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.

Prof. Tülay Adali receives prestigious Humboldt Research Award for advanced data analysis


Prof. Tülay Adali receives prestigious Humboldt Research Award for advanced data analysis


UMBC’s Tülay Adali, professor of computer science and electrical engineering (CSEE) and distinguished university professor, has received the prestigious Humboldt Research Award. The Alexander von Humboldt Foundation describes the award as presented to scholars “whose fundamental discoveries, new theories, or insights have had a significant impact on their own discipline and who are expected to continue producing cutting-edge achievements in the future.”

UMBC Professor Tülay Adali
Tülay Adali. Photo courtesy of Adali.

Adali is the director of UMBC’s Machine Learning for Signal Processing Lab. Her research focuses on developing flexible methods for data fusion. These innovative methods enable researchers to extract powerful features from multi-modal data by letting them fully interact with and inform each other.

A main application area of her work has been medical image analysis, where these features are used in diagnosis as well as treatment planning and evaluation. Adali and her research collaborators are also exploring applications of these methods in remote sensing, misinformation detection, and gesture and video analysis. 

A years-long research collaboration

Humboldt Award recipients spend up to one year conducting collaborative research at institutions in Germany. Adali plans to continue to work with her longtime collaborator Peter Schreier, who is based in Paderborn University. Through a research connection that has spanned many years, Adali says that her lab and Schreier’s continue to have wonderful synergy. 

Together, Adali and Schreier have worked to address problems such as data-driven discovery of relationships in multi-modal data, and in particular, when the sample sizes are small. “This is a key practical problem in many applications, especially in the medical domain,” Adali shares. She notes that this provides an important starting point for their current work. 

“Things are moving along, even though I could not travel this summer, as we started having weekly research meetings between our groups,” Adali says. “This is a valuable experience for my students. In the past, we had hosted Schreier and his students here at UMBC, some of my students had met Schreier and his students at conferences before, and these initial physical connections matter. I am hoping we will all be able to travel again, soon.”

Receiving the award

As a Humboldt Award recipient, Adali was invited to attend a gathering in June with her fellow awardees, hailing from universities around the world. Due to COVID-19, the event was moved online. Awardees had an opportunity to meet the German president virtually as part of the event. 

While she wishes the event could have been held in person, Adali says that it gave her an exciting opportunity to connect with other Humboldt awardees and learn more about scientist and explorer Alexander von Humboldt.

In 2015, Curtis Menyuk, professor of CSEE, received a Humboldt Award.


Adapted from a UMBC News article written by Megan Hanks. Banner image: Tülay Adali, fourth from left, with the members of her lab. Photo courtesy of Adali.

UMBC’s Naghmeh Karimi receives NSF CAREER Award to develop long-lasting security for cryptographic chips

 

Naghmeh Karimi receives NSF CAREER award to develop long-lasting security for cryptographic chips

 

Naghmeh Karimi is the most recent UMBC faculty member to receive a prestigious CAREER Award from the National Science Foundation (NSF). The grant, totaling approximately $500,000 over five years, will support her work to investigate how device-aging related risks compromise the security of cryptographic devices.

Karimi explains that cryptographic chips offer continued advances in authenticating messages and devices as well as preserving the integrity and confidentiality of sensitive information. They do so by implementing cryptographic algorithms in hardware. These chips combine the benefits of cryptographic applications with the speed and power advantage of hardware implementations. 

Despite their significant benefits, cryptographic chips can be compromised by adversaries who have gained physical access to the chips. Current protections against such attacks do not consider the aging of devices, which can shift device parameters over time.

Addressing security vulnerabilities 

Aging makes cryptographic chips operate slower and, ultimately, results in their malfunction, says Karimi. She explains that the typical lifetime of integrated circuits is 7 to 8 years. As the devices age, their performance decreases. Karimi is exploring the specific security vulnerabilities of aged devices and how they can be protected.

“We want to preserve the security of devices over their lifetime,” Karimi says.

Karimi and her research team will study whether the success of the side-channel analysis and fault-injection attacks increase in older devices. Karimi will create and test several countermeasures to protect devices against such attacks.

Connecting students with opportunities in tech security

The CAREER Award funding will support several UMBC undergraduate and graduate student researchers working with Karimi to develop long-lasting security solutions for hardware platforms. 

At the same time, Karimi will also develop and launch a new course in UMBC’s computer science and electrical engineering department on cryptography, hardware security, and testing. She will also work with the UMBC Cyber Scholars Program to connect students with internship opportunities focused on hardware security, to give them additional hands-on experience in the field. 

“The success of this project will enable us to develop long-lasting security for trusted hardware platforms,” Karimi says. “This will result in aging-resistant security solutions that benefit society through devices that remain secure over their lifetime.”


Adapted from a UMBC News article by Megan Hanks. Banner image: UMBC’s ITE building. Photo by Marlayna Demond ’11 for UMBC.

CSEE Prof. LaBerge receives USM Board of Regents’ Faculty Award for Excellence in Teaching

 

CSEE Prof. LaBerge receives USM Board of Regents’
Faculty Award for Excellence in Teaching

 

E. F. Charles LaBerge, Professor of the Practice in the Computer Science and Electrical Engineering department, has been awarded the 2020 University System of Maryland Board of Regents’ Faculty Award for Excellence in Teaching.

Since joining UMBC in 2008, E.F. Charles LaBerge’s career has been marked by outstanding classroom instruction, innovative teaching methods, and development of active learning spaces on campus. He brings a wealth of industry experience and knowledge to UMBC students enrolled in the range of courses that he teaches. As a professor of the practice in computer science and electrical engineering, LaBerge exposes his students to computer and electrical engineering concepts through real-world examples and multidisciplinary instruction. His extensive connections in industry have benefited his students and helped to prepare them for careers and graduate degrees.

As an instructor for the introduction to engineering course taken by all engineering students, he has impacted the educational careers of students across the College of Engineering and Information Technology (COEIT). He consistently receives high ranks and positive comments from students on course evaluations. Both his students and colleagues acknowledge and appreciate LaBerge’s modern approach to classroom instruction, which incorporates technology and new practices.

LaBerge was instrumental in the development of UMBC’s Active Learning Center, a space that supports collaborative learning to promote student success and retention in computing courses. He is a strong supporter of students across campus, opening his office to students, from those who have questions about classes to those seeking professional advice and mentorship. His teaching extends beyond the classroom, and he supports and mentors students presenting at UMBC’s annual Undergraduate Research and Creative Achievements Day each spring.

He is a very engaged member of COEIT, having served as the undergraduate program director for computer engineering and as the coordinator for computer engineering’s accreditation program, among other roles. His commitment to the College was recognized with the inaugural College of Engineering and Information Technology Award for Teaching Excellence in 2018. This award was presented to him based on feedback from fellow faculty and colleagues.

LaBerge earned his B.S. and M.S. in electrical engineering from Johns Hopkins University, and his Ph.D. in electrical engineering from UMBC.

Adapted from the UMBC faculty awards announcement.

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