Wolfram Computation Meets Knowledge

Wolfram Summer School

2019 Faculty All Faculty

Stephen Wolfram

Stephen Wolfram is the author of A New Kind of Science and the principal lecturer at the Summer School. He is the creator of Mathematica, the creator of Wolfram|Alpha and the founder and CEO of Wolfram Research. Having started in science as a teenager (he got his PhD at age 20), Wolfram had a highly successful early career in academia. He began his work on NKS in 1981 and spent ten years writing the NKS book, published in 2002. Over the course of 30 years, Wolfram has mentored a large number of individuals who have achieved great success in academia, business and elsewhere. Starting the NKS Summer School (now called the Wolfram Summer School) was his first formal educational undertaking in 16 years.


Jesse Friedman

Technical Developer

Jesse is a software engineer with a focus on networked applications, systems integration and cloud computing. He enjoys long random walks on Euclidean planes and not writing bios.

Kyle Keane

Program Director

Kyle Keane is currently a full-time lecturer at MIT and part-time consultant at Wolfram in the Technical Communications and Strategy Group. Kyle was a research programmer in the Special Projects Department of Wolfram Research from 2012–2015, where he worked on establishing K–12 programming initiatives, including developing a general step-by-step physics and equation solver in Wolfram|Alpha and helping Siri speak Wolfram|Alpha results. His main areas of interest are the pedagogical effectiveness of interactive graphics, evidence-based infusion of programming into science education, improving the accessibility of technology for people with disabilities and user experience. Kyle has a PhD from the University of California, Riverside, where his dissertation was on utilizing weak quantum measurements to protect quantum systems from information loss during quantum computing.

Vitaliy Kaurov

Academic Director

Vitaliy Kaurov joined the Technical Communications and Strategy Group at Wolfram Research in 2010. He has given numerous talks at universities, research labs, companies and conferences around the world, educating people on how Wolfram technologies empower academics and industries, governments and individuals. Vitaliy is involved with international business development, oversees Wolfram Community, writes for the Wolfram Blog, is a faculty member at the Wolfram Summer School and helps with many other Wolfram initiatives. Vitaliy received his PhD in theoretical physics from the City University of New York in the area of ultra-cold quantum gases, and also worked in the fields of complex systems and nonlinear dynamics. He collaborated in National Science Foundation–sponsored research, was a professor at the College of Staten Island and served as an organizer and chair at American Physical Society conferences. Wolfram technologies helped Vitaliy to discover novel scientific ideas and develop innovative educational solutions.

Swede White

Public Relations

Swede White manages public relations at Wolfram Research and is an alumnus of the Wolfram Summer School. Swede helps audiences understand the innovative things people can accomplish with Wolfram’s technology through thought leadership programs, social media campaigns, and earned media placements in outlets like WIRED, The Wall Street Journal, Scientific American, Business Insider, and others. Prior to joining Wolfram, Swede worked in broadcast journalism and attended graduate school at Louisiana State University studying sociology. Swede’s research interests include applying sociological theory to practical communications projects using computational methodologies in Wolfram Language, including natural language processing and network analysis. Specifically, he examines the relationship between identity formation and online communities. ​He’s also written for VICE, reported for the NPR Newscast Unit, and presented research at academic conferences ranging from computational social science to masculinities and criminology.  


Christopher Wolfram


Christopher Wolfram is a full-stack programmer and algorithm developer who has been programming in Wolfram Language since a young age. He has been the lead developer for several built-in Wolfram Language functions (including Nearest and Encrypt), as well as for Tweet-a-Program and several of his own apps. He has presented at SXSW, Maker Faire, livecoding.tv and other venues on topics such as machine learning, data science and IoT programming. Christopher enjoys 3D modeling, Haskell, Swift, history, tennis and traveling. He has been a mentor for the Wolfram Summer Programs for five years.

Daavid Väänänen


Daavid Väänänen has a passion for advancing humanity by improving accessibility to high-quality education and applying emerging technologies to enhance organizational excellence and life quality for all. Since attending the Wolfram Summer School in 2017, he has been advocating and developing Wolfram Language–based resources as a Wolfram Community Ambassador, particularly with the Wolfram Foundation’s Computational Thinking Initiatives. He holds a PhD in theoretical astrophysics from Pierre and Marie Curie University in Paris, France. As a postdoctoral researcher at North Carolina State University, he continued research on nonlinear dynamics of many-body quantum systems applied to astrophysical environments, as well as promoted educational outreach and public engagement. He also holds a group fitness instructor certificate and enjoys yoga, rock climbing, gardening and other outdoor activities. He firmly believes that by acting together, our persistent efforts will be able to transfer our optimistic ideas into positive realities for all people.

Dariia Porechna


Dariia Porechna was born and grew up in the beautiful city of Kyiv, Ukraine. In 2016, she graduated with a bachelor’s degree in applied maths and cryptology at the Kyiv Polytechnic Institute. Her graduation project was an attempt to attack the Kuznyechik cipher with differential cryptanalysis. Recently she contributed to research in the field of elliptic curves. Dariia fell deeply in love with the Wolfram Language in early 2015 and attended the Summer School as a student the same year. After graduation, she joined the Wolfram|Alpha team as a part of the localization project. Aside from working, she loves self discovery, reading books and traveling, especially taking long walks around cities and enjoying the ocean views.

Etienne Bernard


Etienne Bernard is the lead developer of the Machine Learning Group at Wolfram Research, where he focuses on developing machine learning functionalities for the Wolfram Language. His work aims to simplify the practice of machine learning in order to spread its usage. Etienne obtained a PhD in physics from ENS Paris, where he designed Markov chain Monte Carlo algorithms to solve physics problems. He also worked as a postdoctoral scholar at MIT on Markov chain Monte Carlo algorithms and non-equilibrium statistical physics.

Flip Phillips


Professor Phillips’ career trajectory began in the early 1980s in the school of architecture at The Ohio State University, attracted by its cross-disciplinary combination of art, design, engineering, and science. He was introduced to the then-nascent world of computer graphics by Skidmore, Owings & Merrill’s presentation of a CG fly-through of Chicago Illinois. At the time, OSU was leading the way in computer graphics with notable researchers and artists including Charles Csuri, Chris Yessios, He earned his BFA, studying with Csuri, in 1986.
After his bachelor’s degree, Phillips taught and did research in medical imaging and shape before joining up with the newly constituted Pixar — a spin-off from LucasFilm and another hotbed of interdisciplinary activity. As Pixar became both more successful and more focused on motion picture animation, Phillips returned to Ohio State for a Ph.D. in architecture. A series of coincidences (featuring his Pixar colleagues Alvy Ray Smith and Loren Carpenter and some books by Jan Koenderink and Bela Julesz) happily led to a Ph.D. in cognitive psychology instead. There, he specialized in the perception of three-dimensional shape, inspired by his earlier architectural and computer graphics training. Phillips is a past editor of the Mathematica Journal, which focuses on computer mathematics across the spectrum of science, art, and social and economic modeling. He has written and edited books, journal articles, and reviews on subjects ranging from vision and its interaction with touch to deception in sports and prestidigitation.

Giulio Alessandrini


Giulio Alessandrini graduated with a master’s degree in physics at the University of Rome “La Sapienza.” His studies comprised mainly statistical mechanics and its applications in different fields, such as neural networks, disordered systems and biological systems. His last project revolved around the statistical analysis of bacterium E. coli’s central carbon metabolism. He participated in the 2012 Summer School as a student and joined Wolfram Research afterward. He now contributes to the development of image processing functions for Wolfram Language. His interests span from natural sciences and Karate-Do to Italian cantautori (singer-songwriters), science fiction and politics.

Jérôme Louradour


Jérôme Louradour joined the Machine Learning Group at Wolfram Research two years ago. There he contributes to the neural network framework and applies deep learning to develop new solutions for natural language understanding.
After receiving his PhD in computer science in 2006, Jérôme spent two post-doctoral years at the University of Montreal with professor Yoshua Bengio, one of the main pioneers of deep learning. Since then, Jérôme has been working more than 10 years as a researcher and research manager in the industry, with a focus on implementing state-of-the-art Machine Learning methods for handwriting recognition and various applications in natural language processing.

Jofre Espigulé Pons


Jofre Espigulé Pons has a background in physics. Prior to joining Wolfram, he did research on quantum physics and biophysics, in particular on the magnetoreception of birds and the limits of human vision. He was a student at the Wolfram Summer School 2015, where he used machine learning to identify species of birds based on their songs. He has a broad interest in topics ranging from computational linguistics to computational sports.

Jonathan Gorard


Jonathan Gorard is a research mathematician at the University of Cambridge, where he works on a variety of problems related to the intersection of mathematics, physics and computation; having published his first scientific paper at 17, his published work now covers topics ranging from computational complexity theory, combinatorics and cosmology to general relativity, mathematical logic and the foundations of quantum mechanics to cellular automata, complex systems and quantum computation. Since 2017, he has also worked as a mathematical consultant for Wolfram Research, Inc., leading the development of Wolfram Language’s automated theorem-proving and quantum-computing frameworks and working on various related areas, such as semantic representation of mathematics, symbolic logic, discrete-state quantum mechanics and graph theory. He is also one of the principal researchers on the Wolfram Physics Project, having made several key contributions to the mathematical formalism of the Wolfram model (particularly in regards to the derivations of general relativity and quantum mechanics and its connections to quantum information theory); he has also done extensive algorithms development work for the Physics Project, particularly in relation to multiway evolution, hypergraph isomorphism testing, causal graph computation, causal invariance testing and the application of automated theorem-proving techniques. He attended the Wolfram Summer School as a student in 2017 and has been an instructor since 2018.

Matthew Szudzik


Matthew Szudzik made significant contributions to A New Kind of Science from 1998 through 2000 and during the summer of 2001 as a research assistant to Stephen Wolfram. His work focused primarily on the analysis of simple programs and on the theoretical foundations of computational mathematics. He holds a PhD in mathematical logic from Carnegie Mellon University. Matthew Szudzik has also worked as a special lecturer and as an assistant teaching professor of mathematics at Carnegie Mellon’s campuses in Pennsylvania and Qatar.

Paul Abbott


Paul Abbott is an adjunct professor at the University of Western Australia. He obtained his PhD in theoretical atomic physics from UWA in 1987, worked for Wolfram Research from 1989–1992 and has been a Wolfram consultant and instructor since 1997. Paul was the founding technical editor of The Mathematical Journal in 1990 and was a columnist until 2010. His interests range from computational physics, applied mathematics and special functions to courseware design. All of his research and teaching since 1985 has used Wolfram technologies in some way, and his work has been recognized most recently by a Wolfram Innovator Award in 2015 and an Australian University Teaching Award in 2016. In his spare time, Paul enjoys cycling, walking, swimming, photography, reading and writing.

Riccardo Di Virgilio


Riccardo Di Virgilio received a bachelor’s degree in economics and financial science in November 2005 and another bachelor’s in moral and social philosophy in December 2007. From then on, he has worked as a web developer for Sprint24.com, developing a Python web application to centralize business management. Every employee now uses a barcode system to update in real time the status of an order, and the application automatically dispatches notifications (via email, SMS or fax) and creates related documentation (e.g. invoices, delivery documents, etc.). He succeeded in transforming a heavily paper-based production workflow into a dynamic, database-driven workflow, resulting in increased efficiency, reduced waste and a consistent decrease of labor and human errors.

Robert Nachbar


Robert Nachbar is senior project director in Wolfram Solutions, the consulting arm of Wolfram Research, where he both leads technical teams and develops custom applications for clients with Wolfram technologies. He joined Solutions in 2014 after retiring from the pharmaceutical industry, where he used Mathematica and other Wolfram technologies for drug design, data analysis and clinical research. He holds a PhD in organic chemistry from Brown University and received the Wolfram Innovator Award in 2012. His research and computational interests include chemistry, biology, discrete mathematics, optimization, simulation and interactive visualization. He has been a frequent presenter at Wolfram Technology Conferences.

Timothée Verdier


Timothée Verdier graduated from the École Polytechnique and then obtained a PhD in biophysics at ENS Lyon, where he studied the physics of virus self-assembly and super-resolution imaging. Currently, he is a developer for the machine learning group at Wolfram Research, where he works on developing machine learning functionalities for the Wolfram Language, with a particular interest in neural networks and natural language processing. He is an outdoor and mountain-stuff lover who goes hiking, climbing or ski-touring whenever he has the opportunity…

Tuseeta Banerjee


Tuseeta Banerjee is a Research Scientist in the Machine Learning team, focusing on applications of neural networks. She imports and implements neural net models in the Wolfram Language for various high-level functions in Mathematica and for the Wolfram Neural Net Repository. In her previous role as a technology engineer, she provided machine-learning based solutions to clients. She is also a certified Wolfram language instructor, teaching and creating various courses on Mathematica programming with a focus on statistics and deep learning. Prior to joining Wolfram, she completed her Ph.D. in 2015 from the University of Illinois at Urbana Champaign with her research work in the field of chemical physics and certification in Computational Science and Engineering. For her Ph.D. research, she used Monte Carlo-based quantum-classical path integral methods to study models that mimic chemical reactions and photosynthetic reaction centers.

Teaching Assistants

Wenzhen Zhu

Teaching Assistants

Wenzhen is a data scientist and software engineer at AWS, specifically in the Machine Learning Solutions Lab. As a customer-facing data scientist, her job is to design, develop and evaluate innovative machine learning and deep learning models to solve diverse challenges and opportunities across industries. She interacts with customers directly to understand their business problems and helps them with defining and implementing scalable machine learning and deep learning solutions to derive business value quickly. Before that, she graduated from Washington University in St. Louis, where she got a BS and MS in computer science and math. She likes machine learning because it is a powerful tool and subject that combines math and programming. She is also broadly interested in many machine learning and AI topics, computer graphics and financial investments. Outside of work, she loves traveling (business and personal), reading (emotional novels and research papers), watching movies (romance and sci-fi), shopping (tech gadgets, fashion and beauty products) and exercising. Dance is her favorite way of exercising, and she takes Latin dance and ballet classes regularly. She also plays the guzheng—an ancient Chinese string instrument. She is an INFJ, a very complicated personality. She is also an excellent cook, and she likes to cook authentic Szechuan dishes to host her friends on weekends.