Bernardo is a PhD student in mechanical engineering whose research examines the synthesis of robust strategies for grasping and dexterous manipulation. Specifically, he is examining the problem of caging, a geometric property by which a set of fingers manipulate an object by trapping it rather than immobilizing it. He has developed an explicit optimization approach to formulate the caging condition as a convex mixed-integer optimization problem. This was the first of its kind, since caging had previously been approached as either a topological or computational geometry problem. More recently, he has extended the formulation to synthesizing grasping strategies with certificates of correctness, a problem that is of high interest today both in academia and industry. He uses MATLAB’s Robotics Toolbox, Optimization Toolbox, and Deep Learning Toolbox as the main prototyping interface. In addition, his work has resulted in several tools that have been made open to the robotics and MathWorks communities, including ABB ROS Interface, Contact-TrajectoryOptimization Models, and Certified Grasping Toolbox. Bernando earned a BSc in electronics engineering from Universidad Simón Bolívar, Venezuela
Bernardo Aceituno - CabezaMechanical Engineering https://engineering.mit.edu/fellow/bernardo-aceituno-cabeza/
Shashank is a PhD student in mechanical engineering whose research primarily focuses on the development of reduced-order, rate-dependent methods for a variety of granular intrusion problems, such as meteorite impacts and animal and vehicular locomotion in sands and deserts (a field referred to as terramechanics). He uses large-scale, detailed numerical simulations to understand the physics of such scenarios, which in turn allows him to develop robust reduced-order models that can be run in real time. He uses MATLAB for various purposes in his research, most importantly for the implementation of reduced-order models for granular intrusion, allowing for the real-time simulation of diverse intrusion scenarios with different system properties and intruder shapes. Shashank earned a BTech in mechanical engineering fromIITGandhinagar, India and an SM in mechanical engineering from MIT.He also worked as a scientist at the Defense Research and Development Organization, India before joining MIT
Shashank AgarwalMechanical Engineering https://engineering.mit.edu/fellow/shashank-agarwal/
Mohammad is a PhD student in civil and environmental engineering whose research is focused on explaining and predicting biodiversity changes using mathematical models. Specifically, his goal is to provide closed-form solutions using computational methods in order to skip the impossible task of simulating all possible parameter values and combinations and to establish rigorous and testable estimates about the probability of persistence of species. He is developing his own code and integrating libraries from MATLAB with the goal of generating a computational package that will allow researchers to work with different ecological models, derive the range of parameter values (or combinations of parameter values) compatible with the persistence of a given species in an ecological system, and estimate the probabilities (or risks) of species extinctions or species invasions. Mohammad earned a BS in mathematics and a BS in electrical engineering from Rensselaer Polytechnic Institute and an SM in civil and environmental engineering, an SM in electrical engineering and computer science, and an SM in computation for design and optimization from MIT.
Mohammad AlAdwaniCivil and Environmental Engineering https://engineering.mit.edu/fellow/mohammad-aladwani/
Nicolas is a PhD student in electrical engineering and computer science whose research focuses on medical imaging technology. He is trying to solve challenging MRI problems by creating and distributing the hardware and computational tools needed for simultaneous optimization of coil geometries, encoding field patterns, and received-signal reconstruction algorithms. He has observed that the steps, or modules, that make up most MRI sequences often have conflicting patient-specific field pattern requirements. Nicolas developed a general MATLAB-based framework for use at scan time that optimizes the field patterns for each sequence module. The framework reads patient rapid-scan data from the imager, exploits the coil pre-characterization and convex formulations to efficiently compute sets of sequence-module optimized coil currents, and then transfers the coil currents sets, along with triggering conditions, to the coil driver array. Nicolas earned an SB in electrical engineering from MIT.
Nicolas ArangoElectrical Engineering and Computer Science https://engineering.mit.edu/fellow/nicolas-arango/
A PhD student in electrical engineering and computer science, Roberto is a member of the Organic and Nanostructured Electronics Lab. He uses MATLAB’s versatile Partial Differential Equation (PDE), Global Optimization, and ParallelComputingToolboxes to solve, model, and fit the group’s experimental data sets on carrier recombination and diffusion in semiconductors for optoelectronic applications. Leveraging the PDE Toolbox, his most recent work, “AccurateDetermination of Semiconductor Diffusion Coefficient Using Confocal Microscopy,” explores common pitfalls in modeling charge carrier diffusion in semiconductors that were elucidated by simulations carried out using the PDE toolbox. He is now focused on modeling semiconductors for solar applications that present anisotropic diffusion and complex boundaries using the PDE Toolbox coupled with the Parallel Computing and the Global Optimization Toolboxes to optimize multi-variable minimization problems. The Parallel Computing Toolbox has been essential in bringing the computation times down to manageable time frames, allowing him to explore multiple schemes that could represent the complex carrier diffusion anisotropy that is observed. He earned an SB in electrical engineering and physics fromMIT.
Roberto BrenesElectrical Engineering and Computer Science https://engineering.mit.edu/fellow/roberto-brenes/
Katherine is a master’s student in aeronautical and astronautical engineering and member of the Engineering SystemsLaboratory. A longtime MATLAB and Simulink user, her current research involves population modeling and simulation of pedestrian activity through transit environments. She is implementing agent-based modeling and simulation in order to capture the emergent phenomena of population groups moving across complex sites, both here on Earth and on Mars. She has used MATLAB to numerically simulate pedestrian flows in hallways using a social-force model and is currently developing a Java-based integrated, flexible platform to simulate agent behavior across multiple agent pools and simulation scenarios. Katherine earned a BS in aerospace engineering fromUniversity of Illinois.
Katherine CarrollAeronautics and Astronautics https://engineering.mit.edu/fellow/katherine-carroll/
Cécile is a PhD student in materials science and engineering. Her research is focused on the creation of new methods for manufacturing high-performance polymer and composite materials in a rapid, energy-efficient manner. Specifically, she studies interfacial polymerization (IP), a process by which a polymer is formed at the interface between two immiscible liquids (often water and an organic solvent), each containing one type of reactive species (initiator or monomer). She uses MATLAB to enable experimental data analysis and prediction of IP-based process kinetics, as well as future perspective on the integration of MATLAB algorithms in manufacturing and 3D printing. Cécile earned an MS in materials science and engineering from MINES ParisTech, France.
Cécile ChazotMaterials Science and Engineering https://engineering.mit.edu/fellow/cecile-chazot/
Ximo is a PhD student in aeronautics and astronautics conducting research at the intersection of numerical modeling and physics of nanoscale engineering devices. A frequent MATLAB user, he is working on a problem related to the numerical analysis of the shapes of small liquid menisci stressed under very high electric fields to evaporate ions. As these ions fly away, they produce thrust, hence a rocket can be constructed under this principle. This is difficult to analyze since the scales change dramatically from millimeters to nanometers, which creates a set of numerical challenges as equations describing the balance of electric, surface tension, and hydraulic stresses, including thermal loads that need to be solved simultaneously on meshes with very strong dimensional gradients. He earned a BS in aeronautics and astronautics and physics from Universitat Politècnica de Catalunya, Spain
Ximo Gallud CidonchaAeronautics and Astronautics https://engineering.mit.edu/fellow/ximo-gallud-cidoncha/
Clement is a PhD student in aeronautics and astronautics working on aviation automation problems at the MITInternational Center for Air Transportation. His PhD topic involves investigating high-level aviation automation in dynamic and stochastically varying environments. In particular, he is focusing on automated situation awareness and decision making with regards to airborne trajectory prediction. He is investigating data analytics approaches, usingMATLAB tools, for mining large sets of aircraft surveillance (ADS-B) data to infer aircraft behavior in structured and unstructured airspaces around airports. Clement earned a BS in mechanical and aerospace engineering from Princeton University and an SM in aeronautics and astronautics from MIT.
Li ClementAeronautics and Astronautics https://engineering.mit.edu/fellow/li-clement/
Logan is a PhD student in electrical engineering and computer science. His research focuses on intersecting areas in traditional machine learning, deep learning, and statistical analysis. He is particularly interested in making machine learning more robust and reliable and in making AI more human aligned. Much of his research focuses on adversarial examples or imperceptibly changed inputs that can induce worst-case behavior in machine learning systems. He recently completed a statistical analysis with the help of MATLAB’s interface and toolboxes. In the future, he plans to use the simulation capabilities of MathWorks software (e.g., with Unreal Engine) to complete his domain adaptation and transfer learning research, and the Signal Processing Toolbox to better understand non-robust features. Logan earned an SB in computer science from MIT.
Logan EngstromElectrical Engineering and Computer Science https://engineering.mit.edu/fellow/logan-engstrom/
Hannah is a PhD student in mechanical engineering whose research is centered on the fundamental design, optimization, and device integration of dynamically reconfigurable micro-scale fluid droplet morphologies for biomedical sensing and imaging. Being able to determine whether bacteria are alive or dead has important implications for rapid detection of pathogenic bacteria presence and the quantification of antibiotic effectiveness. This can be accomplished through sensing optical changes.Hannah is advancing sensing concepts that are based on employing micro-scale, bi-phase emulsion droplets for the optical quantification of bacteria motion to readily distinguish between live and dead bacteria. MATLAB is critical for in-situ assessment of the droplets’ optical characteristics and for computational deduction of the underlying bacteria dynamics. If successful, her approach, which involves efficient data capture and analysis enabled by MATLAB, will address drawbacks in sensitivity, delay times, and cost of bacterial culture and polymerase chain reaction approaches, given that her detection strategy is rapid and the required fluid morphologies are relatively inexpensive to fabricate. Hannah earned a BS in mechanical engineering from Schreyer Honors College at Pennsylvania State University.
Hannah FeldsteinMechanical Engineering https://engineering.mit.edu/fellow/hannah-feldstein/
Baoliang is a PhD student in mechanical engineering whose research focuses on developing novel label-free microscopy techniques for biological imaging and material inspection. He recently developed a polarization interference microscopy called Quantitative Polarization Interference Microscopy (QPIM). This novel optical imaging technique realized single-shot quantitative polarization imaging, which can capture and analyze the high-speed dynamics happened in anisotropic samples. With QPIM, he can record the transient retardance of the changing dynamics occurring in a liquid crystal device. He used MATLAB to build a comprehensive polarization parameter retrieval algorithm for QPIM that allows the processing and analyzing of the recorded images. Baoliang earned a BS in information engineering (optoelectronics)from Zhejiang University, China and an SM in mechanical engineering from MIT.
Baoliang GeMechanical Engineering https://engineering.mit.edu/fellow/baoliang-ge/
Fiona is a PhD student mechanical engineering. Her research Global Engineering and Research (GEAR) Lab focuses on designing low-cost, solar-powered drip irrigation systems for small farms in the Middle East, North Africa, and East Africa. Her goal is to improve and expand the optimization design tool for drip irrigation systems, using a modular design tool that facilitates rapid iterations and improvements. In order to identify further cost-saving design configurations, she is working on co-optimizing the system operation scheme with the design of the drip system components. She is using MATLAB to design and test the behavior of an adaptive pump controller that ensures the drip network and pump operating points are optimally paired for minimal power usage throughout the irrigation season. Fiona earned an SB andSM in mechanical engineering from MIT.
Fiona GrantMechanical Engineering https://engineering.mit.edu/fellow/fiona-grant/
Daisy is a PhD student in electrical engineering and computer science working in the Electromechanical Systems Group.Her research is focused on the signal processing and analysis required to create new systems for the automation of energy conservation and for providing actionable insight into the operation of an electrical system and its individual loads. MATLAB was essential to her understanding of machine learning concepts.Her work usesphysics-informed machine learning techniques to identify shipboard loads from an aggregate power stream, track degrading equipment health over time, and detect faults that waste energy.Her work has enabled the expansion of the energy monitoring system to more marine vessels and sites and she will be using MATLAB to analyze this new data.Daisy earned a BS in electrical engineering from University of Hawaii, Manoa.
Daisy GreenElectrical Engineering and Computer Science https://engineering.mit.edu/fellow/daisy-green/
Abhinav is a PhD student in mechanical engineering and computation who is developing state-of-the-art algorithms and methodologies for uncertainty quantification, Bayesian learning, deep learning, and numerical methods for various ocean applications. His research in the past years has focused on the problem of sustainable fisheries management inIndia. Due to the high-dimensional nature of ocean modeling and the operational requirements of making ocean predictions in real time, legacy codes written in programming languages such as Fortran are used. While they provide computational speed, they are notoriously difficult to code, edit, and debug. Acting as a bridge, Abhinav is usingMATLAB as a sandbox to develop and test new theories and algorithms before implementing them in the legacy ocean models. He earned a BS and MS in mechanical engineering, both from Indian Institute of Technology Kanpur, India.
Abhinav GuptaMechanical Engineering https://engineering.mit.edu/fellow/abhinav-gupta/
R’mani is a PhD student in electrical engineering and computer science. She uses MATLAB to create figures such as confusion matrices, and to perform computations on an emerging area in the speech field that revolves around measuring health-related biomarkers from speech. She plans to use the Statistics and Machine Learning Toolbox to automatically detect cognitive impairment from speech. R’mani earned a BS in electrical engineering from Yale University.
R’mani HaulcyElectrical Engineering and Computer Science https://engineering.mit.edu/fellow/rmani-haulcy/
Justin is a PhD student in electrical engineering and computer science and a member of the Spintronic Material and Device Group. His research focuses on the theoretical understanding and experimental realization of spintronics.MATLAB has played a significant role in his research, ranging from experimental measurement, data analysis, and visualization to theoretical calculation of electronic bands and theoretical modeling of magnetic dynamics. With the help of the Instrument Control Toolbox, he uses MATLAB to control the measurement instruments and acquire data throughGPIB Interface for Instrument Control. MATLAB also allows him to process and plot the data while measurements are ongoing, providing quick feedback of measurement setup. Moreover, the function overloading in MATLAB enables him to use the same program for handling various instruments with the same functionality.Using MATLAB programs, he was able to theoretically predict coupled magnetic resonance spectrum, which led to subsequent experimental discoveries.He is currently using MATLAB programs for analyzing micromagnetic simulations with GPU acceleration and is incorporating the photon coupling effect into micromagnetics. Justin earned a BS in electrical engineering and a BS in physics, both from National Taiwan University, Taiwan.
Justin HouElectrical Engineering and Computer Science https://engineering.mit.edu/fellow/justin-hou/
Ifueko is a PhD student in electrical engineering and computers cience. Her research focuses on how computer scientistscan utilize the power of multi-agent collaboration to coordinate swarms of drones completing classic computer vision tasks with extremely high speed and accuracy. The goal of this work is to develop innovative deep-learning models supported by a backbone of drone swarm perception to provide real-time, deep-learning capabilities for autonomous systems. This approach aims to show that leveraging deep learning with multiple low-cost sensors can achieve on-par or improved accuracy compared to expensive sensors.During her first research project at MIT, she was able to learn about many of MATLAB’s custom features for deep learning, which allow for model interoperability and co-execution between different deep learning frameworks. This has enabled her to understand and convert a custom MATLAB deep-learning model that supported sparsely interconnected networks to Pytorch. This facilitated the sharing of weights and the leveraging of favorable training and evaluation conditions within the two frameworks.She earned a BS in computer science and an MS in electrical engineering from Stanford University.
Ifueko Nosakhare IgbinedionElectrical Engineering and Computer Science https://engineering.mit.edu/fellow/ifueko-nosakhare-igbinedion/
Yoonho is a PhD student in mechanical engineering. He developed a submillimeter-scale, soft-bodied continuum robot (a type of slender, thread-like robot) capable of slithering through highly complex and constrained environments, such as the narrow and tortuous vasculature of the human brain.Based on this technology, he is developing a telerobotic neurointerventional platform to enable robotic applications to endovascular neurosurgery and stroke treatments. He uses MATLAB for simulation and quantitative prediction of the behavior of the soft continuum robot, and usesMATLABand Simulink to design the interface for real-time control and teleoperation of the robot arm to remotely control the soft continuum robot.He is also developing data-driven control strategies for autonomous navigation of the soft continuum robots by applying emerging techniques of machine learning. In collaborations with clinicians at HarvardUniversity and Massachusetts General Hospital, he plans to conduct translational studies and preclinical testing to evaluate the safety and efficacy of the developed platform for robotic endovascular neurosurgery. Yoonho earned a BS in mechanical and aerospace engineering from Seoul National University, Korea.
Yoonho KimElectrical Engineering and Computer Science https://engineering.mit.edu/fellow/yoonho-kim/
Abinash is a PhD student in the Department of Materials Science and Engineering. His research involves atomic-scale characterization of materials using scanning transmission electron microscopy (STEM). He focuses on two aspects of electron microscopy: developing new tools for acquiring high quality data; and extracting local chemical and structural information in materials, using various statistical tools. With the discovery of aberration correctors for electron microscopes, acquiring images of various materials at anatomic scale has become common, yet extracting quantitative information from such images is still challenging. Abinash has implemented a revolving STEM based approach to simultaneously acquired images to correct drift and scan distortions in the musing MATLAB programs.Further, he uses correlation analysis to determine various inhomogeneities, like chemical and structural ordering, which drive the unique spatial pattern in polarization leading to the relaxor behavior. He also applies learning tools like convolutional neural networks for obtaining information, like sample mistilt and thickness, from position averaged convergent beam electron diffraction (PACBED) patterns.He also uses MATLAB to automate the process of generation of simulated PACBED patterns and applied image augmentations for neural networks. Abinash earned a BS and MS in materials at Indian Institute of Science, India.
Abinash KumarMaterials Science and Engineering https://engineering.mit.edu/fellow/abinash-kumar/
Eric is a PhD student in biological engineering where he focuses on the bio-directed synthesis and assembly of advanced materials for the direct air capture of carbon dioxide and its conversion to products with a goal of off-setting the net addition of carbon dioxide to the atmosphere. He uses MATLAB to monitor flow data to better understand the fraction of carbon dioxide converted into products, and a custom MATLAB script to calculate and visualize the products generated using the materials he designed. Eric earned a BSE and MS in biomedical engineering from Arizona StateUniversity.
Eric LehnhardtBiological Engineering https://engineering.mit.edu/fellow/eric-lehnhardt/
Wei is a PhD student in electrical engineering and computer science who uses microfluidic technology to study an important but often neglected player of neurodegenerative disease, the blood-brain-barrier (BBB). She uses engineered microfluidic tissue culture devices to recapitulate the BBB microarchitecture in vivo with an approach normally called organ-on-a-chip (OOC). OOC platforms are microfluidic cell culture chips that simulate the activities, mechanics and physiological response of major functional units of human organs. In order to achieve live time-lapse fluorescence microscopy of these extremely fragile cells during the BBB vasculogenesis process, Wei used MATLAB to develop a rapid and robust camera and microscope control strategy which minimizes phototoxicity during the imaging. She has also usedMATLAB SimBiology to understand the temporal dynamics of different forms of vascular endothelial growth factor reactions with the extracellular matrix as they produce different BBB capillary morphogenesis effects. Wei earned a BS in engineering at Tsinghua University, China.
Wei LiaoElectrical Engineering and Computer Science https://engineering.mit.edu/fellow/wei-liao/
Miles is a PhD student in aeronautics and astronautics focusing on space traffic management, space situational awareness, and space sustainability. His research draws on a variety of methods and disciplines to ensure that we, and those who come after us, will be able to continue to enjoy benefits derived from space. His PhD research centers on the development of al ow Earth orbit slotting system using flower constellation theory to coordinate between large numbers of satellites controlled by different operators. MATLAB is helping to enable this work and serves as a “lingua franca”across a multidisciplinary team of collaborators with different backgrounds. He earned a BA in physics and government from Claremont McKenna College and an SM in technology and policy and an SM in aeronautics and astronautics from MIT.
Miles LifsonAeronautics and Astronautics https://engineering.mit.edu/fellow/miles-lifson/
Catherine is a PhD student in electrical engineering and computer science. Her research lies at the intersection of classical signal processing and quantum physics. Being theoretical in nature, her research requires the use of MATLAB tools for simulation and theoretical experimentation, varying parameters and other aspects of a theory to gain insight into the theoretical results. For example, she and her collaborators produced code that takes a non-optimal ROC curve and generates the optimal Neyman-Pearson ROC curve with minimal knowledge of the underlying data. More recently, they became intrigued by the application of generalized sampling techniques, including sigma-delta quantization, to the problem of quantum state estimation. She also uses the SIMULINK Sigma-Delta Toolbox, designing and running experiments using the platform. Catherine earned an SB in electrical engineering and physics from MIT.
Catherine MedlockElectrical Engineering and Computer Science https://engineering.mit.edu/fellow/catherine-medlock/
Jerry is a PhD student in mechanical engineering whose research focuses on system dynamics and applications control in robotics. In particular, he focuses on lifting linearization techniques for nonlinear dynamical systems to be used for realtime, model predictive control. He has used MATLAB to run simulations and experiment with configurations. Jerry has also served as a TA for the subject Introduction to Robotics, taking MATLAB packages and toolboxes that he uses in his own research and transferring that knowledge to laboratory assignments and projects for undergraduates. In the wake of Covid-19, he recently converted in-class laboratories to completely virtual ones, made possible largely due to the abundant toolboxes and packages of MATLAB.Jerry earned a BS in mechanical engineering from University of California at San Diego.
Jerry NgMechanical Engineering https://engineering.mit.edu/fellow/jerry-ng/
Tam is a PhD student in chemical engineering whose research applies systems engineering to solving problems in pharmaceutical manufacturing, with a focus on continuous processes for their potential to decrease costs and increase flexibility. She has constructed a novel kinetic model, written entirely with MATLAB code, for the manufacturing of the most important class of gene therapy products via triple transfection of mammalian cells. She has designed optimal model-based experiments necessary to estimate the model parameters, and she is using the model to design an optimal operating configuration for viral vector production in a bioreactor. Her goal is to build a complete and controlled continuous platform for gene therapy manufacturing. Tam earned a BS in chemical engineering from University ofMassachusetts at Amherst.
Tam NguyenChemical Engineering https://engineering.mit.edu/fellow/tam-nguyen/
Max is a postdoctoral associate at MIT’s Institute of Medical Engineering Science and a member of the Edelman Lab(Harvard-MIT Biomedical Engineering Center). His research is focused on advancing computational models representing diseased coronary arteries to accurately reflect the specific biomechanics of a given patient. Models of coronary arteries have previously been developed, but lack the detailed input data necessary to robustly characterize and represent the systems and to confidently address important questions. Max’s goal is to overcome existing barriers by employing a priori knowledge of arterial geometry and image acquisition procedure, as well as strategic engineering assumptions, toe xtract greater geometric and constitutive information from optical coherence tomography imaging, the highest-resolution modality available clinically. He has used the MATLAB programming environment to build, execute, and analyze his central algorithms, allowing him to construct models from in vivo geometry and morphology ascertained with high resolution. Max earned an MSE in biomedical engineering and a BSE in mechanical engineering, both from the University of Michigan and a PhD in mechanical engineering from MIT.
Max OlenderMechanical Engineering https://engineering.mit.edu/fellow/max-olender/
Chelsea is a PhD student in aeronautics and astronautics. Her research centers on the simulation on similar and non-similar hypersonic boundary layers with temperature-varying properties.She uses MATLAB to efficiently and robustly model the evolution of hypersonic boundary layers, develop heuristics for the impact of various flow conditions such as free stream Mach number, free stream enthalpy, and surface boundary conditions (temperature or heat transfer distribution) on the behaviors of hypersonic boundary layers. She earned a BS in mechanical engineering from Stanford University and an SM in aeronautics and astronautics from MIT.
Chelsea OnyeadorAeronautics and Astronautics https://engineering.mit.edu/fellow/chelsea-onyeador/
Sirma is a postdoctoral associate at MIT’s Institute of Medical Engineering Science. Her PhD research focused on developing energy-efficient circuits and systems, with an emphasis on bio-medical and neuroscience applications. She has developed a platform which involves a modular, light-weight, head-borne neuromodulation platform that achieves low-power wireless neuromodulation and allows bi-directional communication to monitor and manipulate the brain activity in real-time.She used MATLAB to send stimulation updates to the neuromodulation device as well as to receive and visualize the recorded brain activity. The graphical user interface she developed can be used in various neuromodulation experiments. Sirma earned a BS in electrical and electronics engineering from Middle East Technical University, Turkey and an SM and PhD in electrical engineering and computer science from MIT.
Sirma OrgucInstitute for Medical Engineering and Science https://engineering.mit.edu/fellow/sirma-orguc/
David is a PhD student in computer science and a member of the Geometric Data Processing Group. His current research focuses on the hexahedral (hex) meshing problem, which is of interest for applications, including fluid and nonlinear elastic simulations. Automatically computing high-quality hex meshes is a significant problem largely due to the complicated topology of hex mesh singularities, regions of a mesh for which the combinatorial structure is irregular. David’s research addresses challenges through the lens of smooth geometry. The field-based meshing research program replaces the hard combinatorial problem of hex meshing with computing a smooth volumetric frame field, encoding the alignment of the mesh elements with the ultimate aim of recovering a mesh from the field. While frame fields take values in nonlinear, non-convex algebraic spaces (the octahedral and odeco varieties), he has studied the geometry of these spaces and developed manifold-based optimization methods tailored to the frame field problem. He has created aMATLAB toolkit, ARFF, which allows him to experiment directly with high-dimensional spaces and complex topologies.David earned anAB in computer science from Harvard University and anMAS in mathematics from University ofCambridge, England.
David PalmerElectrical Engineering and Computer Science https://engineering.mit.edu/fellow/david-palmer/
Edward is a PhD student in materials science and engineering. His research is focused on the manipulation of the lattice crystallography in zirconia shape-memory ceramics by doping it, with the specific aim of making the two transforming phases more crystallographically compatible to prevent cracking. He is developing a combined machine learning and computational thermodynamics approach to design new material combinations with targeted crystallography and improved functional properties. He has additionally developed new optimization procedures that harness the power of recent physics-based simulations to resolve one of the long-standing limitations of the electron backscatter diffraction(EBSD) technique: indexing of pseudosymmetric materials. Through his research, he has developed three open-sourceMATLAB code packages for the scientific community: pcglobal, EBSDrefine, and EMsoft-utilities. Edward earned a BS in materials science and engineering from Northwestern University and an MPhil in materials science and metallurgy fromUniversity of Cambridge, England.
Edward PangMaterials Science and Engineering https://engineering.mit.edu/fellow/edward-pang/
Clara is a PhD student in the Department of Mechanical Engineering developing a dynamic robotic heart model that can be used as a surrogate heart for testing intracardiac devices, such as valve prostheses and occluder devices, before implanting patients.She focuses on replicating the complex beating motion of the heart, translating patient-specific cardiac muscle fibers to soft robotic structures to build a synthetic robot equivalent. She uses MATLAB to compute and visualize fiber tracts in the design process.Clara earned anSB in biological engineering and SM in mechanical engineering, both from MIT.
Clara ParkMechanical Engineering https://engineering.mit.edu/fellow/clara-park/
Ryan is a PhD student in mechanical engineering whose research is focused on the development of in-situ instrumentation and measurement techniques for end-to-end interrogation of selective laser melting (SLM) additive manufacturing. He has designed, built, and integrated two optical instruments with an SLM testbed: a mid-wave infrared (MWIR) camera that images thermal (blackbody) radiation from the build area and a near IR (NIR) pyrometer that measures the temperature of material directly at the laser’s focus. Determining the mathematical correspondence between a process signature and a component property (e.g. thermal radiance and density, respectively) is established by geometrically aligning the datasets using a metric of cross-predictive power between the datasets known as mutual information (MI). He is using the Signal Processing Toolbox to relate different process signatures to SLM component properties, including density, metallurgical grain size, and residual stress. Ryan earned a BS in electrical engineering and physics from Northeastern University and an SM in mechanical engineering from MIT.
Ryan PennyMechanical Engineering https://engineering.mit.edu/fellow/ryan-penny/
Charles is a PhD student in the Department of Electrical Engineering and Computer Science. His research interests include nanophotonics, light-matter-free-electron interactions, machine learning, complexity theory, quantum electrodynamics, and electron beam physics. His research contributions include the demonstration of novel nanophotonic light sources driven by free electrons, photonic computing architectures for complex optimization, and photonic devices to control light at the nanoscale (called metasurfaces). The MATLAB interface—enabling the simultaneous writing of scripts, decoding, evaluating variables in the command line, and plotting—has been instrumental in the design and analysis of his work on polarization-insensitive dielectric-based metasurfaces and on light emission from all-silicon substrates. In particular, MATLAB’s library of optimization algorithms proved extremely helpful in the correction of chromatic aberrations in dielectric metasurfaces, since the design of such metasurfaces requires the optimization of a complicated constraint function at various wavelengths of operation. More recently, he developed an algorithm called the Photonic Recurrent Ising Sampler (PRIS) that can solve NP-hard optimization problems by performing iterative matrix multiplications. While working on the experimental demonstration of the proposed concept with photonic components, he relied on MATLAB’s computational speed for large-scale matrix multiplications to numerically investigate the performance of the algorithm. MATLAB’s Basic Linear Algebra Subprograms enabled him to test the PRIS on large-scale, real-life problems, thus showing its promising performance on a set of benchmark Ising problems. Charles earned a BS in physics from École Polytechnique, Palaiseau, France.
Charles Roques-CarmesElectrical Engineering and Computer Science https://engineering.mit.edu/fellow/charles-roques-carmes/
Lluís is a PhD student in civil and environmental engineering studying geologic CO2 storage (GCS). GCS is the second stage of a technology known as carbon capture, utilization, and storage, a leading climate change mitigation technology and an enabling application for other negative-emissions technologies. Through a combination of geologic and multiphase flow modeling, he is addressing the critical question of migration and potential leakage of CO2 through faults during CO2 storage in sedimentary formations. Lluís is developing all of this research using MATLAB, ranging from visualization to sophisticated developments for the simulation of multiphase flow (governed by complex coupled PDEs) in multimillion-cell grids. In particular, he is a regular user of the MATLAB Reservoir Simulation Toolbox, to which he is also a contributor. Lluís is currently developing physics-based, probabilistic and machine-learning tools for the upscaling of fault properties and quantitative hazard assessment of CO2 migration through faults. Lluís earned a BS in geology from Universitat de Barcelona, Spain and an MS in geotechnical and earthquake engineering from Universitat Politècnica de Catalunya, Spain.
Lluís Saló-SalgadoCivil and Environmental Engineering https://engineering.mit.edu/fellow/lluis-salo-salgado/
Rohit is a PhD student in mechanical engineering developing continuum mathematical models for the collective dynamics in biological and engineered active fluids—for example, suspensions of swimming cells or self-propelling colloidal particles. In particular, he is developing and investigating physics-informed machine learning methods to infer partial differential equations that govern macroscopic observables directly from particle data. To achieve this, Rohit has used MATLAB for building a learning framework that coarse-grains microscopic data and results in interpretable models that are essential for predicting the complex dynamics in these systems. He has also extensively used MATLAB as a teaching tool in his role as a TA for a graduate subject in fluid mechanics, as well as an undergraduate subject in dynamics and controls. He earned a BTech in mechanical engineering from Indian Institute of Technology, India and an SM in mechanical engineering from MIT.
Rohit SupekarMechanical Engineering https://engineering.mit.edu/fellow/rohit-supekar/
Wenhui is a PhD student in mechanical engineering whose research focuses on the spatial and temporal self-organization of multicellular living systems in 3D during physiological and pathological processes. She uses modern microscopy to image in real time the 4D spontaneous organization of living cells and under various conditions, including different surrounding matrix mechanics and substrate curvature. Using MATLAB, she can extract data from microscopic videos and images and convert the optical intensity information into cell positions as a function of time. She also calculates the multicellular flow field such as swell/shrink, rotation and shear to understand how multicellular system dynamics changes as substrate curvature changes. Based on cell positions in 3D, she uses MATLAB code to perform Voronoi tessellation of cells on a spherical surface that can be used to reveal the cell packing behavior during human lung alveolar development. Wenhui earned a BEng from Xi’an Jiaotong University, China and an SM from MIT.
Wenhui TangMechanical Engineering https://engineering.mit.edu/fellow/wenhui-tang/
Huanhuan is a PhD student in chemical engineering. She is working on shock electrodialysis (shock ED), a new electrochemical process for water treatment that was designed and developed by the Bazant Research Group. Recent experimental results shows that shock ED can selectively remove multivalent cations, which could be promising for continuous and economical heavy metal ion removal from drinking water and industrious waste. For instance, preliminary results showed that shock ED can almost completely remove lead ions (Pb++) from model Flint tap water (mostly NaCl) from unsafe levels (up to 50ppb) down to <1ppb, well below the EPA action limit of 15ppb, in a point-of-use small-scale device with an operating electrical cost of only pennies per meter cubed of fresh water, compared with $25/m³ for existing (impractical) filtration methods. This new technology could have a significant impact on human health in the U.S. and around the world. She is using MATLAB to study PDE-based models of shock ED from experimental data (including her own) on selective ion removal. Her innovative work with MATLAB could lead to new simulation tools for electrochemical systems involving charged porous media and membranes, including (but not limited to) water treatment applications. Huanhuan earned a BEng and SB in engineering mechanics, both from Tsinghua University, China.
Huanhuan TianChemical Engineering https://engineering.mit.edu/fellow/huanhuan-tian/
Tony is a PhD student in the Department of Mechanical Engineering and the Center for Computational Science and Engineering. His research is focused on Bayesian inference and probabilistic machine learning. Tony earned a BEng in electrical and computer engineering from American University of Beirut, Lebanon and an SM in computational science and engineering from MIT.
Tony TohmeMechanical Engineering https://engineering.mit.edu/fellow/tony-tohme/
Haowei is a PhD student in nuclear science engineering whose research focuses on light-matter interaction and topological materials. Specifically, he uses coherent light (lasers) to manipulate the properties of materials and using materials to generate, detect, and manipulate light. He has also demonstrated that topological materials can have outstanding optical properties. He uses MATLAB for numerical modeling, including integration, optimization, and partial differential equations, to test ideas and/or obtain results easily, with far fewer lines of code, significantly accelerating his research. He also uses MATLAB to write code requiring large scale matrices, as well as visualization. Haowei earned a BS in physics from Peking University, China.
Haowei XuNuclear Science and Engineering https://engineering.mit.edu/fellow/haowei-xu/
Jin is a PhD student in biological engineering focusing on the development of a new bottom-up synthetic biology strategy for understanding how 3D genome organization regulates genome function. He is applying super-resolution microscopy to study the dynamics of chromatin looping in live cells and uses MATLAB for image segmentation and analysis. In recent work, using MATLAB SimBiology, he developed a synthetic genetic circuit, the Equalizer, that reduces the cell-to-cell variation of expression from plasmids close to that of a cell line, in which there is no gene copy number variation. Jin earned a BS in bioengineering from Rice University.
Jin (Harvey) YangBiological Engineering https://engineering.mit.edu/fellow/jin-harvey-yang/
A PhD student in aeronautics and astronautics, Yiyun is working on the application of plasma science to aerospace engineering. Her research is on dielectric barrier discharge actuators for flow and combustion modification. Recently, Yiyun has focused on the plasma aspects of the problem, building a 1D model of the discharge and analyzing experimental results in MATLAB. She earned a BS in mechanical engineering from Purdue University and an SM in aerospace engineering from MIT.