Research Laboratories

Research Centers and Laboratories

Computer Science

  • CCL – Computing Compass Lab

    Director: Dr. Chenchen Liu
    Office No. : ITE 325 L, Lab No. : ITE 339

    Develop Novel Computing Paradigms for High-Performance Intelligence Computing and exploring innovations in the algorithm, architecture, system, and circuit designs for Artificial Intelligence. Research topics cover Novel Computer Architecture and Hardware for Artificial Intelligence, Neuromorphic Computing, Deep Learning, Edge Computing, VLSI Design with Emerging Technologies.

  • CDL – Cyber Defense Lab

    Director: Dr. Alan T. Sherman
    Office No. : ITE 224, Lab No. : ITE 228

    The UMBC Cyber Defense Lab (CDL) is a place where students, faculty, and affiliates carry out cybersecurity research. Current projects include high-integrity voting, protocol analysis, and cybersecurity education.

  • CORAL – Cognition Robotics and Learning Lab

    Director: Dr. Tim Oates
    Office No. : ITE 336, Lab No. : ITE 361

    Research in topics related to machine and human intelligence, including machine vision, natural language processing, and reinforcement learning. The long-term goal is to understand how machines can match the human developmental trajectory from sensors to symbols to semantics.  Current projects include sample efficient reinforcement learning for the real world, safe artificial intelligence, graph neural networks for anomaly detection in learned models, and multi-modal learning from images and text.

  • DAMS – Data Management and Semantics

    Director: Dr. Roberto Yus
    Office No. : ITE 342, Lab No. : ITE 230

    he UMBC DAMS Research Group focuses on four main areas of research: Data Management, AI, Privacy, and the Internet of Things. We deal with research challenges in bridging the gap that exists between raw data (e.g., data captured by sensors) and semantically meaningful data that is easily understood by people (e.g., inferences extracted from sensor observations). We incorporate semantics and privacy-awareness to data management to design smarter and more responsible systems. Also, we develop prototypes of the approaches/systems designed as part of the research tasks and deploy them in the real world.

  • DREAM – Discovery, Research, and Experimental Analysis of Malware Lab

    Director: Dr. Charles Nicholas
    Office No. : ITE 356, Lab No. : ITE 366

    The DREAM lab looks at ways of applying machine learning to cybersecurity, and malware analysis in particular. Recent projects involve using tensor decomposition and innovative measures of string similarity to solve practical problems. The lab is also home to UMBC’s very active cyberdefense competition team, the ‘CyberDawgs’

  • Ebiquity Research Laboratory

    Director: Dr. Anupam Joshi
    Office No. : ITE 328, Lab No. : ITE 332

    Director: Dr. Tim Finin
    Office No. : ITE 329, Lab No. : ITE 332, ITE 338

    Building intelligent systems in open, heterogeneous, dynamic, distributed environments.  Research topics include the semantic web, information extraction, mobile computing, privacy, and security.

  • ESNET – Embedded Systems and Networks Laboratory

    Director: Dr. Mohamed Younis
    Office No. : ITE 325 G, Lab No. : ITE 391

    Design and management of wireless sensor networks, network architecture and protocols, underwater communication, MAC and routing protocols for ad-hoc and sensor networks, energy-aware system design, secure communication, fault tolerance, topology management, and applications of sensor and actuator networks.

  • IRAL – Interactive Robotics and Language Laboratory

    Director: Dr. Cynthia Matuszek
    Office No. : ITE 331, Lab No. : ITE 343

    Research in robotics, human-robot interaction, and grounded language understanding, bringing together robotics, natural language processing, and statistical learning approaches to build advanced intelligent agents that can interact robustly with non-specialists.

  • KAI² – Knowledge-infused AI and Inference

    Director: Dr. Manas Gaur
    Office No. : ITE 337, Lab No. : ITE 367

    KAI² believes in the integration and uplifting of AI with human knowledge representable in different forms: Structural Knowledge Graphs, Flattened Lexicons, Process Knowledge in Questionnaires, and Commonsense in General-purpose unstructured content, to design human-centered systems and applications for sensitive domains. Furthermore, we want to make the next-generation neuro-symbolic AI approach inspired by human’s ability to combine data and knowledge to induce Explainable, Interpretable, and Safety aspects in statistical AI.

  • VANGOGH – Visualization, Animation, Non-Photorealistic Graphics, Object Modeling, and Graphics Hardware

    Director: Dr. Adam Bargteil
    Office No. : ITE 341, Lab No. : ITE 365

    Director: Dr. Marc Olano
    Office No. : ITE 354, Lab No. : ITE 352, 365

    The VANGOGH lab covers a range of research in computer graphics and animation. Computer graphics research focuses on real-time approaches using graphics hardware, particularly in areas of visual appearance, data visualization, and techniques applicable to computer games. Animation research focuses on natural phenomena, including physics-based techniques, numerical methods, and machine learning.

  • Vinjamuri Lab

    Director: Dr. Ramana Vinjamuri
    Office No. : ITE 301, Lab No. : ITE 376

    Our lab studies Brain-Machine Interfaces (BMIs) that control upper-limb prostheses. In particular, we are interested in how the brain controls complex hand movements. The human hand has about 30 dimensions in contrast to a human arm with only 7 dimensions. BMIs that control human arms have already been demonstrated with decent accuracy. What type of interface is needed to Extend Brain-Machine Interface control from 7 to 37 dimensions forms the central topic of our research. Our lab contains a mix of current Graduate, Undergraduate, and Highschool Students along with a range of collaborators from multiple industries. Our range of publications dating back to 2014 includes multiple Patents, Articles, Conference Appearances, and more. Our work has been recognized through many Showcases, Grants, and Awards alongside our students who continue to impress.

Computer Engineering

  • ECLIPSE Cluster

    Director: Dr. Nilanjan Banerjee
    Office No. : ITE 362, Lab No. : ITE 351

    Director: Dr. Ryan Robucci
    Office No. : ITE 319, Lab No. : ITE 317

    The ECLIPSE cluster comprises groups with shared laboratories, projects, and students: the Mobile, Pervasive, & Sensor Systems Laboratory led by Dr. Nilanjan Banerjee, and the Covail Analog & Digital Systems Research Laboratory, led by Dr. Ryan Robucci

  • ESNET – Embedded Systems and Networks Laboratory

    Director: Dr. Mohamed Younis
    Office No. : ITE 325 G, Lab No. : ITE 391

    Design and management of wireless sensor networks, network architecture and protocols, underwater communication, MAC and routing protocols for ad-hoc and sensor networks, energy-aware system design, secure communication, fault tolerance, topology management, and applications of sensor and actuator networks.

  • VLSI-SOC Group

    Director: Dr. Riadul Islam
    Office No. : ITE 316, Lab No. : ITE 313

    The primary research areas include Electronic Design and Automation, Brain-inspired computing, Neural network architecture exploration, Autonomous driving and CAN security, digital, analog, and mixed-signal CMOS ICs/SOCs for a variety of applications, Verification and testing techniques, CAD tools for design and analysis of microprocessors and FPGAs, as well as interdisciplinary research projects.

Electrical Engineering

  • CASPR – Center for Advanced Studies in Photonics Research

    Director: Dr. Anthony Johnson
    Office No. : TRC 029, Lab No. : TRC 027

    Advanced photonics research and technology development in optical communications, optical sensing and devices, nanophotonics, biophotonics, and quantum optics.

  • Choa’s Lab

    Director: Dr. Fow-Sen Choa
    Office No. : ITE 303, TRC 274, Lab No. : TRC 018, 151, 153, 155, 156, 159, 291, 292, 293

    The lab is developing novel transcranial magnetic stimulation coils for multisite brain stimulations, extracting brain signals with designed experiments using EEG tools, studying brain dynamics and neural disorders from analyzing fMRI scanned data sets, and building human level intelligent systems through neural network architecture design and modelling. We also continue our research on design, growth and fabrication of photonic and nano-materials and devices including single photon detectors, photonic integration of tunable lasers and detector, mid-IR devices and arrays, meta-materials, phase changing materials, neuromorphic and neural computing devices for AI chips.

  • Computational Photonics Laboratory

    Director: Dr. Curtis Menyuk
    Office No. : ITE 304, Lab No. : TRC 200, 201, 202, 203, 204, 205

    Assistant Director: Dr. Ergun Simsek
    Office No. : ITE 325 K, Lab No. : TRC 201 B

    Computational and theoretical studies of nonlinear optics, RF photonics, and frequency combs. We investigate nonlinear effects in optical fibers including soliton generation and transmission, supercontinuum generation, and four wave mixing. We study frequency comb generation in fiber lasers and microresonators and the noise processes that limit the performance of these devices and the overall system performance. We also study photodetectors, sensors, motheye surfaces, and other components that play an important role in photonic transmission and RF photonics. We use modern machine learning algorithms to optimize the performance of the RF-photonic devices and systems as well as the frequency comb systems that we investigate.

  • MLSP-Lab – Machine Learning for Signal Processing Laboratory

    Director: Dr. Tulay Adali
    Office No. : ITE 324, Lab No. : ITE 363

    Our focus is the development of theory and tools for processing of signals that arise in today’s growing array of different applications and pose challenges for traditional signal processing techniques.  We bring in techniques from statistical and adaptive signal processing as well as machine learning to develop effective methods to address challenges in a wide array of applications with a focus on medical image analysis and fusion.

  • Remote Sensing Signal and Image Processing Laboratory

    Director: Dr. Chein-i Chang
    Office No. : ITE 310, Lab No. : ITE 370

    Research on remote sensing, signal and image processing, specifically, hyperspectral imaging, medical imaging, and automatic target recognition.