After working in a crime lab, Dr. Burks returned to academia, teaching, and forensic science research. Her research team is focused on the development of colorimetric and luminescent sensing systems with integrated image and chemometric analysis for forensic applications. She is co-creator of the Digital Imaging and Vision Applications in Science (DIVAS) project which created a pedagogical and programmatic "onramp" that empowers natural science majors to engage in authentic computational problems as members of community of practice. Beyond the bench, Dr. Burks is a popular science communicator appearing regularly on TV, radio, podcasts, and print outlets. Most recently, she was a series regular in the Smithsonian Channel show "The Curious Life and Death Of..." and writes a science-meets-true crime column called “Trace Analysis” for Chemistry World. In 2020, she was awarded the American Chemical Society's Grady - Stack Award for Interpreting Chemistry for the Public. Central to Dr. Burks' research, teaching, and service is the central tenet that equitable, diverse, and inclusive spaces and practices both respect people and produce scientific outcomes of greater integrity. She is a member of several local, national, and international committees, task forces, and projects focused on social justice and STEM.
Fernando Pérez is an Associate Professor in Statistics at UC Berkeley and a Faculty Scientist in the Department of Data Science and Technology at Lawrence Berkeley National Laboratory. His research focuses on creating tools for computational research and data science across domain disciplines, with an emphasis on high-level languages, interactive and literate computing, and reproducible research. He is particularly interested in the intersection of physical models and machine learning in geoscience, to address critical problems such as climate change and environmental protection. He created IPython while a graduate student in 2001 and co-founded its successor, Project Jupyter. In 2021, IPython/Jupyter was named by Nature one of the "Ten computer codes that transformed science".
Pérez is a co-founder of the 2i2c.org initiative, the Berkeley Institute for Data Science and the NumFOCUS Foundation. He is a National Academy of Science Kavli Frontiers of Science Fellow and a member of the Python Software Foundation. He is a recipient of the 2017 ACM Software System Award and the 2012 FSF Award for the Advancement of Free Software. He holds a PhD in physics from the University of Colorado, Boulder, and did postdoctoral research in applied mathematics at the same institution.
Jim Bednar is the Director of Technical Consulting at Anaconda, Inc. Dr. Bednar holds a Ph.D. in Computer Science from the University of Texas, along with degrees in Electrical Engineering and Philosophy. He has published more than 50 papers and books about the visual system and about software development. Dr. Bednar manages the open source Python projects HoloViz, Panel, hvPlot, Datashader, HoloViews, GeoViews, Param, Lumen, and Colorcet. Before Anaconda, Dr. Bednar was a lecturer and researcher in Computational Neuroscience at the University of Edinburgh, Scotland, as well as a software and hardware engineer at National Instruments.
Australian National University
I'm an interdisciplinary researcher at ANU, currently working on a PhD in computer science - based on my open-source work on Hypothesis and property-based testing. I've previously spent several years working in cybernetics (research and education), and as a research software engineer in remote sensing and earth sciences, so it's super exciting to see so many scientists and maintainers adopting my testing tools!
When I'm not on the internet, you can probably find me either curled up with a good book and a lot of chocolate, or far out of contact along a deserted beach or deep in the Australian bush.
Conference Speakers & Authors
Academy for Mathematics, Science, and Engineering
Thomas Chen is a student researcher whose primary interests lie in machine learning and computer vision. He serves on the U.S. Technology Policy Committee of the Association for Computing Machinery. As much of his work lies at the nexus of artificial intelligence and earth science, he is also an active early-career scientist member of the European Geosciences Union and the American Geophysical Union. He enjoys using the Python programming language to conduct research that has real-world impacts. Previously, Thomas has presented work at a number of conferences, workshops, and meetings, from NeurIPS workshops, to Applied Machine Learning Days, to the Open Data Science Conference, to Machine Learning Week Europe.
Brendan is an expert in data science and geospatial technology and is Co-founder and Principal at makepath, a spatial data science firm in Austin, Texas. With over 15 years of experience in GIS, he has worked with The Nature Conservancy, World Resources Institute, New Forests, World Wildlife Fund, NASA, and The Bill and Melinda Gates Foundation. Brendan is actively involved in the PyData community and is a core developer for several open source libraries including Datashader and Bokeh. He recently created the Xarray-Spatial and mapshader libraries for large scale spatial analysis.
Imperial College London
Nataraj has 21 years of industry experience in developing the vision, strategy and execution of analytic capabilities in finance and pharmaceutical domains. Experience at IBM, UBS Investment Bank, UBS Wealth Management, Purdue Pharma, Philip Morris. He was the core architect of the RWE and Rx Data Analytics solution at Purdue Pharma which was spun out into a new startup, RxDataScience with over $ 3.5M in seed funding. He currently serves as the VP of Advanced Analytics at the firm.
Nataraj is a published author of multiple books on data science, journal articles and research papers in commercial market research, health outcomes, epidemiology and RWE Analytics. He has been a presenter, keynote speaker and Chairperson at over 20+ machine learning and AI-related healthcare conferences in US, Europe and Asia.
University of Michigan
Bradley Dice is a scientist and software developer researching nano-scale materials via computational simulations. He is currently a PhD candidate in Physics and Scientific Computing at the University of Michigan in Ann Arbor. He is a member of the Glotzer Group, a National Science Foundation Graduate Research Fellow, and a MolSSI Software Fellow.
Ralf has been deeply involved in the SciPy and PyData communities for over a decade. He is a core developer of NumPy, SciPy and PyWavelets, and has contributed widely throughout the SciPy ecosystem. Ralf is currently the SciPy Steering Council Chair, and he served on the NumFOCUS Board of Directors from 2012-2018.
Ralf co-directs Quansight Labs, which consists of developers, community managers, designers, and documentation writers who build open-source technology and grow open-source communities around data science and scientific computing projects. Previously Ralf has worked in industrial R&D, on topics as diverse as MRI, lithography and forestry.
Laura is SeMI's Community Solution Engineer. She works on everything UX & DX related to the open-source vector search engine Weaviate. For example, she is responsible for the GraphQL API design, and researches new machine learning features for Weaviate. She is in close contact with Weaviate's open-source community. Additionally, she likes to solve custom use cases with Weaviate, and introduces Weaviate to other people by means of Meetups, talks and presentations at conferences. In her free time she's active in sports, traveling, photography and likes to teach programming to kids.
Zoufiné Lauer-Baré obtained his PhD in applied mathematics in 2014 at the TU Kaiserslautern and the Fraunhofer Institute for Industrial Mathematics (ITWM), Kaiserslautern, Germany. Zoufiné Lauer-Baré worked two years in the data and workflow management in the Crash test simulation context in Ingolstadt, Germany. Currently, he works as simulation engineer in the development of electro hydraulic valves at Hilite International, using analytical, numerical and machine learning techniques in Nürtingen, Germany. Zoufiné is also an external lecturer at the Baden Württemberg Corporate State University, where he teaches programming with python and foundations of mathematics for data science students, as well as the Finite Element Method for engineering students.
S. Shayan Mousavi M.
Shayan Mousavi is a Materials Science and Engineering Ph.D. student at McMaster University. He holds a B.Sc. degree in Materials Science and Engineering from the Sharif University of Technology with a secondary concentration in Theoretical Mathematics. In his research, he investigates the photonic and optoelectronic properties of materials using various electron microscopy and spectroscopy techniques conducted at the Canadian center for electron microscopy (CCEM) and the Canadian light sources synchrotron facility (CLS). He implements a wide range of spectral analysis methods including machine learning- and deep learning-based techniques to refine, extract, and generate information from spectral data.
Karla is a Senior Research Software Development Engineer in the Gray Systems Lab (GSL) at Microsoft. She finished her PhD in Computer Science at the University of Maryland, College Park in 2015.
After graduating, Karla spent 3 years as a research scientist at Intel Labs and joined Microsoft in 2018. Her research interests are broad, and generally enjoys scalability and performance challenges related to systems infrastructure.
National Energy Research Scientific Computing Center
Rollin is a Data Architect and Computational Systems Engineer at the National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory in Berkeley, California. The last 5+ years he has helped hundreds of users on three different supercomputers use Python and Jupyter effectively to make discoveries in all areas of science supported by the US Department of Energy's Office of Science. He has led the NERSC Application Readiness Program for Data, and is the chief architect of NERSC's Jupyter service. He likes making supercomputing more accessible to scientists, and helping them succeed with Python.
Poster Presenters & Authors
I am a software engineer at NVIDIA, working on Clara -- a healthcare application framework for AI-powered imaging, genomics, and for the development and deployment of smart sensors, previously worked in the Camera team as a camera software engineer for Android/Linux camera module on NVIDIA Jetson/Shield platform. Before joining NVIDIA in 2015, I obtained a Ph.D. from Korea Advanced Institute of Science and Technology (KAIST) with a specialization in software testing and program analysis, with emphasis on the application of automated test case generation techniques to GUI software and unit-level code, and on empirical studies.
Corri por Aí
I am Marcel Pinheiro Caraciolo, living in Recife, Brazil. I am computer engineer with undergoing MBA on Technology for Business in Artificial Intelligence, Data Science and Big Data and Specialization in Agile Project Management. I am author of the runpandas scientific library for running activities data analysis.
My interests are product management, bioinformatics computing, data science, sports analytics and productivity. When I am not coding or managing, I often run (training hard to be a marathonist) and build and rebuild one of my collection of Lego Architecture sets.
KLS Gogte Institute of Technology, India
I hold Post Graduate Diploma in Cyber Laws and Cyber Forensics from the National Law School of India University Bangalore. I have presented talks at many conferences including PyData Global, JuliaCon 2018 and 2020, PyCon FR/HK/TW/ID/TZ/AU, COSCUP Taiwan, FOSDEM 2021, FOSSASIA 2021, PyCon Africa, BuzzConf, EuroPython, PiterPy Russia, SciPy India. Worked as a Reviewer and Program Committee member for reputed International conferences including SciPy USA, SciPy Japan, JuliaCon, JupyterCon, PyData Global, and PyCon India, and publishers include Manning USA and Oxford Univesity Press. I am also a GitHub Certified Campus Advisor. I lead the PyData Belagavi chapter and the OWASP Belagavi chapter. I am working as CFP Co-Chair for PyCon India 2021.
Senior year student, pursuing a Bachelor's in Technology, major in Electronics. I have been using Deep Learning for medical imaging for AI research. I have been publishing research articles in the Biomedical image processing domain, using segmentation and analysis. Speaker in PyCon Poland 2020.
IBM Center for Open Source Data and AI Technologies (CODAIT)
Romeo Kienzler is CTO and Chief Data Scientist of the IBM Center for Open Source Data and AI Technologies (CODAIT) in San Fransisco.
He holds an M. Sc. (ETH) in Computer Science with specialisation in Information Systems, Bioinformatics and Applied Statistics from the Swiss Federal Institute of Technology Zurich.
He works as Associate Professor for Artificial Intelligence at the Swiss University of Applied Sciences Berne and Adjunct Professor for Information Security at the Swiss University of Applied Sciences Northwestern Switzerland (FHNW). His current research focus is on cloud-scale machine learning and deep learning using open source technologies including TensorFlow, Keras, and the Apache Spark stack.
Recently he joined the Linux Foundation AI as lead for the Trusted AI technical workgroup with focus on Deep Learning Adversarial Robustness, Fairness and Explainability.
He also contributes to various open source projects. He regularly speaks at international conferences including significant publications in the area of data mining, machine learning and Blockchain technologies.
Romeo is lead instructor of the Advance Data Science specialisation on Coursera with courses on Scalable Data Science, Advanced Machine Learning, Signal Processing and Applied AI with DeepLearning
He published a book on Mastering Apache Spark V2.X (http://amzn.to/2vUHkGl) which has been translated into Chinese (http://www.flag.com.tw/books/product/FT363).
Recently, he published a book on "What's new in TensorFlow 2.x" with O'Reilly (https://learning.oreilly.com/library/view/whats-new-in/9781492073727/)
Romeo Kienzler is a member of the IBM Technical Expert Council and the IBM Academy of Technology - IBM’s leading brain trusts. #ibmaot
I'm currently the head of data science at DrFirst, a health tech company based outside of Washington, DC.
Outside of my work, I enjoy bicycling, climbing, photography, reading, cooking, basketball, music collecting, traveling, and volunteering. I love talking to people who are passionate about "ideas."
Greg is a scientific software engineer at Quansight with a background in medical imaging (magnetic resonance imaging). He is a maintainer for the open source scikit-image, SciPy, PyWavelets and pyFFTW libraries. He also has an interest in GPU computing and has been a frequent contributor to CuPy.
University of Oklahoma Health Sciences Center
Blaine Mooers is an Associate Professor of Biochemistry and Molecular Biology University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA. He is also a member of the Stephenson Cancer Center and serves as director of the Laboratory of Biomolecular Structure and Function. He earned a Ph.D. in Biochemistry and Biophysics with Professor P. Shing Ho at Oregon State University. He was a Howard Hughes Medical Institute fellow with Professor Brian Matthews at the University of Oregon. As a post-doc, he worked on problems in protein structure and design and RNA structure. His research interests include the role of RNA structure in the RNA editing system in trypanosomes. His lab uses X-ray crystallography, small-angle X-ray scattering, and molecular dynamics simulations. He also collaborates with colleagues on crystallographic studies to develop better anti-cancer compounds. He has been using Python and Jupyter to aid the analysis of his data for the past seven years. His research interests include developing software to improve computational workflows in structural biology. A Warren L. DeLano Memorial PyMOL Open-Source Fellowship funded some of this work. The National Institutes of Health currently funds his research. Contact him at email@example.com.
University Hospital of Basel
Background in computer science, business and finance. Worked for financial institutions on software engineering tasks, risk modelling and business transformation. Joined a health institution to be part of to the technological transformation of medical domain in Switzerland, contributing to AI modelling and putting MLOps into practise. Contributed to publications in all of the above mentioned fields. Big supporter of open-source projects, but only a small contributor. Having high hopes the latter one will change for the better.
Jyotika Singh is the Director of Data Science at ICX Media, where she manages and mentors her team as they work on NLP, feature engineering, machine learning, data analytics, research, distributed computing, social media data and audiences data using Python and Spark. She is an inventor of a patent on data science, classification and reclassification algorithms, processes and optimizations for media and audience marketing campaigns. Her efforts in driving data science and analytics at ICX along with introduction of new methods and processes have strongly contributed to reducing operating costs, securing new clients and achieving high double digit revenue growth in the past year with positive EBITDA.
She earned her Bachelor's in Engineering Hons. in Electronics and Communications Engineering from Birla Institute of Technology and Science, Pilani, Dubai (BITS) where she published multiple papers on her research in Signal Processing and Communications and earned a silver medal for the entire graduating class of 2014 and 1st rank for the Electrical Engineering class of 2014. She then earned her Master's in Science from the University of California, Los Angeles (UCLA) where she researched on signal and speech processing, developed novel approaches to remove noise from speech and worked on a variety of machine learning projects on image, text, user ratings, social media, entertainment and movies data. Outside her work, she enjoys working on a variety of problem solving techniques on text, audio and image data. She has opened multiple github open source projects, such as pyAudioProcessing, and has been a speaker at multiple conferences across the globe to share her findings and work with the Python and Data Science community. She is passionate about encouraging women in STEM and continues mentorship efforts to support the topic.
In her free time, she is big on spending time with family and friends, painting, sketching, art & decor, and trying out different sports.
Manasi Vartak is the founder and CEO of Verta, an MIT-spinoff building software to enable high-velocity machine learning. The Verta platform enables data scientists and ML engineers to robustly version ML models, collaborate and share ML knowledge, and when models are ready for graduation, to deploy and monitor models in production environments. Verta grew out of Manasi's Ph.D. work at MIT on ModelDB, the first open-source model management system deployed at Fortune-500 companies. Manasi previously worked on deep learning for content recommendation as part of the feed-ranking team at Twitter and dynamic ad-targeting at Google.