SE Research Labs

ANDERSSON LABORATORY

Associate Professor Sean Andersson
110 Cummington St., Boston, MA 02215
617-353-4949

The Andersson Laboratory at Boston University focuses on systems and control theory, driven in large part by applications in nanobioscience, nanotechnology, and robotics. Through a combination of fundamental theory, applied mathematics, and physical experiments, we explore dynamics in nanometer-scale systems. By focusing on scale-invariant algorithms, we draw inspiration from robotics and multi-agent systems and seek, in turn, to apply our techniques in that domain.

ADVANCED MATERIALS PROCESS CONTROL LABORATORY

Associate Professor Michael Gevelber
15 St. Mary’s St., Brookline, MA 02446
617-353-9572

Research in this laboratory focuses on improving materials processing capabilities by applying a controls-based approach. Our controls-based approach integrates process modeling, sensor development, both system and control design, and experimentation to achieve greater control of material microstructure as well as improving yield and maximizing production rate. Research projects, typically conducted with industry partners, span a range of application areas including opto-electronic applications, advanced engines, power systems, and biomedical applications. Ongoing research projects include real-time control for plasma spray for thermal barrier coatings and fuel cells, e-beam deposition for precision optical coatings, electrospinning of nanofibers, chemical vapor deposition, and Czochralski crystal growth. Research is also being conducted on developing intelligent control and sensing approaches for optimizing building HVAC systems, using university buildings to test out new ideas.

BU ROBOTICS LABORATORY

Professor Calin Belta (Director), Associate Professor Sean Andersson,
Professor John Baillieul, Professor Christos Cassandras and Professor Roberto Tron
750 Commonwealth Avenue, Brookline, MA 02446

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BIOROBOTICS RESEARCH GROUP (BRG)

Adjunct Professor Pierre Dupont
Rm 350, Enders Building, Boston Children’s Hospital
300 Longwood Ave., Boston, MA 02115
617–919–3562

The BioRobotics Research Group (BRG) solves theoretical and practical problems in minimally invasive surgery. They specialize in medical robot and instrument design, development of imaging techniques for surgical guidance, modeling tooltissue interaction; and teleoperation/automation of instrument motion. They utilize analytical tools from robotics, dynamics and control together with innovative design techniques to create successful solutions. The team members come from diverse backgrounds with degrees in mechanical/biomedical/ electrical engineering and medicine. Their specialties range from biomedical robotics, clinical practice and imaging to product design and many areas in between.

CONTROL OF DISCRETE EVENT SYSTEMS (CODES) LABORATORY

Professor Christos Cassandras
8 Saint Mary’s Street, Boston MA 02215
617-353-7154

The Control of Discrete Event Systems (CODES) Laboratory involves faculty and graduate students from the Division of Systems Engineering and operates within the Center for Information and Systems Engineering (CISE). Members of CODES conduct research on modeling, design, analysis, performance evaluation, control, and optimization of a variety of discrete event and hybrid systems including communication and sensor networks, manufacturing, transportation, and multi-agent systems. Some of the best-known analytical frameworks and methodologies in the field of discrete event systems have been pioneered by members of the CODES Laboratory. CODES research projects are supported by several federal agencies and by industry.

DATA SCIENCE & MACHINE LEARNING LABORATORY

Professor Venkatesh Saligrama
8 St. Mary’s Street, Brookline, MA 02446
617-353-1040

The Data Science & Machine Learning laboratory is involved in projects related to Machine Learning, Vision & Learning, Structured Signal Processing, and Decision & Control. In the area of machine learning recent research projects have dealt with resource constrained machine learning, graph-structured signal detection and recovery, topic modeling and anomaly detection. Another focus of our recent research is on developing machine learning methods in the context of computer vision. We work on problems involving video analytics in highly cluttered scenes, search and retrieval in large video stores, zero-shot learning, person re-identification and real-time anomaly detection.

HYBRID AND NETWORKED SYSTEMS LABORATORY (HYNESS LAB)

Professor Calin Belta
15 St. Mary’s St., Brookline, MA 02446
617-353-9586

We are interested in phenomena that occur when continuous dynamics, described by systems of differential equations, are combined with discrete dynamics, modeled as automata or state transition graphs. Such systems are called hybrid, and examples range from man-made systems such as mobile robots, to naturally occurring systems such as biochemical networks, where the continuous dynamics of metabolic processes is regulated by the logic of gene expression. Our approach to the analysis and control of such systems combine concepts and tools from computer science and control theory. Our current application areas are networked mobile robotics, swarming, gene networks, and genome scale metabolic analysis.

INFORMATION & DATA SCIENCES (IDS) LABORATORY

Associate Professor Jeffrey Carruthers, Professor Christos Cassandras, Professor David Castañón, Research Professor Robert Gray, Associate Professor Vivek Goyal, Professor Prakash Ishwar, Professor W. Clem Karl, Professor Janusz Konrad, Assistant Professor Brian Kulis, Assistant Professor Wenchao Li, Professor Thomas Little, Professor Hamid Nawab, Assistant Professor Bobak Nazer, Assistant Professor Alex Olshevsky, Professor Ioannis Paschalidis, Professor Venkatesh Saligrama, Professor David Starobinski, Assistant Professor Lei Tian, and Professor Ari Trachtenberg
8 St. Mary’s St., Boston MA 02215
617-353-1668, 617-353-9919

IDS research centers on the sensing, communication, and processing of various forms of information with the objective of designing and synthesizing secure networked systems for optimum decision-making and control. IDS members have a broad range of research interests but share a common approach to problem-solving, the pursuit of foundational research, and the development and utilization of sophisticated analytic and algorithmic tools from mathematics, statistics, computer science, and physics. The research conducted by IDS faculty and students covers a broad spectrum of problems, from advanced theory to practical algorithm implementation, in the following areas:

• Machine Learning, Big Data, and Analytics
• Computational Imaging and Inverse Problems
• Decision and Estimation Theory
• Signal, Image and Video Processing
• Biological and Medical Imaging
• Computational and Systems Biology
• Medical Informatics
• Communication and Information Theory
• Network Security

INTELLIGENT MECHATRONICS LABORATORY

Professor John Baillieul, Associate Professor Sean Andersson, and Associate Professor Hua Wang
110 Cummington Street, Boston MA 02215
617-353-9848

This laboratory is equipped with a wide variety of robotic devices including RF-networked sensor arrays, nearly forty mobile ground robots, twelve quadrotor autonomous air vehicles, and an infrared based motion capture system for precise indoor positioning. Additional resources include real-time control software, hand-held computing and communication devices, workstations, and a wide variety of sensors and actuators. This equipment is dedicated to research in limited-bandwidth control problems, symbolic control, cooperative systems and control, and animal-inspired agile flight control.

LABORATORY OF NETWORKING AND INFORMATION SYSTEMS (NISLAB)

Professor David Starobinski and Professor Ari Trachtenberg
8 St. Mary’s St., Boston, MA 02215
617-353-0202, 617-353-1581

The Laboratory of Networking and Information Systems (NISLAB) is involved in providing novel perspectives to modern networking with emphasis on security, performance, scalability, and economics. Our research focuses on using mathematics (such as algorithms, probability and stochastic processes, applied cryptography, coding theory, and game theory) and various practical tools to solve advanced problems in networking and systems, including security and privacy for mobile and vehicular networks, data synchronization and dissemination, spectrum management, network monitoring, and high-performance networking. Laboratory activities include both practical and theoretical projects, involving graduate and undergraduate students working in teams.

MULTIMEDIA COMMUNICATIONS LABORATORY

Professor Thomas D.C. Little
8 St. Mary’s St., Boston, MA 02215
617-353-9877

The Multimedia Communications Laboratory (MCL) at Boston University focuses on topics in ubiquitous distributed computing. Our legacy work is in the area of distributed multimedia information systems emphasizing time-dependent and continuous media data such as audio and video. Recent work targets wireless networking and communications to support ambient computing in indoor (smart rooms) and outdoor (vehicles) contexts.

NETWORKS RESEARCH GROUP (NRG)

Professor Azer Bestavros, Professor John Byers, Professor Mark Crovella, and Professor Abraham Matta
111 Cummington Mall, Boston, MA 02215
617-353-8919

The Networks Research Group (NRG) conducts basic research in networking within the Department of Computer Science at Boston University. Our research interests are broad, and encompass network measurement, the design of new network architectures and network protocols, the design and implementation of networked applications and systems, and network performance analysis. Application domains of interest range from cloud computing to social networks to peer-to-peer systems.

OPTIMIZATION AND MACHINE LEARNING LAB
Professor Francesco Orabona
The lab explores the research topic at the intersection between machine learning and optimization, with emphasis on adaptive and parameter-free methods.

NETWORK OPTIMIZATION AND CONTROL (NOC) LABORATORY

Professor Ioannis Paschalidis
8 St. Mary’s Street, Boston, MA 02215, PHO 415
617-353-0434

Research in the NOC Lab deals with fundamental problems in the fields of optimization, control, stochastic systems, and data science. Current topics of interest include:

• Robust learning, with applications in many areas, particularly in computational biology problems involving protein modeling and metabolic networks, and computational medicine where it is of interest to develop predictive and prescriptive analytics for a variety of diseases and health conditions.
• Reinforcement learning, with primary applications in autonomous systems, seeking to develop new, robust, bio-inspired control and navigation policies.
• Networks, focusing on optimization and control aspects, where networks are broadly defined to include computer, communication, and sensor networks, supply chains, transportation networks, cyber-physical systems, networks of autonomous agents, social networks, economic networks, and biological networks (e.g., protein interaction networks).
• Machine learning and AI, from statistical learning theory to applied topics such as deep learning with applications in Natural Language Processing (NLP), applications in computational neuroscience, and processing of a variety of health-related datasets.
• Optimization, including many variants such as inverse, robust, distributed, integer, and on-line, with applications in a variety of domains.

RELIABLE COMPUTING LABORATORY

Professor Mark Karpovsky and Professor Lev Levitin
8 St. Mary’s Street, Boston, MA 02215
617-353-4607

Members of the laboratory conduct research on a broad variety of topics, including the design of computer chips, efficient hardware testing at chip, board, and system levels; functional software testing, efficient signal processing algorithms, coding and decoding; latency, saturation, and critical phenomena in interconnection networks and deadlock prevention in computer networks.

SPIRA-LENBURG LAB

Professor Avrum Spira
One Boston Medical Center Place, Room E633, Boston, MA 02118
617-414-6980

Our focus is on translational research to better understand lung biology and disease using post-genomic technologies and computational tools. The long terms goals of our lab are two fold. On the one hand, we seek to leverage these approaches to improve the diagnosis, treatment, and prevention of lung disease. On the other hand, we seek to develop and apply new research approaches and to train physician-scientists and graduate students who can apply these tools in the setting of translational research.

VAJDA LABORATORY

Professor Sandor Vajda
44 Cummington St., Boston, MA 02215
617-353-4757

The focus of this laboratory is the development and application of computational tools for the analysis of protein structure and protein-ligand interactions. Some of the particular problems we currently study are the evaluation of binding free energy in protein-protein complexes, development of efficient docking algorithms, computational solvent mapping of proteins using molecular probes to identify the most favorable binding positions, method development for fragment-based drug design, construction of an enzyme binding site database, and improving the prediction of protein active sites by homology modeling.

VISUAL INFORMATION PROCESSING LABORATORY

Professor Janusz Konrad and Professor Prakash Ishwar
8 Saint Mary’s Street, Boston, MA 02215, Rooms 406, 446
617-353-1040

The VIP Laboratory belongs to the Information and Data Sciences (ISD) Group at the Department of Electrical and Computer Engineering at Boston University. Its three main objectives are sponsored research, student training, technology transfer, in the broad area of image, video and multimedia processing. It has been home to graduate and undergraduate students working on various aspects of visual information processing, such as visual surveillance, 3-D video or human-computer interfaces. The most recent research thrust in the VIP Laboratory is directed towards the development of next-generation user authentication methods to replace pass-codes, key-cards, RFID tags, etc. The focus is on gesture-based authentication where a user performs, for example, a unique arm swing, allowing the system to recognize him or her. The advantage of such authentication over today’s fingerprint or iris scans is that once such a scan is compromised it cannot be recovered, whereas a gesture can be changed.