image Understanding for UAVs 

Locations: Adelphi, MD and fieldwork at Middle River, MD

The Army has a strong interest in unmanned aerial vehicles (UAVs) for a variety of applications.  This project seeks to help develop several areas important to UAV performance: 1) artificial intelligence and machine learning (AI/ML) capabilities for scene perception from unmanned aerial vehicles (UAVs); 2) image understanding algorithms to enable vehicles to gather information about moving objects that its sensors can see; and 3) perform object recognition onboard a UAV while simultaneously tracking and determining the geospatial coordinates of the objects of interest during the course of a flight.  Student team members will be expected to participate in data collections and field experiments at outdoor locations, help develop vision-based algorithms for object detection and activity recognition leveraging both real data and synthetic data/simulators, and perform implementation of algorithms on embedded computing devices such as the Qualcomm Snapdragon for integration onboard UAVs.  Students will begin by implementing classical techniques to serve as gold standards and will transition to new novel techniques.  

Specific project outcomes for students would include:  1) integration of custom-trained object detection classifiers on-board small UAVs;  2) given the ability to detect objects, algorithms to inform how the vehicle should maneuver to better gather information on objects that may be moving in the scene.;  3) detection, tracking, and localization of objects.

Skills desired:  students with interest and some experience in autonomous ground and air system imaging sensing; interest in sensing for robots. Potential specific research areas:

  • Conduct data collections and field experiments to validate algorithms
  • Develop vision based algorithms for object detection and activity recognition leveraging both real data and synthetic data/simulators
  • Implement algorithms on embedded computing devices such as the Qualcomm Snapdragon for integration onboard UAVs
  • Utilize sensors onboard the UAV (cameras, GPS, IMU, laser range finder, etc.) and a 3D terrain map to train the UAV to compute and report the uncertainty associated with object identification and tracking

Topic 2022D – Novel New Energy Sources   

Locations:  Adelphi, MD

The Army is motivated to provide high-performance, portable power sources for its Soldiers.  Such sources will also have significant impact for a variety of commercial applications.  Specific Army applications require the development of electrochemical energy technologies that are not available commercially to enable long-lived, low power sources.  To that end, ARL has several projects involving research in electrolyte, electrode, and semiconductor materials that provide an opportunity for students to solve problems connected with cutting-edge energy source research.  

Students will gain practical laboratory experience by designing/running/validating experiments and will develop hands-on working knowledge of laboratory instrumentation.  Instrumentation will include particle accelerators, EBIC, XPS, SEM, XRD, EDS, and device fabrication and packaging methods,

Skills desired:  students with an interest or some experience in chemistry, physics, electrochemistry, material science & engineering, chemical engineering, or power sources. Potential specific research areas:

  • Energy Conversion of Radioisotope Materials - investigate radiation tolerance of ultra-wide bandgap (UWBG) semiconductor materials to increase the power density of Betavoltaic power sources
  • Low Operation Temperature Solid Oxide Fuel Cell – investigate materials that enable low-operation temperature solid oxide fuel cells with high power density
  • Aqueous and Non-aqueous Electrolytes – students will design a test cell and perform initial experiments on ARL’s new Hiden Analytical online electrochemical mass spectrometer (OEMS)

TOPIC 2022E – Quantum Information and Sensing

Locations: Adelphi, MD, and the University of Maryland at College Park

Because of the extreme potential sensitivity of quantum sensors, they could enable the detection of electromagnetic emissions, underground structures or other emissions from concealed sources that might be currently undetectable. While quantum technologies are still nascent, ARL and the University of Maryland are actively collaborating to create the basis for future sensing capabilities.  ARL has opportunities at varying levels of expertise.  All efforts are done in conjunction with the Quantum Technology Center at UMD.  The nature of these projects lends itself better to individual student efforts in collaboration with ARL scientists and engineers and UMD faculty rather than teams of students.  That said, the students working in the same locations would be expected to share their experiences, discuss challenges they encounter, and potential solutions for those challenges.

Skills desired:  Graduate students pursuing Masters or Ph.D. in Quantum Information Science. Undergraduate student – Junior or Senior in physics, CS, EE, or ME. Students with fluency in Python (at the level of ); git; track record of writing software for fun.  Experience with low-level hardware interfaces like Arduino (“bit-banging” in C, rust); VHDL/Verilog; soldering.  Experience with lasers and optics is highly desirable.  Proficiency/programming with analysis software (e.g. Matlab).  Potential specific research areas:

  • Experimental Control – assist with writing quantum control algorithms for quantum science experiments and drivers for laboratory instrumentation (lasers, microwave generators, etc.).
  • Optical nanofiber fabrication – experiments in optical propagation, optomechanics, and quantum optics for these 1D systems.
  • Quantum Random Number Generation (QRNG) – student will learn about and provide a review of existing applications of QRNG and SI-QRNG in classical cryptography and discuss the security improvements available to existing classical networks through the introduction of QRNG and SI-QRNG.  Student will quantify how QRNG and SI-QRNG impact the security of future quantum networks both point-to-point QKD networks and entanglement-based networks.  
  • Solid-state defect characterization – Defect quantification and qualification by photoluminescence (PL) and other magnetic/optical measurements in silicon carbide for quantum technology applications.  Student will work with tunable lasers, cryogenic cooling, and optical systems to collect spectroscopic data on silicon carbide and nitrogen vacancy centers at ARL or at UMD-College Park. 
  • ARTIQ Quantum Control Operating System – Contribute to the development of the ARTIQ quantum operating system, an open source infrastructure for quantum control. A student with strong physics and computer science skills is needed to assist with writing quantum control algorithms for trapped ion qubits and drivers for laboratory instrumentation (lasers, microwave generators, etc.). Skills: undergrad student
  • Instrumentation development for quantum experiments:  Contribute to the development of infrastructure to prototype quantum repeaters based on trapped atomic ions. Our approach includes instrumentation operating at cryogenic temperatures through the design and testing of superconducting resonators, ultra-high vacuum instrumentation, and optical resonators.  Skills: undergrad student

Topic 2022F – Co-design of Structural Materials and Components

Location: Aberdeen Proving Ground, MD

This project aims to build a holistic parts performance model starting with materials, building to the full interdependent part. Project components will encompass modeling of quantitative property relationships utilizing state-of-the-art machine-learning (ML) technologies and tools. ML models will be used to extract cross-property and inverse functions for system-level design. Subtasks may involve computer vision methods, scalar models, graph neural networks, data wrangling, and/or data visualization. Depending on prior experience, students will learn data management workflows to apply pre-trained models (load & clean & fuse data, convolutional neural networks (CNNs) to image data, kernel models to scalar data sets), train models (in particular CNNs on image data, support vector and Gaussian process regressions to scalar data), or model development (NN composition from layer types, graph representations of data for graph neural networks and their layer by layer composition).  

Skills desired:  students with interest in materials modeling, some machine learning and neural networks classes. Potential specific research areas:

  • Microstructure analysis for materials property prediction
  • Geometry design for additive manufacturing of structural parts
  • Mechanical property prediction for materials from unit cell and bonding information
  • Hardness prediction from composition

UMBC Computer Engineering major Joshua Slaughter receives Marshall Scholarship

photo of Joshua Slaughter with mentor Chuck LaBerge
Joshua Slaughter with his Computer Engineering mentor Prof. Chuck LaBerge

Computer Engineering major Joshua Slaughter ‘22, M30, has received the Marshall Scholarship, becoming the second student in UMBC history and the first in 29 years to be selected for the prestigious award. Slaughter is one of 41 American students chosen this year from institutions across the country for the Marshall Scholarship, which supports graduate study at institutions in the United Kingdom. He was also a finalist for the Rhodes Scholarship.

Slaughter, who is earning his degree in computer engineering, will pursue his Ph.D. in informatics at the University of Edinburgh. His goal is to advance equity in the developing field of personalized medicine.

Read more about his accomplishments and plans and his support from mentors and UMBC programs in this UMBC News article.

Learn about AI in the free 10-week Discover AI program this Spring

AI4ALL Opens Doors to Artificial Intelligence for Historically Excluded Talent Through Education and Mentorship

Ten-week online Discover AI program
apply by February 11

Are you interested in learning about artificial intelligence and how it intersects with a variety of fields? Do you want to learn about career paths in AI and technology? Apply for the free Discover AI program, co-sponsored by UMBC and AI4ALL!


  • Discover AI is a no-cost virtual program in partnership with UMBC that offers a hands-on introduction to computer science and artificial intelligence (AI), ethical issues surrounding AI implementation, and tech careers. There is no cost to participate.
  • Students who complete the program will emerge with actionable next steps in pursuing an academic or career path in AI; the opportunity to continue in the following semester to our second program, Apply AI; and direct mentorship from industry leaders in the AI and tech industry from companies like  Google, Capital One, Facebook, Slalom Consulting, Accenture, Pearson; and more.
  • At the end of the Discover AI program, participants receive an AI4ALL Discover AI certificate of completion.


  • Begins in the week of 7 March 2022 and ends in the week of 9 May 2022.
  • Weekly synchronous online lectures/discussion on Fridays 11:30 am – 1:00 pm, weekly and addional asynchronous lectures


  • AI4ALL programs are designed to bring together and highlight voices that have been historically excluded and that will lead and shape the future of AI.  
  • Undergraduate students who are Freshman, Sophomores, or Juniors
  • All coding and/or Computer Science/AI levels (including everything from no experience to advanced)



Interested in AI? Join free Discover AI program this Fall, apply by Fri 9/3

AI4ALL Opens Doors to Artificial Intelligence for Historically Excluded Talent Through Education and Mentorship

Discover AI through the free AI4ALL eight week online class this Fall

Are you interested in learning about artificial intelligence and how it intersects with a variety of fields?  Want to learn about career paths in technology? UMBC has partnered with AI4ALL to offer its free online class introducing AI technology to selected UMBC undergraduate students from any major.

Apply online for the free Discover AI program, co-sponsored by UMBC and AI4ALL

Discover AI is a virtual program that offers a hands-on introduction to computer science and artificial intelligence, ethical issues surrounding AI implementation, and tech careers. It is intended for college students not already on an AI academic path to introduce them to the field, get them excited about AI, and encourage them to take the next step in their academic path in AI. Students will complete the program with a Discover AI Certificate of Completion and ideas for the next steps to take to pursue an academic or career path related to AI in their chosen major.

Discover AI is the first of a series of online education programs focused on AI. It will take place over eight weeks, starting in the week of September 21, and includes both synchronous and asynchronous instruction. The program involves a total commitment of 15-20 hours during the Fall semester. The Discover AI program is open to all Freshmen, Sophomores, and Juniors and is designed to accommodate both students with and without prior computer science or AI experience.

AI4ALL programs are designed to bring together and highlight voices that have been historically excluded and that will lead and shape the future of AI. The programs aim to serve the following students, especially those at the intersection of two or more of these identities:

  • Indigenous Peoples, Black, Hispanic or Latinx, Pacific Islander, and Southeast Asian 
  • Trans and non-binary; two-spirit; cis women and girls
  • Lesbian, gay, bisexual, asexual, and queer
  • Students with a demonstrated financial need (for example, students who receive financial aid)
  • First-generation college student 

All students who apply will be considered subject to space availability.

Interested students can Apply using this Google form by Friday, September 3, 2021.

If you have questions, you can attend a Discover AI Program Infomation Sessions for Students, send email to and visit the AI4ALL website.

UMBC’s 25th Undergraduate Research & Creative Achievement Day had a global audience

A scene from the game Recurring Moment by Kristian Mischke. Image courtesy of Mischke.

UMBC’s 25th Undergraduate Research and Creative Achievement Day had an expanded global audience

UMBC’s 25th Undergraduate Research and Creative Achievement Day (URCAD) reached more viewers than ever before, with visitors connecting online from as far away as Spain, Indonesia, Nigeria, Brazil, Bhutan, Germany, and the U.K.. Audiences logged more than 11,000 visits (compared with 8,000 in 2020) and posted more than 3,500 comments over the course of the week-long event. 

For UMBC’s video game designers, going virtual was not new. Marc Olano, associate professor of computer science and electrical engineering, mentored four projects presented at URCAD, each led by a group of about four students. They include Sword Shibe; Recurring Moment – A Time Travel Puzzle Platformer; Jump Starters, and the two-player Android and PC strategy game Hamster Toaster Checker. Students in UMBC’s computer science game development track collaborated with students in animation and interactive media to envision and begin developing the new games.

“The beauty of the CMSC 493 class is that it brings artists and programmers together and the management of the project is completely led by us,” says Kristian Mischke ‘21, computer science, the game designer for the Recurring Moment project.

In Sword Shibe, players take a dog with a sword through different paths. The student team that created it drew inspiration for its concept designs from Japanese culture, folklore, and legends. The dog in the game is also inspired by a Shiba Inu, which is a breed of hunting dog from Japan. 

Olano worked to model the students’ project experience on the structure of the game design and development industry. “Students began working through ideas in small teams and worked their way through prototypes and onto a bigger team,” he explains. “In the game industry, you have to work collaboratively or you fail.” 

Mischke explains how he would bounce ideas off the artists for visual appeal or about the game’s narrative arc. With the other programmers, he talked through implementation feasibility. “We all would give feedback and discuss adaptations together,” says Mischke. “Everyone on the team was able to be part of the process and apply their unique skill set.”

This post was adapted from a UMBC News article written by Catalina Sofia Dansberger Duque.

UMBC’s Grand Challenge Scholars Program, apply by May 3

UMBC’s Grand Challenge Scholars Program, apply by May 3

virtual informational session 5:00 pm, Wednesday, April 28

UMBC’s Grand Challenge Scholars Program is designed for students from all majors who are interested in solving important societal problems. The program fosters a vibrant interdisciplinary community to help tackle the National Academy of Engineering’s (NAE) Grand Challenges and gives students experiences and skills to create solutions to some of the most pressing challenges of the 21st century.

The Grand Challenges are 14 broad problems in the areas of sustainability, health, security, and knowledge. Solutions to these issues require interdisciplinary teamwork and years of sustained effort.

The program aims to recruit a cohort of 20 undergraduates from a diverse pool of disciplines for Fall semester 2021. Ideal candidates are students starting their junior year in order to complete the requirements of the program during their last two years at UMBC. Although there is no financial support provided, the students will have the opportunity to incorporate five experiences into their undergraduate studies that will give them valuable interdisciplinary experiences they can bring to the workplace or graduate school, as well as recognition from the National Academy of Engineering upon successful completion of the program.

Read more about the program and find out how to join at the UMBC GCSP site and via a virtual informational session at 5:00 pm on Wednesday, April 28.

Unique research experiences open doors for UMBC’s Class of 2020

Danilo Symonette, right, with his friends at a restaurant. Photo courtesy of Symonette.

Unique research experiences open doors for UMBC’s Class of 2020

Danilo Symonette, Robin Bailey, and Hye-Jin Park are earning their UMBC degrees this month having researched in top labs and being invited to present their findings to colleagues across the country. They sound like phenomenal Ph.D. students, but they’re actually all undergraduates.

Symonette ‘20, computer science, has earned one of the most prestigious graduate fellowships in the U.S. after completing years of research in artificial intelligence. Bailey ‘20, biological sciences, conducted research at Harvard Medical School’s Joslin Diabetes Center. Hye-Jin Park ‘20, psychology, researched the experiences of Asian immigrants in the United States, including discrimination and resilience. 

Their interests vary greatly, but each celebrates the impact that UMBC mentors have had on their college careers, including the chance to access incredible opportunities.

Finding a community

When Symonette transferred to UMBC from the College of Southern Maryland in La Plata, Maryland, he knew he wanted to study computer science and conduct research on artificial intelligence, which he sees as a “revolutionary” field. He quickly found a supportive community of friends and mentors at UMBC, and became a McNair Scholar. 

UMBC’s McNair Scholars program is a Federal TRIO program that supports students from disadvantaged and underrepresented groups in preparing for graduate education. The program emphasizes intensive research experiences and mentoring. Symonette’s McNair mentors helped him define and achieve his goals and navigate challenges along the way.

Danilo Symonette, left, and two of his friends at UMBC. Photo courtesy of Symonette.

“Being a McNair Scholar has entirely shaped my experience at UMBC and given me the community I needed to support my ambitions and pursue opportunities,” says Symonette. The program also introduced him to some of his favorite people at UMBC.

The value of mentorship

Don Engel, assistant vice president for research, is Symonette’s advisor on the award that supports his artificial intelligence work. He has been one of his most impactful mentors over the years. “Don Engel gave me the freedom to explore any and all of my ideas,” says Symonette. “He advised me on career decisions, wrote countless letters of recommendation, and always supported and believed in me no matter how lofty my goals seemed.” 

Engel connected Symonette with the neuro-AI lab at the Johns Hopkins Applied Physics Lab, where Symonette is currently interning. Symonette accepted a full-time job offer to work at APL starting in June. This allowed him to explore his interests at the intersection of computer science, neuroscience, and psychology, and further refine his graduate school career goals. 

“Danilo is one of the most talented and motivated students with whom I’ve had the pleasure to work. He has been a wonderful teammate to a broad range of student, faculty, and external research collaborators,” shares Engel. “I’m looking forward to following Danilo’s career, which I’m sure will be exciting and impactful.”

Symonette has also found mentors outside his discipline who have helped him develop a well-rounded perspective. They include Simon Stacey, director of the Honors College; former UMBC professor Marie DesJardins, now a dean at Simmons College; and Christy Ford Chapin, associate professor of history. Symonette says that Chapin helped him elevate his grad school essays and fellowship applications “to the highest level they could be.”

Exploring opportunities beyond UMBC

In addition to connecting Symonette with mentors, the McNair Scholars program also provided him with travel funding to visit several graduate schools across the country. 

In 2018, he completed the Louis Stokes Alliances for Minority Participation (LSAMP) summer research program and focused on machine learning. The following year, he attended the NSF Graduate Research Fellowship Program at the Institute on Teaching and Mentoring, which was sponsored by the Southern Regional Education Board. “I saw a slew of Ph.D. students from underrepresented backgrounds come on stage and encourage me to pursue graduate education,” Symonette shares.

In 2019, he headed to MIT and studied models that detect confusion in features that rely on voice. His work was used as a foundation to develop sensors for a teacher education platform, to make it more effective. 

“That experience equipped me with the inspiration, motivation, and knowledge to plan my next steps,” he says. Over the next 18 months, Symonette explains, “I was accepted to the top computer science Ph.D. programs in the world and won the NSF Graduate Research Fellowship.” 

Today, he describes the LSAMP and McNair programs as “the vehicles through which I arrived at many of the pivotal moments in my journey.”

Inspiring younger students

While focusing on his courses and research at UMBC, Symonette also enjoyed gaining early experience as an educator. He served as a teaching assistant for Computer Science 202, inspired by his own earlier challenges with the course. 

“I struggled a lot in CS202 when I came from community college,” Symonette recalls. “Seeing all the errors and mistakes troubling students during office hours and being able to help them through those same situations…was extremely rewarding.” 

Symonette also found ways to connect with younger students, to encourage them to pursue degrees and careers in computing. He served as the head of outreach for UMBC’s Computer Science Education Club, establishing strong partnerships with local high schools.

“I wanted to expand our outreach efforts so that more people could volunteer,” he says. He connected with Lori Hardesty, associate director for applied learning and community engagement at UMBC’s Shriver Center, to ensure the program would have the structure to be successful in the long term. 

“We managed to get a consistent group of students volunteering at Landsdowne High School last semester and supporting the high school’s computer science and robotics club,” says Symonette. “It’s been great to connect with high school students, especially at a school like Landsdowne. There are students from similar backgrounds as me that I have a chance to inspire. It continues to motivate me to do research in AI and education.” 

After working at APL for a year, Symonette will begin a Ph.D. program in computer science at Stanford University in fall 2021, with the goal of becoming a professor. “I’m looking forward to broadening my perspective, accessing opportunities, and developing as a researcher and educator—everything that comes with studying in a top-tier Ph.D. program,” he says. “I can’t wait to bring all of that back to my community.” 

You can read more about Robin Bailey and Hye-Jin Park in the UMBC News article from which this was excerpted. Adapted from a UMBC News article written by Megan Hanks.

JHU/APL CIRCUIT internship program information session, 3pm Fri 1/31

JHU/APL CIRCUIT internship program information session

3:00-4:00 pm Friday, 31 January 2020


There will be a special information session on the JHU/APL CIRCUIT internship program from 3:00 pm to 4:30 pm on Friday, 31 January 2020 in room ITE 459.

This session is for undergraduates who want to spend their summer (June through August) getting paid to do mentored research at the Johns Hopkins University Applied Physics Lab. The research areas include AI, data science, cybersecurity, precision medicine, and planetary exploration.

Interns selected for the program will do mission-oriented research on-site at JHU/APL in Laurel MD mentored by STEM professionals. There will also be year-round opportunities for engagement and enrichment. The selection for an internship will be based on a combination of potential, need and commitment.

Email or with questions.

UMBC Cyberdawgs win first place in the 2019 DOE CyberForce Competition

UMBC’s CyberDawgs win first place in the 2019 DOE Cyberforce Competition

Cyberdawgs place first out of 105 teams in DOE’s 5th CyberForce Competition

Congratulations to the UMBC CyberDawgs team for their first place finish in a field of 105 collegiate teams in the U.S. Department of Energy’s Fifth Annual CyberForce Competition. The distributed event was held at ten of the DOE’s National Laboratories and challenged 105 teams to defend a simulated energy infrastructure from cyber-attacks.

The took place on November 15 and 16 with the goal of bolstering the U.S. cybersecurity workforce by extending skill-building opportunities for students, offering memorable hands-on experiences and highlighting the crucial role this field plays in preserving national energy security. The Cyberdawgs participated at the Argonne National Laboratory site in Illinois.

During the competition, teams competed to defend their simulated infrastructure from attacks by adversarial ​“red teams” composed of industry professionals, all while maintaining service for their ​“green team” customers, played by volunteers. The scenarios included simulated industrial control system components, real-world anomalies and constraints, and interaction with users of the systems.

Teams were scored on their success in protecting the infrastructure against attacks while ensuring the usability of the system, with additional points awarded for innovative ideas and defenses.

The team that competed in this year’s competition was chosen from members of the CyberDawgs student group, composed of students from a variety of majors who share a common interest in computer and network security. No prior experience is required to join and any UMBC students who want to learn more about cybersecurity and learn new skills in the field are encouraged to subscribe to its mailing list and attend meetings.

The CyberDawgs group is advised by CSEE faculty Charles Nicholas and Richard Forno.

National Science Foundation Graduate Research Fellowship Program Workshop

On October 3, 2019, Dr. Francis Ferraro presented a workshop for the National Science Foundation Graduate Research Fellowship Program (NSF GRFP).  During the workshop, Dr. Ferraro covered many topics including scholarship eligibility, funding, and the application process. He also provided a detailed application checklist as well as suggestions for developing personal and research statements. In addition to giving information about the NSF GRFP, Dr. Ferraro provided an overview of the graduate school experience.

Application deadline for the NSF GRFP is October 22, 2019.

The purpose of the NSF Graduate Research Fellowship Program (GRFP) is to help ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing full-time research-based master’s and doctoral degrees in science, technology, engineering, and mathematics (STEM) or in STEM education. The GRFP provides three years of support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM or STEM education. NSF especially encourages women, members of underrepresented minority groups, persons with disabilities, veterans, and undergraduate seniors to apply.

  • Three years of funding to use across five years (in 12 month blocks). Stipend: $34,000 per year. Tuition/education expenses: $12,000 per year.
  • Applicants must be US citizens, national or permanent residents. Applicants must be an undergraduate senior, or first or second year graduate student.
  • Registration information can be found here:
  • All registration materials should be submitted here:
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