We are an interdisciplinary research group of mechanical engineers, materials scientists, chemists, and physicists. Our mission is to advance the fundamental understanding of heat and charge transport in polymers, to create polymers with improved thermal conductivity and electrical insulation for better micro-electronic cooling, and to create others with improved thermal and electrical conductivity for better energy storage and conversion as well as biomedical temperature imaging, and higher solar cell efficiency.
The University of Massachusetts Center for Energy Efficiency and Renewable Energy (CEERE), founded in 1997, is a national leader in industrial energy efficiency and combined heat and power. Under the leadership of Research Assistant Professor Beka Kosanovic, we offer valuable training and research experience for graduate and undergraduate engineering students, while providing technical assistance at no cost to industrial, commercial and municipal clients. We have worked with more than 800 facilities around the northeast, helping them to identify and implement cost-effective measures that reduce their operating costs, environmental impacts and greenhouse gas emissions. Our research has informed energy policy and program development, and our graduates have gone on to found energy consulting companies and work for top energy efficiency programs.
Learn more at our website
Welcome to the Computational Nanomaterials Laboratory at UMass Amherst. We are a young research group lead by Ashwin Ramasubramaniam, Professor in Mechanical and Industrial Engineering and Adjunct Faculty in Chemical Engineering. Our group members come from diverse backgrounds, but our overarching interests lie in using computational methods to probe materials at length scales ranging from the nano- to macroscale. Our primary tools are density functional theory, empirical potential methods, and continuum mechanics-based models (with the occasional paper-and-pencil theory too). Some of our recent and past activities are...Read More
Research topics for the Control in Biomedical Systems Lab include:
- Math models of the human thyroid.
- Optimal dosing of radioactive iodine in Graves’ disease.
- Pharmacokinetic/pharmacodynamics model of erythropoiesis.
- Design of anemia management protocols in end-stage kidney disease.
Diseases prediction and prevention analysis is a challenging mathematical problem because it is the outcome of a complex dynamical system that consists of interactions between multiple factors related to epidemiological, social, economical, environmental, population mobility, demographics, and individual behavioral and lifestyle. Disease prevention and intervention decisions, and subsequently resource allocation, at the national and global levels thus need to be based on evaluations of the impact of alternative decisions under this complex dynamical context. Our lab works on development of new methodologies and computational models for simulating the dynamics of disease incidence and spread for purposes of disease prediction, prevention, and control.
Our laboratory conducts research in the following areas
- topological network design
- facility layout and location
- stochastic network design and analysis
- Steiner minimal Trees in 3-dimensions
- state dependent queueing network analysis and finite buffer queueing network models
Real world applications of our research include
- the design and layout of manufacturing plants, health care facilities, and many other production and service oriented systems
- analysis of routing in large transportation networks
- modeling and evaluation of building and vehicular evacuation in case of emergencies
The Center for e-Design is an NSF supported Industry/University Cooperative Research Center involving a number of high technology companies such as Raytheon, PTC, Vistagy, and ANSYS, as well as several universities, including Virginia Tech, University of Central Florida, Carnegie Mellon University, University of Buffalo, Brigham Young University, and Wayne State University. The mission of the Center is to serve as a nucleus of excellence for the creation and dissemination of a systematic body of knowledge in intelligent e-design and product realization. Research at UMass-Amherst is focused on development of new design paradigms and processes, with particular emphasis on engineering knowledge modeling and development of ontologies to support e-Design.
We work on various aspects of Fluid-Structure Interactions, Nonlinear Dynamics, and Biomimetics. View current research projects here.
The Arbella Insurance Human Performance Laboratory (HPL) is a multi-disciplinary research facility at the University of Massachusetts in Amherst, based in the Department of Mechanical and Industrial Engineering. Since the HPL’s founding in the 1980s, the lab’s research has focused on driver behavior and driver safety, and this research has contributed to the understanding of driving, and the identification of factors that:
- increase the crash risk of novice and older drivers
- impact the effectiveness of traffic signs, signals, and pavement markings
- improve the interface of in-vehicle equipment such as forward collision warning systems, back over collision warning systems, and music retrieval systems, and
- influence drivers’ understanding of advanced parking management systems, advanced traveler information systems, and dynamic message signs
The HPL has created PC-based programs to train drivers to anticipate potential roadway hazards, and to maintain their attention on the forward roadway. The lab’s driving research is conducted using two state-of-the-art driving simulators, and simulator software, and equipment such as eye trackers, head trackers, and portable camera systems that can be used both in the lab and in the field.
The Human Robot Systems (HRS) Laboratory is part of the Department of Mechanical and Industrial Engineering at the University of Massachusetts Amherst.
Our mission is to advance how humans and robots learn to guide the physical interactive behavior of one another. To achieve this, our research aims to:
(1) develop new methods of describing human motor behavior that are compatible for robot control,
(2) understand and improve how humans learn models of robot behavior, and
(2) develop robot controllers that are compatible for human-robot physical collaboration.
This highly interdisciplinary research lies at the intersection of robotics, dynamics, controls, human neuroscience, and biomechanics.
Engineering, Environment, and Policy
The start of Intelligent Sensing Lab includes three key areas:
1. Machine design (flexible electronics printer and medical device);
2. Control (Sensing, metrology, pattern analysis, feedback control)
3. Machine intelligence (Machine vision, image processing, deep learning)
Interdisciplinary interface engineering, such as：
Our laboratory studies the interaction between fluid flow and biology, by integrating fluid dynamic engineering, cellular and molecular biology. Body fluids or biofluids, such as blood, lymph, and cerebrospinal fluid continuously interact with cells in the body eliciting biochemical and physical responses. Our research seeks to elucidate the fluid flow characteristics and fluid flow-dependent biomolecular pathways relevant in medicine.
Our research applies and integrates fundamental engineering principles, such as manufacturing, biomechanics, materials science, and micro/nanoengineering, to understand and harness the mechanobiology of stem cells for modeling currently incurable human diseases and for applications in regenerative medicine. Current research interests include:
- Stem cell bioengineering
- System mechanobiology
- Active biomaterials
- Tissue biomechanics
Lee Nano-engineering Lab at UMass Amherst focuses on the rational design of various functional materials including metamaterials with emphasis on energy, defense, and bio applications through 2D/3D nano-structuring of polymers, metals, ceramics, and more. Our quest is driven by the acknowledgement that future material innovation will rely on the development of novel materials based on tailored thermal, mechanical, and photonic responses of materials.
Associated Faculty: Jae-Hwang Lee
Materials processing, the basis of materials engineering, is the relationship among structure, properties, and processing: any one determines the other two. Our research is on the design and control of the processes that lead to the required structure or properties in materials. We use mathematical modeling to identify and quantify the effect of different process parameters on the structure and properties of materials, and measure the thermophysical properties that are used in the models...Read More
In the MRRL our research focuses on developing human-centered robotic technologies for augmenting human gait and balance and exploring physical human-machine interfaces. The 1000 sq. ft. of lab space is dedicated to the fabrication and evaluation of physically interactive mechatronic systems.
Power is fundamental to the existence of modern society. Without power, you couldn't be reading this web page, for example. However, the environmental consequences of our current methods of power generation are unsustainable. Our lab seeks to improve the performance and reduce the emissions of modern power systems by better understanding of the fuel/air mixing.
The research of the Multiphase Flow Simulation Lab include sprays, cavitation, and other multiphase flows. These studies combine the intellectual challenge of multiple phenomena interacting at multiple scales, and provide the long-term benefits to society of cleaner and more efficient power. For diesel and jet engines, the spray quality has a tremendous impact on the emissions. We also simulate sprays in rockets, where we have great difficulty predicting and controlling the combustion process.
Multiscale Materials and Manufacturing Laboratory works at the interface of materials science and advanced manufacturing. We are particularly interested in understanding the fundamental microstructure-property-processing relationships in advanced materials and integrating control over materials on different length scales (atomic structure, microstructure, architecture) through materials processing and additive manufacturing (or 3D printing), to eventually arrive at optimized, multi-functional engineering components.
Nanomaterials are materials with at least one of their three dimensions limited to nanometer, that is, a scale that quantum effects emerge. Two-dimensional (2D) materials is a class of nanomaterials with outstanding electrical, mechanical, chemical, and bio-transducing properties. Using methods based on chemical vapor deposition, 2D materials can be prepared in large scale (~ m) and high quality with tunable strength, transparency, disorder density, and electron transport properties.
Development of High-Performance 2D-Bio Interface Technologies
Interfacing biosystems with 2D materials by developing 2D-enabled biosensing devices and systems provides significant opportunities for interrogating the life activities and biological/physiological properties (pH, electrostatic potential, structure & function, concentration, etc.) of biosystems with unprecedented sensitivity, spatiotemporal resolution, and efficiency in power, size, cost, and time.
Translation of 2D-Based Biosensors
Device structures based on 2D materials can be translated into precise, point-of-use, portable (PPP) biosensing tools for healthcare, screening/diagnosis of diseases such as HIV and cancer, or even environmental monitoring. Another application of 2D-based devices/systems is implantable arrays of graphene microelectrodes for chronic monitoring of life activities/effects.
The Nanoscale Interfaces, Transport, and Energy (NITE) Laboratory evaluates materials for energy transduction applications via direct, in-situ observation of local responses along critical heterophase interfaces in the operating regime.
The Non-Newtownian Fluid Dynamics Lab is actively involved in research in a number of different areas including: the dynamics of complex fluids; laminar and turbulent drag redution; the development and utilization of superhydrophobic surfaces; shear and extensional rheology of a number of different complex fluids; non-Newtonian fluid dynamics; microfluidics; nanotechnology; non-isothermal flows; hydrodynamic stability; and polymer processing. On our lab website, you will find a number of short examples of active research along with links to the corresponding publications and graduate students responsible for the work.
Disease — a threat that is common to all human beings across the globe and across generations. Prediction of diseases is a tough problem because it is the outcome of a complex dynamical system that consists of interactions between multiple factors related to epidemiological, social, economical, environmental, population mobility, demographical, and individual behavioral and lifestyle. Disease prevention and intervention decisions, and subsequently resource allocation, at the national and global levels thus need to be based on evaluations of the impact of alternative decisions under this complex dynamical context. Our lab works on development of new methodologies and computational models for simulating the dynamics of disease incidence and spread for purposes of disease prediction, prevention, and control.
Our primary research interests are broadly in operations research applied to healthcare delivery. Some examples: I've worked on planning and scheduling of surgical suites; designing primary care physician panels to maximize timeliness and patient-physician continuity; and optimization of prostate cancer screening decisions. We have also recently begun looking at improving emergency room operations. In addressing these problems, we collaborate with a diverse set of...Read More
The Process Automation Laboratory at the University of Massachusetts Amherst focuses on development of general solutions that can cope with process uncertainty. Areas of concentration are Simulation Tuning, Fault Diagnosis and Manufacturing Automation. Among the products of this laboratory are the pattern classifying fault diagnostic method Multi-Valued Influence Matrix (MVIM) and the Structure-Based Connectionist Network (SBCN) for fault diagnosis of helicopter gearboxes. The MVIM method has been applied to tool breakage detection in turning (in collaboration with GE Corporate Research) as well as fault diagnosis of helicopter gearboxes (in collaboration with NASA Lewis and Sikorsky Aircraft). This laboratory has also contributed to manufacturing automation....Read More
Our group studies the interaction of non-ionizing energy and biology at multiscale resolution, from cells through organ systems. Computer simulations are used to model biological response evoked upon exposure to energy and to design energy parameters that improve the specificity of the desired treatment effect. We develop novel medical devices for energy delivery in vitro and in vivo, allowing identification of signaling pathways and cellular activity that is altered or upregulated upon energy-based treatment. Our techniques allow the targeted modulation of barrier function in the tissue microenvironment (cell membrane, stroma and blood vessels), creating new platforms for the study of cancer and other diseases. The knowledge gained from our experiments has applications in tumor ablation, drug delivery, immunotherapy and tissue engineering. We emphasize rapid translation of our findings to the clinic through collaboration and involving physicians and other key stakeholders at all stages of our research.
"Supply Chain Management takes a holistic approach towards managing the flow of material and information throughout the supply network - including different tiers of suppliers, manufacturers, warehouses and stores - in order to maximize system-wide profits and create customer value."
The Theoretical and Computational Fluid Dynamics Laboratory is dedicated to the development of practical and generally applicable tools for the prediction of complex and often chaotic fluid flows.
Research at the Lab is focused on the entire CFD food chain from hardware and software to algorithms and turbulence models. Understanding in detail how the computational, mathematical, and physical problems of CFD interact is the key to designing lasting CFD solutions.
To study the details of a turbulent flow, it is sometimes more informative to accurately simulate the flow with a computer than to try to observe it in the laboratory. Direct numerical simulation involves the numerical solution of the equations that govern fluid flows. It is a research tool that provides us with an extremely detailed description of the flow field. Our lab uses these techniques to study various flows...Read More
The University of Massachusetts Wind Energy Center is a leading institution in wind energy engineering nationally and internationally. Since 1972 the Center has worked diligently to maintain and enhance its important wind energy education programs and research activities. This website will familiarize you with the breadth and depth of that work.
We invite you to learn and grow with us in this very exciting time for wind energy. The stakes have never been higher.