Research Focus Areas and Centers

Focus Areas

Brain Discovery

The human brain is the most complex organ in our body – and possibly the most complex entity on earth.  It controls decision making to each and every process that controls our body.  This organ that weighs just about three pounds has stunned and delighted scientists and engineers for decades and continues to do so.  Our work encompasses brain-computer interfaces, their applications in human-robot interaction, the study of brain networks and connectivity, understanding the brain function using brain imaging and data fusion methods, brain stimulation (deep and focused transcranial magnetic stimulation), and cortical arousal during sleep.  Our work targets understanding the healthy or developing brain as well as one suffering from a disorder.

Work in the area is conducted in the following research labs as well as part of an upcoming NSF IUCRC center, Building Reliable Advances in Neurotechnologies (BRAIN).  The center has the following five themes spearheaded by diverse faculty in our department: cyber-human systems, AI and Big Data for Brain, Neural Signal Processing and Machine learning, Neural stimulation, and Virtual and augmented reality.  For more information please see www.nsfbrain.org.

Research Faculty and Labs

Tulay Adali – Machine Learning for Signal Processing Lab

Nilanjan Banerjee – Mobile Pervasive and Sensory Systems Lab

Justin Brooks

Fow-Sen Choa – Choa’s Lab

Seung-Jun Kim – Signal Processing and Smart Systems Lab

Ramana Kumar Vinjamuri – Vinjamuri Lab 

Human-System Engineering to Optimize Health and Performance

The proliferation of technologies for mobile and pervasive sensing, advances in computational/cloud capabilities, and advances in machine learning and AI are shaping multidisciplinary frontiers for systems that improve the human condition: health and well-being.  Individuals and patients across diverse groups and caregivers cooperating with new technology can now address afflictions and surpass past limitations, such as those imposed by gaps in observability and obstacles to the frequency of interactions so that we can
  • explore new datasets with increased volume, complexity, and real-world variability;
  • develop novel systems to collect data and provide real-time feedback and intervention;
  • enable caregiver data exploration and assisted interpretation.
Humans and systems can work integratively to address a wide range of health and performance-related conditions, including disease states (e.g., diagnosis, illness trajectory monitoring) and performance states (e.g., stress, fatigue, boredom). Our research in this area spans sensor and embedded system development, real-time control systems, and applications of machine learning methods to human state estimation.

Research Faculty and Labs

Nilanjan Banerjee – Mobile Pervasive and Sensory Systems Lab

Justin Brooks

Sanorita Dey – Social Intelligence Lab

Manas Gaur – KAI² – Knowledge-infused AI and Inference

Tim Oates – CORAL – Cognition Robotics and Learning Lab

Ryan Robucci – Covail Lab

Ramana Kumar Vinjamuri – Vinjamuri Lab 

Mohamed Younis – ESNET – Embedded Systems and Networks Laboratory

Natural Language Processing (NLP)

Natural Language Processing (NLP) is an interdisciplinary field that lies at the intersection of computer science, artificial intelligence, and linguistics. It focuses on the interaction between computers and humans through natural language—or the computational processing of human-human communication, aiming to enable machines to understand, interpret, and generate human language in a manner that is both meaningful and useful. Although definitions might vary, the broadest definition of NLP encompasses textual processing & understanding as well as speech processing (speech recognition/analysis/synthesis), natural language generation (NLG), computational linguistics (using computational techniques to study human languages), and social computing (social media analysis). Many modern NLP techniques leverage machine learning and deep learning, seeking to bridge the gap between human communication and computer understanding. As an evolving field, NLP continues to grow in importance with the increasing volume of unstructured data and the rising use of large language models (LLMs) like ChatGPT. NLP can include a variety of tasks such as text analysis, translation, and summarization. (Description edited from GPT-4o output using the prompt “Please provide a paragraph describing the field of natural language processing.”)

NLP Research at UMBC has included, but is not limited to:

  • Grounded understanding of events
  • Safe usage of LLMs via neuro-symbolic methods
  • NLP and robotics
  • Applications for text generation
  • Reasoning with extracted representations from text
  • Social computing
  • Multimodal Learning (vision and language)

Research Faculty and Labs

Sanorita Dey – Social Intelligence Lab

Frank Ferraro

Tim Finin

Manas Gaur – KAI² – Knowledge-infused AI and Inference

Tejas Gokhale – Cognitive Vision Group

Lara J. Martin – LARA Lab

Cynthia Matuszek – IRAL

Tim Oates – CORAL – Cognition Robotics and Learning Lab

 

Centers

CARTA – Center for Accelerated Real-Time Analytics

Director: Dr. Karuna Joshi

An NSF-sponsored IUCRC center focused on cutting-edge inter-disciplinary research in real-time analytics using next-generation accelerated hardware.

Centaνr – Center for Navigation, Time and Frequency Research

Director: Dr. Curtis Menyuk

CENTAUR was established in 2022 to support rapidly evolving and critical Army Position, Navigation, and Timing (PNT) needs. UMBC has teamed with the National Center for Manufacturing Sciences (NCMS) under a national consortium to develop an Integrated photonics center to address this rising need.

UCYBR – UMBC Center for Cybersecurity

Director: Dr. Anupam Joshi
Assistant Director: Dr. Richard Forno

The UMBC Center for Cybersecurity is an interdisciplinary university center that unifies UMBC’s many cybersecurity capabilities. It provides Maryland and the nation with academic and research leadership, collaboration, innovation, and outreach in this critical discipline by streamlining our academic, research, workforce development, and technology incubation activities to advance UMBC’s position as a leading research university in cybersecurity-related disciplines.

UMBC Center for Artificial Intelligence

Director: Dr. Tim Finin

The UMBC Center for AI is an interdisciplinary center to support, promote, and develop UMBC communities doing research, application, and education in all areas of Artificial Intelligence.

BRAIN – Building Reliable Advances and Innovations in Neurotechnology

Director: Dr. Ramana Vinjamuri
Co-Directors: Dr. Tulay Adali, Dr. Nilanjan Banerjee, Dr. Fow-Sen Choa, and Dr. Don Engel

The BRAIN Center aims to tackle challenges in neurotechnology by bringing together experts in a wide range of topics, from neural, cognitive, and rehabilitation engineering to neurorobotics, neuromodulation, and ethical artificial intelligence. As an Industry–University Cooperative Research Center (I/UCRC), it emphasizes academic research conducted jointly with innovative industry partners, and UMBC’s location will facilitate cooperation with biomedical companies.