Development Team
Whether developing software, consulting with enterprise users, contributing to open source projects, or instructing students, Enthought developers are widely regarded as the experts in scientific computing with Python.
Puneeth Chaganti
Puneeth holds a B.S. in Electrical Engineering from Birla Institute of Technology and Science, Goa. Before joining Enthought, he worked with the Free and Open source Software for Science and Engineering Education (FOSSEE) project. There, he taught students and teachers to use Python and incorporate the language into their curricula.
Chris Colbert
Chris holds a bachelor's and master's of science in mechanical engineering from the University of South Florida. He has published research in the field of robotics and robotic vision with an emphasis on the shape and pose recovery of novel objects. Chris is a main contributor to the scikits.image project and is the primary author of Pymazon.
Mark Dickinson
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 currently maintains much of Python's numeric code.
Tim Diller
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.
Chris Farrow
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.
Simon Jagoe
Simon received his B.S. in Electrical and Information Engineering from the University of the Witwatersrand, South Africa. Simon is an experienced scientific software developer in a range of fields, from clinical research to mining.
Eric Jones
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.
Valery Kalatsky
Val received his B.S. in applied physics and mathematics from Moscow Institute of Physics and Technology (MIPT) before obtaining a M.S. in applied physics and mathematics from MIPT and Landau Institute for Theoretical Physics. In 1999, he earned a Ph.D. in physics from Texas A&M University. Before joining Enthought, Val was a postdoctoral fellow in the Keck Center for Integrative Neuroscience at UC San Francisco and in the Materials Science Division at National Argonne Laboratory. From 2004 to 2011 he worked as an Assistant Professor of Electrical and Computer Engineering at the University of Houston where he also directed the Neuromaging Lab and taught various courses ranging from circuit analysis and electromagnetism to stochastical processes and functions of the visual system. Val has expertise in data acquisition and analysis. He has written several applications for collection and analysis of data for optical imaging of intrinsic signals.
Robert Kern
Robert majored in geophysics at Caltech. He is major contributor to a variety of open source initiatives including NumPy, SciPy, grin, and line_profiler.
Jonathan March
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.
Jason McCampbell
Jason has 15+ years of software engineering experience, much of it building design automation tools for the semiconductor industry. He has worked with developer teams at numerous startups, with roles including product architect and R&D manager. Jason has expertise in circuit analysis and distributed/parallel system architecture. He holds a B.S. in computer engineering from the University of Michigan and MBA from Arizona State University.
Naveen Michaud-Agrawal
Naveen received his B.S. in computer science from Pennsylvania State University, an M.S. in computational biophysics from Johns Hopkins University. He is finishing a Ph.D. in biophysics from Johns Hopkins University and has been using Python for scientific data analysis and visualization for seven years, and wrote an open source package that utilizes NumPy to analyze molecular dynamics simulations. The package is now used in several laboratories.
Pankaj Pandey
Pankaj earned his Bachelor and Master of Technology in Aerospace Engineering from IIT Bombay. Prior to joining Enthought, he worked on smoothed particle hydrodynamics (SPH) modeling. For his masters research, Pankaj implemented load balancing and solid mechanics in the PySPH framework for SPH simulations.
Didrik Pinte
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.
Prabhu Ramachandran
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.
Raymond Roberts
Raymond Roberts received his B.A. from New College of Florida. His background is in mathematics and computational science with applications in bioinformatics. For his senior thesis he studied microRNA regulatory networks. This research focused on the application and analysis of graph algorithms to these networks.
Jonathan Rocher
With experience in complex system modeling and scientific computing, Jonathan contributes to Enthought's fluid dynamics applications as well as course materials and training tools. Prior to working at Enthought, he was an instructor and research assistant in particle physics and astrophysics at the University of Texas and Brussels University. Jonathan holds a M.S. in physics and a Ph.D. in particle physics and cosmology from the University of Paris, France.
Sean Ross—Ross
Sean earned his Bachelor of Science in computer science from the University of British Columbia. Prior to joining Enthought, he worked as an independent consultant designing custom solutions to address scientific computing challenges.
Ilan Schnell
After earning his Ph.D. in theoretical solid state physics from the University of Bremen, Germany, Ilan held positions as a postdoctoral research assistant at Los Alamos National Laboratory and Georgetown University. Ilan's scientific programming experience includes writing a program suite for first-principle band structure calculations for solids. At Enthought, Ilan is one of the key developers of the Enthought Python Distribution and works tirelessly configuring various Python libraries to run smoothly on multiple platforms. He is the author of the bitarray package.
Deepankar Sharma
Deepankar holds an M.S. in computer science from George Mason University and B.S. in electronics engineering from Mumbai University. His background is in artificial intelligence, and he is passionate about using heuristic techniques to solve real world problems. Other interests include genetic algorithms, data mining, and building tools on top of web-scale data.
Hugo Shi
Hugo received his B.S. in electrical engineering from UC Berkeley in 2003 and a Ph.D. from the University of Michigan in signal processing with a focus on medical image reconstruction in 2008. Prior to working for Enthought, he worked as a quantitative analyst for the Chicago Trading Company. Hugo's interests include signal processing, machine learning, data mining, and parallel computing.
Kurt Smith
Kurt has been using Python in scientific computing for nearly ten years, and has developed tools to simplify the integration of performance-oriented languages with Python. He received his B.S. in physics and applied mathematics from the University of Dallas, and his Ph.D. in physics from the University of Wisconsin-Madison. His doctoral research focused on the application of fluid plasma models to astrophysical systems, involving the composition of high-performance simulations of plasma turbulence.
Ioannis Tziakos
Ioannis has a background in physics and holds a M.S. in electronics from the University of Patras, Greece. He earned his Ph.D. in electronic engineering at Queen Mary, University of London, UK, where he investigated graph-based manifold learning approaches to address the novelty detection problem for video surveillance scenarios. He is an experienced researcher with published work in the field of graph-based dimensionality reduction methods and their application to high-dimensional pattern recognition problems such as image and video analysis.
Corran Webster
Corran obtained his B.S. from the University of New South Wales and his Ph.D. in pure mathematics from UCLA. He has held teaching positions at the University of Nevada, Las Vegas as well as Texas A & M. His academic areas of concentration included functional analysis and operator algebras. As Chief Scientist at Compudigm International, Corran worked on enterprise data visualization and redictive modeling using self-organizing maps. Corran has been programming in Python since 1995, when he was a teaching assistant in UCLA's Program in Computing courses.
Warren Weckesser
Warren received his M.Eng. in computer and systems engineering and Ph.D. in mathematics from Rensselaer Polytechnic Institute. He held assistant professorships at the University of Michigan, Colgate University, and the University of Sydney for a cumulative eight years. His specialties include mathematical modeling, dynamical systems, multiple time scale systems, and perturbation methods.
John Wiggins
John earned his Bachelor of Science in computer science from the University of Texas. Prior to joining Enthought, he worked as a research assistant in scientific visualization at UT before spending several years as a mobile and embedded games developer.
David Wyde
David obtained his B.A. from New College of Florida. Aside from Python, he is primarily interested in client-side web technologies. His senior thesis was a web application for collaborative data analysis.
