Speakers & Presenters

Meet the speakers who make SciPy Japan fascinating. 

To all our speakers - thank you. 

Keynote Speakers

10/30  13:30-14:30

Ryo Yoshida

Professor, The Institute of Statistical Mathematics, Research Organization of Information and Systems

Machine Learning Technologies for Accelerating Discovery of Innovative Materials

The open source software XenonPy provides machine learning modules for various tasks in materials informatics. In this talk, I introduce some important technologies of machine learning, which would be key drivers to the next frontier of creative design and manufacturing in materials science. In addition, the potential applicability of XenonPy is illustrated on the discovery of new polymers exhibiting novel thermophysical properties and application to process control of the microstructure of composite materials, and so on.

Bio

Ryo Yoshida, a Professor for Department of Data Science at the Institute of Statistical Mathematics (ISM), has served as the director of Data Science Center for Creative Design and Manufacturing in ISM since the center’s opening in July 2017. After receiving his Ph.D. in Statistical Science from the Graduate University for Advanced Studies in 2004, he worked as a Project Assistant Professor for the Human Genome Center at Institute of Medical Science, the University of Tokyo – a position he has maintained after joining the ISM in 2007. In addition, he serves as an invited researcher for National Institute for Materials Science (NIMS). He received the IIBMP Research Encouragement Prize (2016 and 2017). He has the experience of using his expertise in data science for research work in both biology and materials science. He is leading the development of XenonPy–a machine learning platform for materials science. He is devoted to foster and practice machine learning technologies for creative design and manufacturing through industry-academia collaboration. In addition, he is devoted to creating the scientific foundation of materials informatics for polymeric materials and quasicrystals through some research projects founded by the JST-CREST program and the Japan Society for the Promotion of Science (JSPS).

10/31  13:30 - 14:30

Kaoru Kawamoto

Professor, Faculty of Data Science, Shiga University
Deputy Director of the Center for Data Science Education and ResearchFormer head of the Business Analysis Center, Osaka Gas Co.

 

The Business Supportive Data Scientist Work Approach
How can you make data analysis more than just an analysis, but an analysis leading to business outcomes? Based on my experience of repeated failures in my previous jobs, I’ve learned the causes of what goes wrong and the types of work that can be done to overcome them. The key point is to turn tacit knowledge into formal knowledge before embarking on data analysis.  In this talk I would like to systematize this method.

Bio

Graduated from Kyoto University in 1991 with a degree in Applied Systems Science and joined Osaka Gas. In 1998 started research at the Lawrence Berkeley National Laboratory in the U.S working on energy consumption data analysis. After returning to the company, he worked on promoting business reform through data analysis. In 2011, he served as director of the Business Analysis Center and established the data analysis organization. He was awarded the first Data Science of the Year by Nikkei Information Strategy, April 2018. He has been in his present position. Doctor of Engineering and Economics. He is the author of multiple books related to the power of analysis for changing company. He has also appeared on NHK professional documentary show. 

Talk and Turotial Presenters

Crissman Loomis

After starting Python programming while hacking the Pokemon Go API, Crissman joined the machine learning team at Preferred Networks, a Japanese startup. He has worked there for three years, focussing on documentation and presentations at programming conferences, like SciPy, GTC, and ODSC. His ODSC West workshop on Deep Learning was selected as one of the top 10 workshops for learning Machine Learning.

Genevieve Buckley

Genevieve Buckley is a scientist and programmer based in Melbourne Australia, and builds software tools for scientific discovery. Her interests include deep learning, automated analysis, and contributing to open source projects. She has a wealth of professional experience with image processing and analysis spanning x-ray imaging, fluorescence microscopy, and electron beam microscopy. She is a maintainer for the dask-image project.

Jyh-Miin Lin, MD, MSc, PhD

 

Education

2012–2016 Ph.D. Radiology, University of Cambridge

2005–2007 M.Sc. Department of Electrical Engineering, National Taiwan University

1999–2005 M.D. Department of Medicine, National Taiwan University

Academic Appointments

2019–2020 Senior Research Associate, CEA Grenoble

2018–2019 Research Associate, University College London

2016–2018 Postdoc, Department of Electrical Engineering, National Taiwan University

2011–2012 Post-doctoral (MD) research assistant, Duke University Medical Center, NC, USA

Matt Hancock

Matt Hancock is a senior scientific software developer at Enthought in Austin, Texas. He holds a PhD in applied mathematics from Florida State University, where he performed research related to image processing and machine learning for medical imaging problems.

Max Frenzel

Max Frenzel is an AI researcher, writer, and digital creative. He is the R&D Lead at Bespoke Inc. and author of the bestselling book Time Off: A Practical Guide to Building Your Rest Ethic and Finding Success Without the Stress. Max has also been interested in the applications of AI and deep learning to creativity, design, and music, and he is a regular public speaker on topics such as AI and creativity. In his time off, Max enjoys good coffee, tries to perfect his bread baking skills, and produces electronic music and performs around Tokyo. You can find him online at www.maxfrenzel.com.

Naoki Yoshii

Naoki Yoshii joined Tokyo Electron in 2002. He is mainly in charge of semiconductor process development, and currently supports the development of processes and materials using machine learning as a technology marketing.

Ram Rachum

Ram Rachum is a software developer specializing in Python. When he's not writing his biography in the third person, he's doing consulting work for clients big and small, giving Python training to teams that would like to deepen their Python skills, and organizing the bi-monthly PyWeb-IL conference. Python training: http://pythonworkshops.co/

Robert Crowe

Robert Crowe is a self-described data scientist and TensorFlow addict who has a passion for helping developers quickly learn what they need to be productive. He's used TensorFlow since the very early days and is excited about how it's evolving quickly to become even better than it already is. Before moving to data science Robert led software engineering teams for both large and small companies, always focusing on clean, elegant solutions to well-defined needs. You can find him on Twitter at @robert_crowe

Sandeep Subramanian

Sandeep Subramanian has a Masters in Computer Science and Engineering with a specialization in Machine Learning and likes to work on projects where Machine Learning meets Software Engineering.

Sayak Paul

Sayak Paul is currently working at PyImageSearch on Computer Vision and Deep Learning. His projects span across a wide variety of topics including model optimization, generative modeling, CRNN architectures, and so on. Previously at DataCamp, Sayak developed projects (Predicting Credit Card Approvals and Analyze International Debt Statistics), and practice pools (Advanced Deep Learning with Keras (requires a login to see)). Prior to DataCamp, he worked at TCS Research and Innovation (TRDDC) on Data Privacy. There, he was a part of the cyber security research team working on TCS’s critically acclaimed GDPR solution called Crystal Ball. His subject of interest broadly lies in the area of visual representation learning. He loves open-source initiatives and currently, he is actively contributing to TensorFlow Hub. Off the work, he likes writing technical articles, working on applied Machine Learning ideas, and giving talks at developer meetups and conferences.

Shotaro Ishihara 

Shotaro Ishihara is a data scientist at a Japanese media company, engaged in data analysis and service developments. While studying computer science at university, he was also involved in a university press. He has participated in machine learning competitions and has experiences of getting first place on a Kaggle competition, hosting a Kaggle Days Tokyo competition and publishing a technical book for beginners. The International News Media Association gave him “ 30 Under 30 Awards and Grand Prize” in 2020.

Sutou Kouhei

Sutou Kouhei is an Apache Arrow PMC member.

Tetsuo Koyama

Tetsuo Koyama is a CAE software engineer in Japan. He is interested in scientific computing and visualization with computer graphics. He's writing a self-published book entitled "Getting Started with GetFEM". This book is a Japanese translation of the Python interface tutorial from GetFEM, an open source finite element method library.

Wakana Nogami

Wakana Nogami is a Software Engineer at Mercari and is in charge of developing and maintaining image search system.