UMBC faculty Karimi and Yus help team win 2nd place in Sandpit Challenge on Digital Trust

A research team that includes UMBC CSEE faculty Naghmeh Karimi and Roberto Yus won the second place prize in the 2022 INCS-CoE Sandpit Challenge on Digital Trust. The International Cyber Security Center of Excellence (INCS-CoE) is an international collaboration of government, industry, and academic organizations that have partnered to explore pioneering efforts to address cybersecurity challenges created by a growing borderless digital society.  UMBC is a charter member of INCS-CoE.

The INCS-COE Sandpit Challenge invited self-assembled teams to compete for seed research funding prizes to pursue their work further. The UMBC faculty teamed up with researchers from Royal Holloway (UK) and Keio University (Japan). They were awarded second prize for their proposal to deal with challenges associated with developing an International Digital Trust Framework. In particular, their project proposal focused on designing an ontology-based interoperability solution amongst the US, UK, and Japan for mutual recognition of trust, capturing private and public sector use cases with different assurance levels.

Prof. Matuszek receives prestigious NSF CAREER award for robotics research

Matuszek’s new CAREER award focuses on how robots can learn to understand how speech refers to objects and environments when dealing with diverse end-users.

Prof. Cynthia Matuszek receives prestigious
NSF CAREER award for robotics research

CSEE professor Cynthia Matuszek received an NSFCAREER award to support her research on improving the ability of robots to interact with people in everyday environments. The five-year award will provide nearly $550,000 in funds to support research by Dr. Matuszek and her students in the Interactive Robotics and Language lab.

The CAREER award is part of the NSF Faculty Early Career Development Program and is considered one of NSF’s most prestigious grants.  It supports faculty members beginning their independent careers and who have “the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization.”  One of the program’s central goals is to help early-career faculty “build a firm foundation for a lifetime of leadership in integrating education and research.”

Dr. Matuszek joined UMBC in 2014 after receiving her Ph.D. at the University of Washington in Seattle, where she was co-advised by Dieter Fox and Luke Zettlemoyer.  Before beginning her graduate studies, she was a senior research lead at Cycorp.

Dr. Matuszek’s proposal, Robots, Speech, and Learning in Inclusive Human Spaces, addresses the problem of how robots can use spoken language and perception to learn how to help support people.  A description of her project is below.

“The goal of this project is to allow robots to learn to understand spoken instructions and information about the world directly from speech with end users. Modern robots are small and capable, but not adaptable enough to perform the variety of tasks people may require. Meanwhile, too many machine learning systems work poorly for people from under-represented groups. The research will use physical, real-world context to enable learning directly from speech, including constructing a data set that is large, realistic, and inclusive of speakers from diverse backgrounds.

As robots become more capable and ubiquitous, they are increasingly moving into traditionally human-centric environments such as health care, education, and eldercare. As robots engage in tasks as diverse as helping with household work, deploying medication, and tutoring students, it becomes increasingly critical for them to interact naturally with the people around them. Key to this progress is the development of robots that acquire an understanding of goals and objects from natural communications with a diverse set of end-users. One way to address this is using language to build systems that learn from people they are interacting with. Algorithms and systems developed in this project will allow robots to learn about the world around them from linguistic interactions. This research will focus on understanding spoken language about the physical world from diverse groups of people, resulting in systems that are more able to robustly handle a wide variety of real-world interactions. Ultimately, the project will increase the usability and fairness of robots deployed in human spaces.

This CAREER project will study how robots can learn about noisy, unpredictable human environments from spoken language combined with perception, using context derived from sensors to constrain the learning problem. Grounded language refers to language that occurs in and refers to the physical world in which robots operate. Human interactions are fundamentally contextual: when learning about the world, we focus on learning by considering not only direct communication but also the context of that interaction. This work will focus on learning semantics directly from perceptual inputs combined with speech from diverse sources. The goal is to develop learning infrastructure, algorithms, and approaches to enable robots to learn to understand task instructions and object descriptions from spoken communication with end users. The project will develop new methods of efficiently learning from multi-modal data inputs, with the ultimate goal of enabling robots to efficiently and naturally learn about their world and the tasks they should perform.”

UMBC Computer Science open-rank, tenure-track faculty position

Computer Science Professor
University of Maryland Baltimore County (UMBC)
Department of Computer Science and Electrical Engineering

The Department of Computer Science and Electrical Engineering (CSEE) at the University of Maryland, Baltimore County (UMBC) invites applications for an open-rank, tenured/tenure-track position in Computer Science to begin in the Fall of 2022. We are committed to inclusive excellence and innovation and welcome applications from women, minorities, veterans, and individuals with disabilities. UMBC is an affirmative action/equal opportunity employer.

The College of Engineering and Information Technology (COEIT) at UMBC crosses the boundaries of engineering, computing, and information disciplines to develop research and educational programs that engage faculty, students, and staff from all of the disciplines. COEIT is deeply committed to the success of all of our faculty. We have formal programs including “launch committees” to encourage regular and structured mentorship for faculty to start successfully, mentoring programs to provide support in the longer term, shared services for grant finance support, grant writing and editing support, monthly gatherings in which faculty share lunch and community, and we encourage all of our faculty to participate in the university’s eminent scholar mentor program to build relationships with leaders in the field beyond UMBC. You can read more about these programs and our Diversity & Inclusion initiatives on our website.

The University of Maryland, Baltimore County (UMBC) community redefines excellence in higher education through an inclusive culture that connects innovative teaching and learning, research across disciplines, and civic engagement. We advance knowledge, economic prosperity, and social justice by welcoming and inspiring inquisitive minds from all backgrounds. According to the 2021 US News and World Best Colleges Report, UMBC placed 6th in the Most Innovative Schools category and 6th in the Best Undergraduate Teaching category. To continue to support this goal, the Faculty Development Center leads the Nation in supporting and guiding faculty in their educational mission with regular workshops and pedagogical demonstrations. In the 2021 Chronicle of Higher Education Great College to Work For rankings, UMBC is on the list for the 12th year in a row and is in the Honor roll for the 10th year.

UMBC is a research-intensive university that is leading the world in inclusive excellence in research and teaching. We are redefining how to teach, and we are one of the most innovative universities in the nation, according to US News. Our research is bold, cross-disciplinary, and leverages our location near the hospitals in Baltimore, NIH, NASA, NSF, and USGS. Inclusive excellence also means being a strong community partner in Baltimore, and the UMBC Shriver Center and Center for Democracy and Civil Life help forge and maintain connections. Social justice is core to our role in Baltimore, Maryland, and beyond.

UMBC’s campus is located on 500 acres just off I-95 between Baltimore and Washington DC, and less than 10 minutes from the BWI airport and Amtrak station. The campus includes the bwtech@UMBC research and technology park, which has special programs for startups focused on cybersecurity, clean energy, life sciences, and training. We are surrounded by one of the greatest concentrations of commercial, cultural, and scientific activity in the nation. Located at the head of the Chesapeake Bay, Baltimore has all the advantages of modern, urban living, including professional sports, major art galleries, theaters, and a symphony orchestra. The city’s famous Inner Harbor area is an exciting center for entertainment and commerce. The nation’s capital, Washington, DC, is a great tourist attraction with its historical monuments and museums. Just ten minutes from downtown Baltimore and 30 from the D.C. Beltway, UMBC offers easy access to the region’s resources by car or public transportation.


Applicants should have or be completing a Ph.D. in a relevant discipline, have demonstrated the ability to pursue a funded research program, have a strong commitment to undergraduate and graduate teaching, and have a strong commitment to diversity and inclusive excellence. Candidates will be expected to build and lead a team of student researchers, obtain external research support, and teach both graduate and undergraduate courses. We welcome applications that can build and expand upon the areas of specialization in Computer Science.

Application Instructions

Applicants should submit a cover letter, a statement of research experience and interests, a statement of teaching experience and interests, a statement of commitment to diversity and inclusive excellence, a CV, and three letters of recommendation at Interfolio.

For full consideration, please submit application materials by January 15th, 2022. Applications will be accepted until the position is filled. Please send questions to and see for more information.

Application Process

This institution is using Interfolio’s Faculty Search to conduct this search. Applicants to this position receive a free Dossier account and can send all application materials, including confidential letters of recommendation, free of charge.

UMBC is an Equal Opportunity/Affirmative Action Employer.

UMBC Professor Mohamed Younis elected Fellow of the IEEE

Professor Mohamed Younis has been elected as Fellow of the Institute of Electrical and Electronics Engineers.

UMBC CSEE Professor Mohamed Younis has been elected as a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) for his contributions to protocols, architecture, and analysis of multi-hop wireless networks.  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.

Dr. Younis is currently a professor and associate chair for UMBC’s Computer Science and Electrical Engineering department. Previously he served as the director of UMBC’s Computer Engineering graduate program. Before joining UMBC, he was with Honeywell International Inc., where he led multiple projects to build integrated fault-tolerant avionics and dependable computing infrastructure and participated in developing the Redundancy Management System for the Vehicle and Mission Computer for NASA’s X-33 space launch vehicle.

Dr. Younis’ technical interest includes network architectures and protocols, wireless sensor networks, embedded systems, fault-tolerant computing, secure communication, and distributed real-time systems. He has published over 300 technical papers in refereed conferences and journals and has seven granted and three pending patents. In addition, he serves or has served on the editorial board of multiple journals and the organizing and technical program committees of numerous conferences.

The IEEE Board of Directors confers the IEEE Grade of Fellow upon a person with an outstanding record of accomplishments in any of the IEEE fields of interest. The total number selected in any one year cannot exceed one-tenth of one- percent of the total voting membership. IEEE Fellow is the highest grade of membership and is recognized by the technical community as a prestigious honor and a significant career achievement.

Five CSEE Faculty included in World Ranking of Top Computer Scientists in 2021

Five CSEE Faculty in 2021 World Ranking of Top Computer Scientists*

On May 10, 2021, Guide2Research released the 7th edition of the annual ranking for top scientists in the area of computer science and electronics. Many metrics were considered in measuring the research profiles of over 6300 computer scientists worldwide in order to determine their ranking.

The inclusion of five CSEE faculty in these rankings highlights the cutting-edge computer science research that is coming out of UMBC, and the rich learning environment available to CSEE students. The groundbreaking research taking place in CSEE has provided a foundation for drawing in top-notch scientists and students, and helped to build CSEE’s reputation as a leader in computer science education.

Faculty Name TitleNational RankingWorld RankingCitations
TIMOTHY FININProfessor, Willard & Lillian Hackerman Chair14621546,065
ANUPAM JOSHIOros Family Professor & Chair29847927,390
TULAY ADALIDistinguished Professor738122721,152
CHEIN-I CHANGProfessor858144824,294
MOHAMED YOUNISProfessor and Associate Chair1392259522,582

*Guide2Research – For the 2021 7th edition of the ranking, more than 6300 scientist profiles have been examined with several indicators and metrics reviewed in order to consider each scientist’s inclusion in the ranking. The position in the ranking was based on H-index value from Google Scholar. Only scientists with an H-index >= 40 were considered. The second verification step included a manual examination of each scientist’s list of publications on DBLP to ensure they are indeed authors of a significant number of computer science-related publications. The final step involved the verification of awards and fellowships of each researcher. 

Prof. Anthony Johnson selected as the 2021 recipient of The Optical Society Stephen D. Fantone Distinguished Service Award

Professor Anthony Johnson selected as the 2021 recipient of The Optical Society Stephen D. Fantone Distinguished Service Award

CSEE Professor Anthony Johnson has been selected as the 2021 recipient of The Optical Society (OSA) Stephen D. Fantone Distinguished Service Award. Dr. Johnson is being honored specifically for decades of principled leadership and steadfast service to The Optical Society and to the optics community, and especially for serving as a tireless ambassador for OSA.

Dr. Johnson has served in numerous leadership roles for OSA, including Director-at-Large on OSA’s Board of Directors, chair of the Women & Minorities Committee, and chair of the Awards Council. He was the 2002 OSA President, and continues to remain active with OSA. He currently sits on the Presidential Advisory Committee (PAC) and serves as a member of the OSA Diversity, Equity and Inclusion Rapid Action Committee (DEI RAC). In addition to his service to OSA, Johnson is an active leader in the National Society of Black Physicists, American Physical Society (APS), and IEEE, and he supported the African Laser Atomic, Molecular, and Optical Sciences Network (LAM Network) by establishing the African Optics and Photonics Society.

Founded in 1916, OSA is the leading professional organization for scientists, engineers, students and business leaders who fuel discoveries, shape real-life applications and accelerate achievements in the science of light. Through world-renowned publications, meetings and membership initiatives, OSA provides quality research, inspired interactions and dedicated resources for its extensive global network of optics and photonics experts.

This award was established in 1973 by the Board of Directors. It is presented to a recipient who, over an extended period of time, has served the Optical Society in an outstanding way, especially through volunteer participation in its management, operation, or planning in such ways as editorship of a periodical, organization of meetings, or other service to the Society. He joins an esteemed group of past recipients recognized for their outstanding contributions, service, and leadership in the field of optics and photonics.

press release announcing several 2021 award winners is available, as well as an announcement about the 2021 Stephen D. Fantone Distinguished Service Award.

Prof. Chein-I Chang honored by journal special issue dedication

Prof. Chein-I Chang honored by journal special issue dedication

CSEE Professor Chein-I Chang was recently honored by the IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing by dedicating an upcoming special issue to him. The special issue is on Hyperspectral imaging and data exploitation, a topic that Professor Chang has pioneered and published more than 300 research papers and books on over the past 30 years.

Hyperspectral imaging is a technique in remote sensing data processing that expands and improves multispectral image analysis capability. It takes advantage of hundreds of contiguous spectral channels to uncover materials that usually cannot be resolved by multispectral sensors.

Professor Chein-I Chang established his Remote Sensing Signal and Image Processing Laboratory shortly after joining UMBC in 1991 with a research focus that has included remote sensing, signal and image processing, hyperspectral imaging, medical imaging, and automatic target recognition. The RSSIPL lab has produced more than 40 Ph.D. graduates, nearly 50 M.S. graduates, and many patents.

In dedicating the special issue, the journal’s call for papers says.

“Prof. Chein-I Chang is an important pioneer in the areas of hyperspectral imaging and data exploitation, including many new developments in target/anomaly detection, classification, endmember finding/unmixing, band set/subset selection, compressive sensing, real-time processing, etc. His contributions to these areas have been of great importance, with many highly innovative ideas and techniques that are now currently being used in academia and industries for analyzing and interpreting remotely sensed hyperspectral data. With the special occasion of his 70th anniversary, this special issue honors his contributions by soliciting papers in the main areas in which Prof. Chang has remained active for more than 30 years.”

Visiting Prof. Ed Raff’s forthcoming book: Inside Deep Learning

Visiting Prof. Ed Raff’s forthcoming book Inside Deep Learning

Congratulation to Dr. Edward Raff for his forthcoming book Inside Deep Learning being published by Manning. The first three chapters are now available free online via Manning’s Early Access Program, with more to come. Dr. Raff is a Chief Scientist at Booz Allen Hamilton and both an alumnus of and visiting assistant professor in the UMBC CSEE department. 

He describes the target audience for his book as “the middle between “give me a tool” and ‘CS/Stats/ML Ph.D. graduate book’ that gives utility and understanding.” He gives thanks to his UMBC students in his Computer Science and Data Science classes who have been “guinea pigs for this book/course material.”

Here’s how the publisher describes the book: “Inside Deep Learning is a fast-paced beginners guide to solving common technical problems with deep learning. Written for everyday developers, there are no complex mathematical proofs or unnecessary academic theory. You’ll learn how deep learning works through plain language, annotated code, and equations as you work through dozens of instantly useful PyTorch examples. As you go, you’ll build a French-English translator that works on the same principles as professional machine translation and discover cutting-edge techniques just emerging from the latest research. Best of all, every deep learning solution in this book can run in less than fifteen minutes using free GPU hardware!”

Ed Raff received a Ph.D. in Computer Science in 2018 with a dissertation on “Malware Detection and Cyber Security via Compression.” He is currently a Chief Scientist at Booz Allen Hamilton. He has done research on deep learning, malware detection, reproducibility in machine learning, detecting fairness and bias in machine learning models and data analytics, and high-performance computing. He has also been a visiting Assistant Professor at UMBC since 2018 and taught in both the Computer Science and Data Science programs. Dr. Raff has over 40 peer-reviewed publications, three best paper awards, and has presented at many major conferences.

Prof. Sherman receives Hrabowski Fund for Innovation award to develop quantum computing teaching material

Prof. Sherman receives Hrabowski Fund for Innovation award to develop quantum computing teaching material

CSEE Professor Alan Sherman received a seed award from UMBC’s Hrabowski Fund for Innovation to develop educational material for quantum algorithms. The project, Evaluation and Enhancement of a Learning Unit on Quantum Algorithms, will involve a multidisciplinary team that will assess and enhance materials for a two-week learning unit on algorithms for quantum computers for use in a general course on algorithms. Some material has already been developed and field-tested in UMBC’s computer science graduate algorithms course, CMSC 641.

The educational unit will introduce the new transformative paradigm of quantum algorithms, which offers tremendous potential for solving important complex problems when executed on a quantum computer. This project will make this learning unit, including its six videos and other materials, freely available after they are revised and enhanced based on reviews by three experts.

The Hrabowski Fund for Innovation exemplifies UMBC’s commitment to investing in faculty initiatives that fuel creativity and enterprise and also create opportunities for student engagement.

New NSF grant to improve human-robot interaction

person interacting with a virtual robot
Professor Ferraro in UMBC’s Pi2 visualization laboratory talking to a virtual robot.

CSEE faculty receive NSF award to help robots learn tasks by interacting naturally with people

UMBC Assistant Professors Cynthia Matuszek (PI) and Francis Ferraro (Co-PI), along with senior staff scientist at JHU-APL John Winder (Co-PI) received a three-year NSF award as part of the National Robotics Initiative on Ubiquitous Collaborative Robots. The award for Semi-Supervised Deep Learning for Domain Adaptation in Robotic Language Acquisition will advance the ability of robots to learn from interactions with people using spoken language and gestures in a variety of situations.

This project will enable robots to learn to perform tasks with human teammates from language and other modalities, and then transfer what they have learned to other robots with different capabilities in order to perform different tasks. This will ultimately allow human-robot teaming in domains where people use varied language and instructions to complete complex tasks. As robots become more capable and ubiquitous, they are increasingly moving into complex, human-centric environments such as workplaces and homes.

Being able to deploy useful robots in settings where human specialists are stretched thin, such as assistive technology, elder care, and education, has the potential to have far-reaching impacts on human quality of life. Achieving this will require the development of robots that learn, from natural interaction, about an end user’s goals and environment.

This work is intended to make robots more accessible and usable for non-specialists. In order to verify success and involve the broader community, tasks will be drawn from and tested in community Makerspaces, which are strongly linked with both education and community involvement. It will address how collaborative learning and successful performance during human-robot interactions can be accomplished by learning from and acting on grounded language. To accomplish this, the project will revolve around learning structured representations of abstract knowledge with goal-directed task completion, grounded in a physical context.

There are three high-level research thrusts: leverage grounded language learning from many sources, capture and represent the expectations implied by language, and use deep hierarchical reinforcement learning to transfer learned knowledge to related tasks and skills. In the first, new perceptual models to learn an alignment among a robot’s multiple, heterogeneous sensor and data streams will be developed. In the second, synchronous grounded language models will be developed to better capture both general linguistic and implicit contextual expectations that are needed for completing shared tasks. In the third, a deep reinforcement learning framework will be developed that can leverage the advances achieved by the first two thrusts, allowing the development of techniques for learning conceptual knowledge. Taken together, these advances will allow an agent to achieve domain adaptation, improve its behaviors in new environments, and transfer conceptual knowledge among robotic agents.

The research award will support both faculty and students working in the Interactive Robotics and Language lab on this task. It includes an education and outreach plan designed to increase participation by and retention of women and underrepresented minorities (URM) in robotics and computing, engaging with UMBC’s large URM population and world-class programs in this area.

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