Cognitive Wireless Systems Networks

Cognitive Wireless Systems Networks

Biao Chen Information theory, Wireless communications and networks, MIMO, Cognitive radio and networks, Wireless sensor networks, Distributed inference.

Makan Fardad Optimization and resource allocation.

M. Cenk Gursoy Wireless communication and networks, Energy efficient and green communications.

Pramod Varshney Wireless sensor networks, Distributed inference, Sensor management Multi-modality sensor networks.

Senem Velipasalar Wireless embedded smart cameras, Video sensor networks, Resource efficient algorithms for embedded platforms.

Intelligent Systems Including Data Mining & Network Analysis

Link creation, leader selection, and community detection in consensus/synchronization networks.

Data Mining, Social Network Dynamics, Evolutionary Optimization, Neural Networks, Anomaly Detection.

Multi-agent systems, Game theory, Swarm robotics, large scale learning and classification, Big data visualization.

Machine Learning, Security and Privacy in Social Networks.

Structure of social networks and communities, Identifying communities in networks, Predicting missing links, Applications. Interdisciplinary topics, including ecology, social sciences, and computational sustainability.

Text Mining and Social media mining.

Information fusion, Intelligent signal processing.

Wireless embedded smart cameras, mobile camera applications (including smart phones and UAVs), wearable sensors, visual surveillance, smart camera networks and resource efficient algorithms for embedded platforms.

Big Data Analytics, Social Media Mining, Large-Scale Information Networks, Social Computing; Information diffusion, influence, opinion formation, and means of evaluation in social media.

Artificial Intelligence, Machine Learning, Privacy, Multi-agent Systems

Faculty

Hardware Design and Computer Architecture

Hardware delay and power modeling and optimization; new methodologies and application for software development.

Dynamic power and thermal management for computer systems, High performance computing for cognitive applications, Neuromorphic computing.

Green and sustainable computing, energy generation/storage systems, and near-threshold computing for next generation devices.

Faculty

Energy and Signal Processing


Smart grid technology, renewable energy, sensors, VLSI RF circuits.

Power grid infrastructure, Intelligent sensing and Control architecture, Optimization methodology to meet load demand, Control in smart grid.

Renewable energy resources and planning, Intersection of network science theory and power system analysis; Power system operation with widespread deployment of Phasor Measurement Units.

Faculty

Artificial Intelligence and Data Sciences

Link creation, leader selection, and community detection in consensus/synchronization networks.

Data Mining, Social Network Dynamics, Evolutionary Optimization, Neural Networks, Anomaly Detection.

Multi-agent systems, Game theory, Swarm robotics, large scale learning and classification, Big data visualization.

Machine Learning, Security and Privacy in Social Networks.

Structure of social networks and communities, Identifying communities in networks, Predicting missing links, Applications. Interdisciplinary topics, including ecology, social sciences, and computational sustainability.

Text Mining and Social media mining.

Information fusion, Intelligent signal processing.

Wireless embedded smart cameras, mobile camera applications (including smart phones and UAVs), wearable sensors, visual surveillance, smart camera networks and resource efficient algorithms for embedded platforms.

Big Data Analytics, Social Media Mining, Large-Scale Information Networks, Social Computing; Information diffusion, influence, opinion formation, and means of evaluation in social media.

Artificial Intelligence, Machine Learning, Privacy, Multi-agent Systems

Faculty

Mathematical and Numerical Analysis

The properties and collective response to stimuli of biological and chemical systems often depend on physico-chemical and/or biological interactions that occur at disparate length and time scales. For instance, when a macromolecule (say a polymer with radius of gyration ~ nm) in solution is subjected to flow deformation, it can uncoil and orient in the flow direction. This causes the solution itself to behave differently in a macroscopic sense, e.g., flow aligned molecules can “slide” past each other more easily, hence the viscosity of the solution could decrease as flow deformation (shear rate) is increased. The purpose of Multiscale Modeling and Simulation (MMS) in this context is to device a self-consistent numerical simulation that would combine say a mesoscopic or “micro” simulator (e.g. Brownian Dynamics) that would “track” polymer configurations with a continuum-level or “macro” solver (e.g. Finite Element) for the conservation laws that represent the overall mass and momentum balance for the flowing system. The advantage of such an approach is that one can predict the additional stresses produced by the polymers without resorting to ad hoc closure approximations from the knowledge of polymer configurations obtained from the micro simulation. This information is then used in the overall force balance in the macro solver. The macro solver in turn updates the micro on the velocity distribution. Hence the method is self-consistent. Such numerical simulations together with sound theoretical framework for bridging the behavior of a system at one length or time scale to the dynamics at other scale is the key to understanding and predicting behavior of complex systems. Further, MMS is important to modern process and product design since it allows one to establish structure-processing-property relationships.

MMS can link different scales ranging from the quantum-mechanical, atomistic, molecular, mesoscopic and the continuum: see Figure above for a hierarchy of computational techniques. In the BMCE department Sureshkumar, Sangani and coworkers focus on developing efficient algorithms to explore the structure and dynamics of polymeric fluids, self-assembled phases of surfactants (micelles), bacterial biofilms, bubbly liquids and particulate/fiber/colloidal suspensions.

Representative publications

  1. Koppol, R. Sureshkumar & B. Khomami, Anomalous friction drag behavior of mixed kinematics flows of viscoelastic polymer solutions: a multiscale simulation approach, J. Fluid Mech., 631, 231-253 (2009).

Faculty

Biomaterials/Tissue Engineering

Biomaterials science is the physical and biological study of materials and their interaction with the biological environment. Tissue engineering uses of a combination of cells, biomaterials, and biochemical and biomechanical factors, individually or in combination, to repair or replace tissues or organs. The Biomedical and Chemical Engineering Department at Syracuse University has a strong and growing emphasis on biomaterials and tissue engineering, and many faculty in the department are members of the recently created Syracuse Biomaterials Institute.

Research in the department includes disciplinary projects in biomaterials and in tissue engineering, as well as interdisciplinary projects at the interface of these two exciting research areas. These projects are nearly universally motivated by the potential to improve human health and well-being. Examples of current biomaterials and tissue engineering projects in the department are listed below:

  • Active Cell Culture
  • Biomineralization
  • Control of bacterial biofilm formation
  • Fragmentation Mechanisms of Bacterial Biofilms of Physiological Relevance
  • Freeform Fabrication of Biomaterials
  • Cartilage Tissue Engineering
  • Micromechanics of Wear of Ultrahigh Molecular Weight Polyethylene (UHMWPE)
  • Redox electrochemistry and metallic biocompatibility
  • The reduction half-cell and protein adsorption and interaction
  • Control of cell viability with redox electrochemistry
  • Smart medical devices with electrochemical monitoring
  • Fretting Corrosion of Medical Alloys and Devices
  • Electrochemical Atomic Force Microscopy of Metallic Biomaterials
  • Passive oxide films and their behavior in the biological milieu
  • Performance testing of orthopedic, spinal, and cardiovascular devices
  • Micro- and nano-indentation of polymeric biomaterials and tissue engineered constructs
  • Development of novel two solution bone cements for vertebroplasty, kyphoplasty and joint replacement
  • Modeling polymerization processes, residual stresses and porosity development in bone cements
  • Atomic Force microscopy for biomaterials, proteins, and cells
  • Nanoindentation testing of biomaterials
  • Viscoelastic analysis of nanomechanics
  • Nanoparticle development
  • Failure analysis of retrieved total joint replacements
  • In-vitro testing of corrosion mechanisms in medical devices
  • Fatigue and fracture testing of medical devices

Faculty