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 Science Students Learn About Quantum Algorithms

Graduate students in CMSC-641 Algorithms actively engage to learn quantum algorithms in a new two-week unit created by Professor Alan T. Sherman and his team.  The new ILSB 116B classroom nicely supports the team’s hands-on approach.

UMBC Computer Science Students Learn About Quantum Algorithms

UMBC computer science graduate students now gain an introduction to quantum algorithms in the required core course CMSC-641 Design and Analysis of Algorithms.  Professor Alan T. Sherman and his colleagues–including Professors Sam Lomonaco (computer science) and Linda Oliva (education)—are piloting a two-week unit on quantum algorithms.  With support from a Hrabowski Innovation Fund award, the team created six modules, each comprising a video, hands-on activities, and readings.  Using the flipped classroom, students watch the videos before coming to class prepared to engage actively in programming the QUIRK quantum circuit simulator and the IBM Q quantum computer using the Qiskit software development kit.

Quantum algorithms running on quantum computers offer the potential to solve complex problems with dramatically reduced execution time and energy consumption. For example, Shor’s quantum algorithm for factoring integers runs in polynomial time, faster than any known algorithm for classical computers. Shor’s algorithm offers the future potential to break the widely-used RSA cryptosystem. Whereas classical computers use discrete 1’s and 0’s to perform calculations, quantum computers use Q-bits, which involve complex numbers and can simultaneously be 0 or 1.

Based on quantum physics, quantum computers operate in a strange universe that includes the curious and potentially useful effects of superposition and entanglement. In pursuit of transformative potential advantages, government and private industry are investing significantly in quantum computer technologies.  All computer science students need to know about these vital emerging technologies.

Whereas there exist full courses in quantum computation or quantum algorithms, Sherman’s innovation is to develop a two-week unit focused sharply on quantum algorithms targeted at computer science graduate students.  The unit highlights three quantum algorithms: Deutsch-Jozsa, Simon, and Shor. To keep the unit manageable within 15 hours of work per week per student, the unit focuses sharply on background sufficient to understand the fundamentals of these three algorithms.

Additional members of the team include graduate students Marc Laczin and Siddharth Chandrasekaran, and Dr. Omar Shehab (IBM), a former Ph.D. student of Dr. Lomonaco.

UMBC grad students present new ideas at GEARS Ideathon: 9 April 2021


11:30-1:30 Friday, April 9, 2021

GEARS, UMBC’s Graduate Experience, Achievements, and Research Symposium, bring you its first-of-a-kind event IDEATHON that invites graduate students to describe how new or existing problems can be better tackled by using their new idea. Participants will present their ideas to the jury and fellow graduate students in UMBC.  You can participate either individually or in a group of up to three people.

This event will highlight your creative skills and the uniqueness of your idea, which can be social, environmental, IT technology, medical field related, etc. These ideas can be real or hypothetical. You create a three-minute presentation showcasing your idea and how unique it is. Up to $1000 in prize money will be available for the winning ideas. All the participants are eligible for a free UMBC logo Mask, and the first ten participants will get a chance to win UMBC merchandise T-shirts.

Sign up here.

We welcome all department’s graduate students to come to participate and celebrate Graduate week with us on the event day i.e.  9th April 2021. For any queries contact Sulabh Sharma (+14438504311, ) or Jhansi Sankaramaddi (+14109006743, )

CSEE alum Balaji Vishwanathan’s robotics company featured in Forbes

Balaji Vishwanathan, CEO of Invento Robotics, with Mitra, its flagship robot. Image: Hemant Mishra for Forbes India

Balaji Vishwanathan (MS ’07) startup company Invento Robotics is featured in Forbes India magazine

Balaji Viswanathan started his career at Microsoft, and moved from there to develop startups in such diverse areas as robotics, education, and finance. He has embraced the true calling of an entrepreneur, using long term goals to develop companies that actively seek to make a global impact. This is exemplified by his Bengaluru-based company, Invento Robotics, which is currently using its humanoid robots to provide a myriad of services, from taking temperatures to collecting patient information to bringing medications and food to patients in isolation wards, in an effort to fight COVID-19.

His business was featured in Forbes India magazine as part of a series on companies that have pivoted to use technology to address the Covid-19 pandemic. The article discusses how  Invento has applied its first mobile robot models, Mitra, to perform tasks like collecting patient details, checking temperatures, and setting up video calls with doctors. Two new models, C-Astra and Robodoc have now been deployed to disinfect rooms and virtually interact with patients inside Covid-19 wards.

Balaji has recently returned to UMBC as a part-time Ph.D. student in the Computer Science program and will work on research topics that will advance the state of the art in supporting intelligent robotics.

UMBC seeks Professor of the Practice, Graduate Program Director, Engineering Programs

Professor of the Practice and Graduate Program Director,
Engineering Programs

Apply online at

Location  Baltimore, MD, Open Date Dec 2, 2019

The College of Engineering and Information Technology (COEIT) of the University of Maryland Baltimore County (UMBC) invites applications for a 12-month, Full Time, Non-tenure track Professor of the Practice position in the Engineering and Computing Education Program (ECEP).

RESPONSIBILITIES: Reporting to the Dean of COEIT, this position serves as the Graduate Program Director of UMBC’s suite of industry-oriented engineering programs leading to a graduate certificate, and Master of Science degree, and Masters of Professional Studies degree. The suite of engineering programs include Systems Engineering, Engineering Management, Technical Management, Integrated Product Development & Manufacturing and Project Management. These programs are offered to professional students through a partnership between the College of Engineering and Information Technology and UMBC’s Division of Professional Studies (DPS). The incumbent will teach up to two courses per semester within the suite of engineering programs. In addition to teaching, the incumbent will: oversee curriculum and instruction; recruit and supervise qualified part-time faculty; collaborate with DPS on program marketing, student recruitment and retention activities; pursue business development opportunities with industry; manage program Advisory Boards; build the programs and connect the programs with other existing and new opportunities,  and carry out the administrative duties associated with academic program oversight.

UMBC is a dynamic public research university integrating teaching, research and service. Located between Baltimore and Washington D.C., it offers numerous opportunities for collaboration in teaching, research and service as well as rich cultural resources. UMBC has been listed by the U.S. News and World Report as one of the best universities for undergraduate teaching and as a leading innovator in higher education, and it was named as a Great College to Work For by The Chronicle of Higher Education.

The College of Engineering and Information Technology (COEIT) is comprised of four departments: Chemical, Biochemical & Environmental Engineering, Computer Science and Electrical Engineering, Information Systems, and Mechanical Engineering. The faculty and staff of COEIT achieve many noteworthy accomplishments in the pursuit of academic excellence and are highly committed to supporting students in their academic journey. 

Inclusive excellence is a foundational value of our community. UMBC is an Affirmative Action / Equal Opportunity Employer and has a strong commitment to increasing faculty diversity. We seek to attract a diverse pool of candidates for this position and therefore members of under-represented groups including women, minorities, veterans, and individuals with disabilities are especially encouraged to apply.


Education/Experience:  Requires a doctorate degree in a relevant field with at least five years of relevant professional experience and documented college-level teaching in the classroom and/or on-line environment. Extensive experience as an engineering professional is desired.

Application Instructions

APPLICATION:  For best consideration, submit a cover letter of interest, CV, a statement of purpose including a paragraph on commitment to diversity and inclusion, and the names and telephone numbers of three professional references through the Interfolio website at Document review and selection of candidates will start immediately. Position will remain open until filled.

For any questions about this position, please contact Maria Sanchez at 

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:
  • Post-Bac Certificate in Digital Forensics

    Post-Baccalaureate Certificate in Professional Studies: Digital Forensics

    UMBC’s cybersecurity graduate program has added a new 12-credit post-baccalaureate certificate in professional studies focused on digital forensics.

    The Digital Forensics certificate program is intended for early and mid-career IT and law- enforcement professionals who want to learn basic and advanced concepts and develop skills in the field of computer forensics. Students will understand the role of digital/computer forensics as a subspecialty of cybersecurity. Through firsthand experience using industry-standard forensic tools, techniques, and procedures in the digital forensic process, students will understand the incident-handling process, the special rules of evidence that apply to cybercrime investigations (i.e., chain of custody, search and seizure, forensic imaging), and the relevant state, federal, and/or regulatory frameworks governing such activities within different industry sectors (such as defense, healthcare, and financial services). The four-course, 12-credit certificate can be applied toward obtaining the MPS in Cybersecurity degree.

    • CYBR 620 Intro to Cybersecurity or CMSC equivalent (i.e., CMSC 626, CMSC 687)
    • CYBR 641 Computer Crime Investigations
    • CYBR 642 Introduction to Digital Forensics
    • CYBR 643 Advanced Digital Forensics

    UMBC CSEE student and alumna selected to attend Heidelberg Laureate Forum

    talk: A Practitioner’s Introduction to Deep Learning, 1pm Fri 11/17

    Open House: UMBC Graduate Cybersecurity and Data Science Programs, 6-7:30 Wed. 10/25

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