Research focuses on the design and manufacture of smart material based actuators and sensors for innovative robotic systems. Particularly interested in how novel geometries, such as textile architectures and 3D printed structures, can enhance the capabilities of smart material systems. Research combines analytical modeling and experimental characterization to enhance technologies across diverse application fields including biomedical, transportation, aerospace, and consumer products.
Professor Hemati 's research program is aimed at gaining an improved understanding of the various mechanisms required to achieve reliable fluid flow sensing and control in the context of human-engineered systems. Broadly speaking, his research program encompasses the fields of modeling, optimization, and systems and control. Professor Hemati's ultimate goal is to innovate at the intersection of these disciplines, especially in the context of machine-fluid interaction. His near-term research is guided by applications in autonomous systems, energy, and the environment. The practical problems he plans to address in the near future are (1) real-time model-based control of agile flyers, (2) gait optimization and hydrodynamic perception for robotic swimmers, and (3) bio-inspired control and coordination in wind turbine arrays.
Research focuses on the use of wearable technology to improve human performance both in space and on Earth -- previously worked with NASA to develop advanced space suit technologies for future exploration missions. Specific interest in developing wearable smart systems using active materials, onboard sensing and computing systems, and advanced additive manufacturing techniques to address a variety of challenges in biomedical, military, athletic, commercial, and space scenarios. Work encompasses wearable technology, human factors design, textile engineering, aerospace engineering / bioastronautics, materials science, and biomedical device development.
The work will focus on engineering robotic tools for scalable, high-throughput, cellular resolution manipulation and interrogation of intact biological systems such as the brain. These technologies aim to automate difficult to perform assays used to study intact biological systems and generate large-scale quantitative datasets that is not possible with conventional methods. Along with their collaborators, these tools will be applied in novel scientific studies enabling new discoveries that enhance our understanding of complex biological systems and inform how their cellular components go awry in pathological diseased states.
Research at the intersection of control systems, robotics, and neuroscience. One theme focuses on decentralized control, where agents cooperatively control a physical system by using a combination of local measurements and communicated information. Theoretical work focuses on finding computationally tractable decentralized optimal control strategies. Experiments examine strategies that humans employ to solve cooperative control problems. Another theme focuses on control and estimation with uncertainty in time. Optimal control and filtering with time noise are studied, and human-robot interaction experiments examine the interplay between movement and time perception.
My research is focused on how to get data from the natural environment out of the field and into a form that can be used to make decisions. I make sensors and sensing systems that can be deployed statically, or dynamically on rovers or UAVs, which can be used to check anything from the methane off-gassing of a manure pool, water quality of agricultural runoffs to whether invasive species of fish are swimming up the Mississippi. Of particular interest to me are open biological problems, especially in agriculture, silviculture, and natural resource management, where sensing systems will allow for new data to answer old questions, such as in stream gauging, water and air quality assessment, and in regions drastically affected by climate change.
Professor McAlpine's research is focused on 3D printed bionic nanomaterials, which is the three-dimensional interweaving of biological and electronic nanomaterials using 3D printing. He has received a number of awards, most prominently an NIH Director’s New Innovator Award, a TR35 Young Innovator Award, an Air Force Young Investigator Award, an Intelligence Community Young Investigator Award, a DuPont Young Investigator Award, a DARPA Young Faculty Award, an American Asthma Foundation Early Excellence Award, a Graduate Student Mentoring Award, and an invitation to the National Academy of Engineering Frontiers in Engineering.
Numerical techniques for the simulation of complex physical systems, such as those arising in planning and control of robotic systems, in prototyping for advanced fabrication, and in dynamic virtual environments for training or computer animation. These applications give rise to challenging computational problems. Efficient, versatile, and robust solutions to such problems are sought via adaptive techniques and multiscale formulations. Current focus is on adaptively refined discretizations and on-line refinement criteria for problems in continuum dynamics.
Junaed's research focuses on making robots work safely and intuitively with people, so humans and robot can safely coexist. This means looking into improving a robot's perception about people, their intentions and/or actions, engaging in dialog, as well as the environment. Perceiving the world robustly, particularly under changing conditions is an open challenge, and consequently, his research interest naturally extends into multi-modal sensory perception. Making robots collaborate with humans through natural, intuitive means of communication in unstructured environments, particularly underwater, is a key objective of his research. His work on quantitative models of human-robot dialog is specifically geared towards improving safety in human-robot collaborations.
We leverage the unique properties of nanomaterials to create flexible electronic systems, addressing societal-scale challenges by working at the intersection of semiconductor device physics, materials science, and bioengineering. Our focus is on the materials, devices, and fabrication processes that will enable innovative advancements in biological sensors and green electronics. Flexible displays, electronic textiles, bio-inspired sensors, and wearable or implantable medical devices are a few applications that benefit from large-area form factors and mechanical flexibility, both of which are challenging to achieve with conventional wafer-based electronics. Instead, we employ low-cost and energy-efficient additive manufacturing methods such as solution-processing to fabricate electronic devices on flexible substrates.
Precision agriculture, agricultural robotics, remote sensing, machine vision, spectroscopy, hyperspectral imaging, machine learning and pattern recognition, high-throughput phenotyping. Applying advanced ideas of robotics, remote sensing, data mining and information technology into precision agriculture. The core techniques used include multispectral/hyperspectral imaging, spectroscopy, machine learning, geographic information system (GIS), digital mapping, biochemical sensing, etc.
Research focuses on neural recording, stimularion, and processing with three long term goals: 1) innovating drug-like electronics that treat diseases and provide better healthcare to patients, 2) developing signal processing circuts that make implants more intelligent for BCI and neutoprothetics, and 3) engineering emergent technologies that massively interact iwth the brain to aid basic neuroscience research.