Adrian Heilbut is a PhD candidate in Bioinformatics at Boston University and the Broad Institute, working on on development of statistical methods for analysis of structured experiments and tailoring feature learning algorithms to biological data. Before going back to school, he worked in biotech, deconstructing yeast at MDS Proteomics and fighting robots at CombinatoRx. He holds B.Sc.(Hon) in Computer Science and Neuroscience from the University of Toronto.

Alex Rubinsteyn is a Computer Science Ph.D. student at NYU. His interests are a high variance mixture distribution around programming language implementation and machine learning.

Andrew Giessel is a postdoctoral research fellow in the Datta Laboratory, Department of Neurobiology, Harvard Medical School. His work focuses on the brain circuits of odor detection and innate behaviors of mice using a combination of microscopy, electrophysiology and genetics. He uses Python for daily analysis and management of neurobiological data.

Coming soon.

Ben is the co-founder and CEO of DataNitro, a YCombinator backed startup which integrates Excel with Python. He has a degree in Mathematics from MIT.

Bryan Lewis is the chief data scientist at Paradigm4. Bryan is an applied mathematician and is the author of a number of R packages including irlba, rredis, doRedis, websockets, and bigalgebra.

Cam Davidson-Pilon is a ex-finance quant from Waterloo, Ontario. His experiences in statistics and Python have taken him to Moscow, Toronto and now Ottawa, where he recently joined the data-team at Shopify. Cam is the author of Bayesian Methods for Hackers, the open-source book on Github, and the blog camdp.com (aka that subway blog).

Cathy O’Neil earned a Ph.D. in math from Harvard, was postdoc at the MIT math department, and a professor at Barnard College where she published a number of research papers in arithmetic algebraic geometry. She is co-authoring a book (with Rachel Schutt) called “Doing Data Science” to be published by O’Reilly in Fall 2013. She previously worked as a quant for the hedge fund D.E. Shaw in the middle of the credit crisis, and then for RiskMetrics, a risk software company that assesses risk for the holdings of hedge funds and banks. For the last couple years she’s been a data scientist in the New York start-up scene. She writes a blog at mathbabe.org and is involved with the #Occupy Wall Street Alternative Banking Working Group.

Chris is a professional software developer in New York City where he uses Python and C++ to develop the UI framework for the front office trading platform of a large investment bank. He is the creator of the Nucleic project which is a collection of software for developing enterprise quality Python applications. He received his MS in Mechanical Engineering from the University of South Florida.

Chris is a data analyst at Meetup.com, where he uses Python for exploration and predictive modeling. He received his BA from Washington University in St. Louis in statistics and economics. He organizes a data Meetup in NYC: nydatameetup.com

Craig Schmidt is the founder of Predictobot. He has a background in Operations Research and optimization. He has worked on supply chain software, for a quantitative hedge fund developing trading strategies, and for a company developing predictive models in the education space. He has a Ph.D. in engineering from Carnegie Mellon.

Coming soon.

Demian graduated from the University of Buenos Aires, Argentina, where he obtained his B.Sc in computer science. He obtained his PhD at the Athena research team at the INRIA Sophia Antipolis under the supervision of Professor Rachid Deriche. In his PhD he focused on the analysis of white matter fibers traced from Diffusion MRI, aiming at providing a sound mathematical framework for automatic dissection and statistical analysis of the structures of the human brain's white matter. Since May 2010, Demian is jointly working at the Laboratory of Mathematics in Imaging, the Psychiatry and Neuroimaging Lab and the Surgical Planning Laboratory at the Harvard Medical School and the Brigham and Women's Hospital.

Eric Jonas is Chief Predictive Scientist at Salesforce.com, and currently a PhD candidate at MIT working on scalable stochastic systems. He tweets as @stochastician.

Coming soon.

Coming soon.

Imri Sofer is a graduate student at Brown University. His research involves building computational models of object recognition and decision-making. His interests are in Bayesian data analysis, machine learning, scientific computing, and computer vision. He is also a core developer of HDDM, a package for Bayesian analysis of decision-making experiments.

James Powell is a professional Python programmer based in New York City. He is the chair of the NYC Python meetup nycpython.com and has spoken on Python/CPython topics at PyData SV, PyData NYC, PyTexas, PyArkansas, PyGotham, and at the NYC Python meetup. He also authors a blog on programming topics at seriously.dontusethiscode.com

Coming soon.

Jonathan Jesneck’s first large machine learning project was building a successful breast cancer detection system that integrated disparate medical data across several hospital departments. Dr. Jesneck then conducted postdoctoral research in the cancer program at the Broad Institute of Harvard and MIT. He served as a computational biologist in the pediatric oncology department of the Dana-Farber Cancer Institute, where he led the analysis team for high-throughput screening for drug discovery. As a research scientist at the MIT Field Intelligence Laboratory, he built machine learning systems for city-scale energy mapping using computer vision analysis of thermal images. He then founded Essess, scaling up distributed image processing and machine learning applications for high-throughput energy mapping.

Fisa is a developer at Machinalis, where he uses python. He is also an instructor at UCSE DAR*, where he teaches about Artificial Intelligence and Software Engineering for Internet Applications, also with python. Fisa love python, lisp, artificial intelligence, software development, and anything that makes him think and learn :)

Justin Riley is a senior developer in the Office of Digital Learning (ODL) at the Massachusetts Institute of Technology (MIT). Justin works with faculty to help bring research tools into the classroom at MIT. He is the lead developer for the StarCluster project at MIT.

Justin is a Principal Software Engineer at World Travel Holdings. He previously was a Director of Technology at Selventa, and a Senior Software Engineer at Perot Systems.

Lynn Cherny is a data analysis consultant in the Boston area (www.ghostweather.com). She works with Python, R, and javascript; she's particularly interested in ways that interactive data visualization can clarify the results of machine learning algorithms. Lynn has a Ph.D from Stanford University in Linguistics.

Matei Zaharia is finishing his PhD at UC Berkeley, where he started the Spark project and has also done research on other large-scale computing systems including Hadoop, Mesos and Shark. He has contributed to open source throughout his PhD, becoming a committer on both Hadoop and Mesos. After finishing at Berkeley, Matei will start an assistant professor position at MIT.

Michael Becker is a Data Engineer at AWeber and founder of the DataPhilly Meetup group. On a day to day basis, he spends a majority of his time acquiring, scrubbing, exploring, and visualizing data. He loves machine learning and gets his kicks out of clustering, regression and classification algorithms.

Michael Selik is an econometrics and machine learning consultant based in New York City. He has worked for Dow 30 corporations and venture-backed startups delivering sophisticated analysis and technology project management services. Recent projects include hyperlocal demographics inference, customer segmentation, and market share forecasting. He received a MS Economics, a B.S. Computer Science, and a B.S. International Affairs from the Georgia Institute of Technology.

Michael Sun is a Principal Engineer at Jumptap, Inc. Michael has eighteen years of experience of software system architecture, design, and development in the fields of big data, data warehouse, data analytics, statistics, databases, and distributed systems. Michael holds a Ph.D. in Applied Physics from Harvard University.

Coming Soon

Satrajit Ghosh is a research scientist in the McGovern Institute for Brain Research at MIT, a faculty member for the Speech and Hearing Biosciences and Technology program at Harvard Medical School and a member of the INCF taskforce on Standards for DataSharing. His work focuses on enhancing interoperability across brain imaging software and on data mining with the intent of optimizing solutions for translating brain imaging research to clinical applications. He is a lead architect of the Nipype (nipy.org/nipype) project and an ardent proponent of implementing W3C provenance standards and standard vocabularies across brain imaging and scientific disciplines.

Saul Diez-Guerra is a senior software engineer at Ampush in New York City, where he uses Python to build ad management and bidding systems, after a stint in social network R&D at Telefónica. He hails from Spain, where he received both a Bachelors in Computer Science as well as one in Telecommunications.

Coming soon.

Coming soon.

Thomas Wiecki is a 3rd year Ph.D. student at Brown University. His research domain is computational cognitive neuroscience. He also works as a researcher for Quantopian Inc. His interests include statistical modeling, Bayesian data analysis and scientific and higher performance python programming. Thomas is the author of several open source Python packages including HDDM, a scientific tool used to study decision making, and mpi4py_map, which adds worker-pool and queuing capabilities to mpi4py.

CEO and Co-Founder, Continuum Analytics Introduction to NumPy; Introduction to SciPy

Dr. Oliphant has a Ph.D. in Biomedical Engineering from the Mayo Clinic, and M.S. and B.S. degrees in Electrical Engineering (and Math) from Brigham Young University. Travis has worked extensively with Python for numerical and scientific programming since 1997, and was the primary developer of the NumPy package and the author of the definitive Guide to NumPy. He is also the primary founding author of the SciPy package. During his academic career, he has worked in the fields of satellite remote sensing, Magnetic Resonance Imaging (MRI), Ultrasound, elastography, and general inverse problems. He was an Assistant Professor of Electrical and Computer Engineering at Brigham Young University from 2001 to 2007 where he taught courses in probability theory, electromagnetics, inverse problems, and signal processing. In addition, he directed the BYU Biomedical Imaging Lab, and performed research on scanning impedance imaging. He has done consulting work since 1997 in laser scattering off of semiconductors, sparse matrix calculations for search engines, and mesh transformations for fluid dynamics. Dr. Oliphant co-founded Continuum Analytics, Inc. in 2012 and currently serves as its CEO.

Coming soon.

After completing his graduate work at CU Boulder, Mr. Ye joined SRI International, where he focused on design and development of innovative wireless, handheld, and Web-based simulation tools and services. Mr. Ye returned to Boulder as a developer on the commercialization team at Tech-X Corp, where he developed and productized large-scale HPC software. Mr. Ye is currently a Senior Research Program Manager responsible for Cloud-based Big Data and Big Compute projects at Microsoft Research Connections.

Zak Fallows is a software engineer at Medica, a medical device company. Prior to that, Zak studied chemistry and neuroscience at MIT. Zak's interests include open source software, health care, teaching, and web development.