Steve holds a Ph.D. in Physics with an emphasis on strongly correlated particles. As a postdoctoral fellow, he specialized in computer vision research and development. Before joining Enthought, Steve worked for ten years at the Universite de Sherbrooke as a Scientific Programming Analyst in support of research projects from various disciplines. He engineered a number of computer applications for high performance clusters. He is broadly interested in code parallelization, optimization and developing algorithms.
Eric earned his Ph.D. in nuclear physics and M.S. in physics from The Ohio State University, as well as a B.S. in both physics and mathematics from the University of Kentucky. His graduate research focused on applications of numerical renormalization group methods to the ab-initio computational solution of the nuclear many-body problem. Prior to joining Enthought, Eric held a post-doctoral research position at the University of North Carolina at Chapel Hill where he worked on the development of lattice Quantum Monte Carlo methods and their application to diverse quantum systems.
Stefano holds a Ph.D. in quantum chemistry from Ferrara University in Italy and Paul Sabatier University in France, where he specialized in ab-initio perturbation theory, localized orbitals techniques, and their software implementation and integration. He focused his expertise toward scientific programming, working in both industrial and academic environments for quantum chemistry, material science, and bioinformatics.
Alexandre Chabot-Leclerc holds a Ph.D. in Electrical Engineering from the Technical University of Denmark. His graduate research was in the field of hearing research, where he developed models of human speech perception. Alexandre's interests include teaching, psychoacoustics, and rock climbing.
Kit holds a B.S. in physics from Chinese University of Hong Kong and Ph.D. in Atmospheric and Oceanic Sciences from Princeton University. Prior to joining Enthought, Kit worked on numerical simulations of the Earth climate dynamics, cloud formation, laser optics and neutrino detection. Apart from typing and scribbling at the computer desk, she was also in the machine shop lathing and milling tools for instrumental experiments.
Before joining Enthought, Andrew worked as a experimental physicist at the University of Colorado’s IMPACT hypervelocity accelerator facility, studying the effects of high-speed micrometeoroid impacts on planetary surfaces and spacecraft. Andrew is the founder of the HDF5 for Python (h5py) software project, and while in Colorado operated a small consulting company focused on HDF and LabVIEW-based software. He holds a Ph.D. in plasma physics from UCLA, where he worked on expanding laser-produced plasmas at the Basic Plasma Science Facility.
David graduated with a MsC in EE from Telecom Paristech, Paris in 2004, and obtained his PhD in Computer Science at Kyoto University, Japan, in the domain of speech recognition. He is a long-time contributor to NumPy and SciPy, and also started what would become the scikit-learn package for machine learning during summer 2007. He joined Enthought during the summer 2011, after having worked for Silveregg, a SaaS Japanese company delivering recommendation systems for some of the biggest Japanese online retailers.
Mark received a B.A. in pure and applied mathematics from the University of Cambridge and a Ph.D. in pure mathematics from Harvard. He has held teaching and research positions at the University of Michigan, the University of Pittsburgh, and the National University of Ireland, Galway. Mark is a member of the Python core development team, and has worked on much of Python's numeric code.
Tim holds a Ph.D. in mechanical engineering, specializing in thermal and fluid sciences. He has worked in the automotive industry with emissions measurement, modeling, and control in addition to vehicle dynamics modeling and simulation. He comes to us from a post-doctoral research position at the University of Texas, where he developed a numerical model and simulation of thermal transport processes in the laser sintering rapid-prototyping process at the LFF
Robin Dunn, the creator and maintainer of wxPython, has been working in the software industry for more than 2 decades in a wide variety of application disciplines, from medical records to telecoms to business applications, both server-side and client-side. He discovered both wxWidgets and Python in 1995 while looking for a cross platform toolkit for C++ and has used Python and wx whenever possible since then, and in the process has become a strong proponent of Open Source. Robin has a B.S. degree in Computer Science from Brigham Young University, is the co-author of the first book about wxPython, wxPython In Action, and spends most of his time in Vancouver, Washington, USA.
Chris has a background in computational physics, which he has applied to various problems in materials science. Chris earned his Ph.D. in physics at Michigan State University, where he investigated the dynamics of correlated percolation and methods for combining complimentary structural information to determine the atomic structure of materials. At Michgan State, and later Columbia University, Chris was a member of the DANSE diffraction team and helped develop the DiffPy package for diffraction analysis.
Eric has a broad background in engineering and software development and leads Enthought's product engineering and software design. Prior to co-founding Enthought, Eric worked in the fields of numerical electromagnetics and genetic optimization in the Department of Electrical Engineering at Duke University. He has taught numerous courses about Python and how to use it for scientific computing. He also serves as a member of the Python Software Foundation. Eric holds M.S. and Ph.D. degrees from Duke University in electrical engineering and a B.S.E. in mechanical engineering from Baylor University.
Steven earned B.S. degrees in biology and mathematics at the University of Maryland and is currently pursuing a M.S. in Statistics at Texas A&M University. Before joining Enthought he worked in biostatistics for medical research and biodefense. His interests include experimental design, Bayesian estimation, statistical plotting, and minimizing the boundaries between researchers and informative inferences on their data.
Jonathan brings decades of experience developing real-time data collection, signal analysis, and interactive exploratory data analysis. He collaborated and published extensively on basic sleep research at UC San Francisco and Davis.
Prashant earned a B.E. in mechanical engineering from BITS Pilani, and a M.S.E in engineering mechanics from the University of Texas at Austin. His graduate work focused on developing scalable models of flow and fracture mechanisms in reservoirs. After a successful internship during summer 2015, he joined the company full-time in January 2016. In his spare time, Prashant dabbles in photography and remains active in his alma mater’s local alumni chapter.
Dillon Niederhut holds a Ph.D. in Anthropology from the University of California at Berkeley. His graduate research was in computational semantics and advanced neuroimaging applications, and he taught graduate-level classes in R and Python. Prior to joining Enthought, Dillon developed heterogeneous processing and analytics pipelines for Berkeley's Data Lab. Outside of the office, he contributes to several open-source initiatives, including Mozilla Science Lab, Bayes Impact, and Open Austin.
Didrik Pinte brings us his broad experience in data management and software development. Prior to working with Enthought, Didrik ran his own company providing data management solutions in the environmental sector. He also worked as a research assistant during 4 years at Catholic University of Louvain (UCL) in Belgium. His research there focused on the development of integrated water resource management applications with Python. Didrik holds a M.S. degree from UCL in Agricultural Engineering as well as a M.S degree from UCL in Management.
Jenni received a M.S. in solid state physics from the University of Milan Bicocca and a Ph.D. in applied and computational physics from Michigan State University. Her research focused on modeling and optimising a high brightness electron microscope and using ab-initio techniques to simulate measurements taken with this instrument. She also brings in years of experience in teaching coding and physics.
Rahul graduated with a Dual Degree (B.S. & M.S.) in Physics from IIT Madras. Rahul is interested in astronomy and astrophysics and his thesis project was on numerically evaluating various models describing the early universe to estimate parameters, parameters that can be crosschecked using observations. In his spare time, he writes code that visualizes physics concepts.
Prabhu Ramachandran has been a faculty member at the Department of Aerospace Engineering, IIT Bombay, since 2005. His research interests are primarily in particle methods and applied scientific computing. He has been active in the FOSS community for more than a decade. He co-founded the Chennai Linux User Group in 1998 and is the creator, and lead developer of Mayavi. He has contributed to the Python wrappers of the Visualization Toolkit. Prabhu has a Ph.D. in Aerospace Engineering from IIT Madras. He is an active member of the SciPy community as well as a member the Society for Industrial and Applied Mathematics and a nominated member of the Python Software Foundation.
Joe received a B.S. in computer science from the University of Texas at Austin. He has a background in scientific visualization and high performance computing in various domains. Before joining Enthought, he had been involved in software development projects ranging from the visualization and modeling of biological phenomena to seismic interpretation. Joe's interests include software engineering, graphics algorithms, parallel computing, and decentralized computing.
Joris has a Ph.D. in applied mathematics from Ghent University in Belgium and has held research positions at Caltech, the University of California, San Diego, and Imperial College before joining Enthought. He has published extensively about dynamical systems and hydrodynamics and has developed fast numerical algorithms for curve matching and for the geometric integration of hydrodynamical systems.
Jordan holds a B.S. in physics from Louisiana State University and Ph.D. in nuclear engineering from the University of Texas at Austin. His graduate research involved using Python to develop detection systems that improved environmental radionuclide monitoring for nuclear weapons test ban treaty verification. Prior to joining Enthought, Jordan worked in Washington, D.C. as a Program Scientist and Science Fellow for one of the nation's largest environmental NGOs, where he focused on improving the safety and economics of the existing nuclear fuel cycle through interactions with the DOE, U.S. NRC, and other government agencies, as well as conducting research that examined the proliferation and environmental risks of emerging nuclear technologies.
Corran has a B.S. from the University of New South Wales and a Ph.D. in pure mathematics from UCLA and has held positions at the University of Nevada, Las Vegas and Texas A&M University, working primarily in operator algebras and functional analysis. Prior to joining Enthought, he was Chief Scientist at Compudigm International working on machine learning with self-organizing maps and large data visualization methods. Corran wrote his first Python code back in the days of Python 1.3 and has used it as his primary programming language for over 20 years.