In the September 4, 2019 update:
- The Environmental Data Initiative
- Upcoming Campus Events
- Upcoming Training and Workshops
- Campus Opportunities and Groups
- External Opportunities
- Featured Course Offerings for Fall 2019
- unsure which campus data and computing resources you need for your research?
- interested in making connections and starting new collaborations with data scientists and other researchers on campus?
- looking for training in data and computing skills?
The Data Science Hub can help! Send an email to the Data Science facilitator (email@example.com) or come by Hub Central in the Discovery Building during office hours (Th 3:00-5:00 PM). Sarah will also be at Open Coding Lab in Steenbock Library (T 2:30-4:30 PM). Check calendar for latest details and updates.
The Environmental Data Initiative is an NSF-funded project at the UW Madison accelerating curation and archive of environmental data, emphasizing data from projects funded by the NSF DEB. Programs served include, but are not limited to, Long Term Research in Environmental Biology (LTREB), Organization for Biological Field Stations (OBFS), MacroSystems Biology (MSB), and Long Term Ecological Research (LTER). EDI is committed to enable data that is Findable, Accessible, Interoperable, and Reusable (FAIR). EDI provides support, training, and resources to help archive and publish high-quality data and metadata. They operate a secure data repository and work closely with the LTER Network Communications Office and DataONE to promote data management best practices and stewardship.
Upcoming Campus Events (Calendar View)
Center for Demography of Health and Aging (CDHA) Training Seminar: 2:00pm-3:15pm, 8417 Sewell Social Science Building
Sept 4, Reproducible Research, Lars Vilhuber (Cornell Economics)
Applied and Computational Mathematics Seminar (ACMS): 2:25pm, 901 Van Vleck Hall
Sept 6, TBA, Leonardo Andrés Zepeda Núñez
Sept 13, TBA, Daniel Floryan
Statistics Seminar: 4:00pm, 140 Bardeen
Sept 4, Statistical Analysis and Spectral Methods for Signal-Plus-Noise Matrix Models, Joshua Cape
Sept 11, TBA, Alfredo Canziani
Computing in Engineering Forum 2019, Sept 10-11, Discovery Building
This two day event brings together on- and off-campus parties to exchange ideas and learn from each other through showcasing emerging technologies, networking, and providing opportunities for cross-pollination.
Systems, Information, Learning, and Optimization (SILO) Seminar, 12:30pm-1:30pm, Orchard View Room, Discovery Building
Sept 11, TBA, Alfredo Canziani
The Wisconsin Association for Computing Machinery – Women in Computing (WACM-W) meets every month on the first Tuesday of each month.
Oct 1, 12:00pm-1:00pm, Computer Sciences 2310.
Upcoming Training and Workshops
Software Carpentry – Sept. 11, 18, 25, Oct. 2 & 9, 2019
Software Carpentry aims to help researchers get their work done in less time and with less pain by teaching them basic research computing skills. This hands-on workshop will cover basic concepts and tools, including program design, version control, data management, and task automation. Participants will be encouraged to help one another and to apply what they have learned to their own research problems. Event hosted by the Data Science Hub. Registration is now open.
Data Carpentry – Sept. 11, 18, 25, Oct. 2 & 9, 2019
This hands-on workshop teaches basic concepts, skills and tools for working more effectively with data acquired in research. The workshop is for any researcher who has data they want to analyze, and no prior computational experience is required. Event hosted by the Data Science Hub. Registration is now open.
R workshops for Researchers
UW-Madison libraries are offering R programming Workshops on R programming for researchers. The content will cover useful skills for anyone working with tabular data. Later sessions go beyond the Data Carpentry Lessons to cover how to use git version control within R Studio and writing reproducible reports using RMarkdown. Registration is by workshop, not for the entire series. A full list of workshops and registration information can be found here.
Data Wrangling in Stata
“Data Wrangling” is the process of preparing data for analysis, which includes importing, cleaning, recoding, restructuring, combining, and anything else data needs before it can be analyzed. In this class you’ll learn how to wrangle data using Stata. The course dates are 9/11, 9/16, 9/18, 9/23, 9/25, 9/30, and 10/2 (9:00 – 12:30). Note that this class is a series and you should plan on attending all of the sessions. If you are interested, you can register here.
Next Gen. Microbiome Analysis Series
In cooperation with Microbial Science, the Microbiome Hub, the Bioinformatics Resource Center (BRC) – UW Biotechnology Center (UWBC) – is announcing the microbiota series hands-on workshops for FALL 2019: with
R and with
|Microbiota Processing in
|Microbiota Analysis within
|Microbiome Analysis using QIIME2||10/21/19||https://go.wisc.edu/3pgqmn||$175|
Location: UW-Biotech Center / room 1360, all-day workshops.
* Location: UW-Biotech Center / room 5406. ~2h workshop.
UW Extended Campus Coding Bootcamp
The digital revolution has transformed virtually every area of human activity—and you can become part of it as a web development professional. UW Extended Campus Coding Boot Camp is a live, online Full Stack Flex course with a part-time schedule that gives you the knowledge and skills to build dynamic end-to-end web applications and become a full stack web developer in 24 weeks. Designed to fit into the lives of busy adults and working professionals, the program features convenient online classes in real-time, with evening and weekend sessions. We pair live classes with in-depth, curated resources to reinforce knowledge and supplement those days you can’t make the live session. You can learn more here.
Campus Opportunities and Groups
Special Session on Recent Trends in the Mathematics of Data
In a collaboration between the NSF TRIPODS Institutes at the University of Wisconsin-Madison (IFDS), the Ohio State University (TGDA@OSU), and the University of Arizona (UA-TRIPODS), this special session will cover a number of mathematical areas of relevance to data science, including topological data analysis, stochastic processes on graphs, optimization theory and more. A particular emphasis will be on recent work at the critical trans-disciplinary interface of mathematics, computer science and statistics. The event will be held in Van Hise Hall, Room 104 on September 14-15, 2019. Additional details can be found on the event website.
Teaching and Learning Data Steward
The Division of Information Technology (DoIT) is currently seeking candidates for the Teaching & Learning Data Steward with applications due September 9, 2019. The person in this position will be part of a dynamic learning data team situated in DoIT Academic Technology’s (DoIT AT) Evaluation Design & Analysis (EDA) service. The data professionals in this service provide expertise on how to leverage data to better support teaching and learning across the university. For more information and to apply, please see the job posting here.
Data Wonks Community of Practice
The Data Wonks (formerly known as the Ad Hoc Query Writers CoP) is a UW-Madison Community of Practice for individuals who work with campus data and the provided tools. The next meeting of the Data Wonks is 9/11 from 12:00-1:00 in Bascom Hall. This is one in a series of semi-monthly meetings. The topic this month is Writing Queries in Toad Data Point and is presented by Nick Sigmund, Policy and Planning Analyst.
Computational Biology, Ecology, and Evolution (ComBEE)
ComBEE is a group of researchers at UW-Madison interested in computational biology in ecology and evolution. ComBEE offers R, Python, and Julia study groups throughout the semester. Checkout their website and sign up for their email lists for more information. Better yet, consider joining them at their social on Friday, September 6 from 3:30-5:00 pm in 6201 MSB.
Computational Plant Sciences (ComPS) Group
A common problem both bench and field plant scientists face is that advance in high-throughput measurement platforms have outpaced our ability to readily analyze the datasets produced. To help solve this problem, the researchers in Plant Sciences formed a community of practice, a peer-to-peer mentoring network that will work across lab, departmental, and college boundaries to help plant scientists build computational and data science skillsets. Monthly meetings are held on the first Tuesday of each month at noon in 1153/54 Discovery.
Midwest Computational Biology Workshop
The 2019 Midwest Computational Biology Workshop (September 12-13 @ Toyota Technological Institute at Chicago) will explore emerging topics in the field of computational biology, covering a spectrum of algorithmic and machine learning challenges to address biological questions. The workshop will bring together a wide range of participants from different backgrounds and positions and also aims to initiate new interdisciplinary interactions and collaborations. This workshop is part of the 2019 TTI-Chicago Summer Workshop Program. Additional funding has been graciously provided by the National Center for Brain Mapping (NCBM).
Syngenta Crop Challenge in Analytics
Today, the agriculture industry works to maximize the amount of food gained from crops by breeding plants with the strongest, highest-yielding genetics. Plant breeding is complex, and data analytics can help scientists at research and development organizations like Syngenta make advances in seed product development. Developing models that can predict the performance of potential corn products can help scientists more accurately select seeds that increase the productivity of the crops farmers plant – and will help address the growing global food demand. The challenge gives students the opportunity to test their analytical skills by using real-world data to develop a model that applies analytics in new, creative ways to help feed our growing population. Check out their website to learn more.
Workshop on Distributed Estimation and Control in Networked Systems (NECSYS)
NECSYS is a two-day workshop consisting of a single-track set of talks and a couple poster sessions. The workshop covers a wide range of topics of interest to engineers, computer scientists, and optimizers, including: Multi-agent systems, Control under communication constraints, Consensus and gossip algorithms, Decentralized and cooperative control/estimation, Distributed optimization and MPC, Cyber security in networked control systems, Event-triggered and self-triggered control, Wireless sensing and control systems, Graph-based methods for networked systems, Cooperation in the presence of adversaries, and Networked games. For more information, check out the NECSYS website.
National Science Policy Network (NSPN) Symposium
Catalysts for Science Policy is hosting the NSPN’s annual symposium here in Madison, WI on November 1-3, 2019. This year’s theme is “Leveraging Science and Technology to Benefit Marginalized Populations.” The symposium features speakers, workshops, and 300+ attendees. Information about the symposium can be found here. Early bird registration ends August 30 and individuals who qualify to become NSPN members can receive a 50% discount.
Big Data Neuroscience Workshop
This workshop will continue work on the development of common practices and standardization to make it easier for neuroscience researchers to annotate and process data; to share data, tools and protocols, and to work with distributed high-performance computing environments. The workshop will bring together members of the Midwest, national, and the global neuroscience research community to promote data reuse, aggregation, result validation and new discoveries in neuroscience. Program and registration details can be found here.
Data Science Forum 2019
September 17 – 18, Cornell University, Ithaca, NY
The Data Science Forum is an opportunity for institutions of higher education to share ideas, perspectives, and solutions designed to extract value from our institutional data. Broad topics will include: data and infrastructure strategy; hiring the “right” expertise; big data, machine learning, and statistical modeling; privacy and legal concerns; and pitfalls and success stories. They would like to have as many institutions as possible participate in these discussions. To that end, they ask that you send at most two representatives from your institution. If in addition to your two representatives you have a speaker well suited to one of the topics listed on the registration form, please contact Cecilia Earls for special consideration.
Deep Learning: Mathematical Foundations and Applications to Information Science
The IEEE Journal on Selected Areas in Information Theory (JSAIT) seeks high quality technical papers on all aspects of Information Theory and its applications. JSAIT is a multi-disciplinary journal of special issues focusing on the intersections of information theory with fields such as machine learning, statistics, genomics, neuroscience, theoretical computer science, and physics. This special issue will focus on the mathematical foundations of deep learning as well as applications across information science. Prospective authors are invited to submit original manuscripts on topics within this broad scope including, but not limited to: Information theoretic methods for deep learning, robustness for training and inference, understanding generalization in over-parametrized models, efficient and compressed model representations, deep generative models and inverse problems, large-scale efficient training of large models, non-convex optimization in deep learning, and deep learning for source and channel coding. For details and templates, please refer to the IEEE Journal on Selected Areas in Information Theory Author Information webpage. All papers should be submitted through Scholar One by October 1, 2019.
Featured Course Offerings for Fall 2019
Computational Network Biology Course – This course surveys the current literature on computational, graph-theoretic approaches that use network algorithms for biological modeling, analysis, interpretation and discovery. The material covered in this class will come from published literature, review articles, and selected book chapters. Students will participate in discussions of papers and gain hands-on experience in network biology by implementing class projects. This class should be of interest to students from multiple disciplines including computer science, engineering, math, statistics, microbiology, biochemistry and genetics. Learn more here.
Forensic Science and Law Course – Taught by Professors Jo Handelsman (Plant Pathology) and Kieth Findley (Law), this is the first course at the University of Wisconsin—and among the first in the nation—to bring together law students and graduate students in STEM to examine law and forensic science together. The course will focus on the legal system and processes, the fundamentals of science and the challenges confronting the forensic disciplines, and close scrutiny of many of the dominant forensic techniques used today. Find PL PATH 875-005 (66958) in the UW course guide. The class meets 4:10-5:30 pm on Tuesdays and Thursdays in the Discovery Building.
If you have a course you would like us to feature, please send us an email at firstname.lastname@example.org.
Check calendar for latest details and updates for all listed events. If you have a relevant event or group you’d like to see included in next month’s newsletter. Please send us an email at email@example.com.