From left, photos of Zhen Han, Zahra Sharifnezhadazizi, and Katya Cherukumilli

Participants reflect on first Waterhackweek

April 30, 2019

The eScience Institute and the UW Freshwater Initiative co-hosted the first Waterhackweek, a five-day collaborative event for freshwater-related data science Mar. 25 – 29, 2019. We asked participants to give us their insight on the event, and three of them responded. Here are their thoughts.


A photo of Zahra Sharifnezhadazizi
Zahra Sharifnezhadazizi

Zahra Sharifnezhadazizi, PhD candidate, Department of Civil and Environmental Engineering, The City College of New York

I am pursuing a doctorate in environmental engineering at City College of New York (CCNY) where I am working on satellite remote sensing data analysis for environmental purposes. The main focus of my current research is remote sensing analysis of Land Surface Emissivity with high spatial and temporal resolution which makes me handling a huge volume of data using MATLAB. In order to be able to apply novel data analytics, I started to attend the Consortium of Universities for the Advancement of Hydrologic Science, Inc. Cyberseminar Series which introduced me to new horizons of data analysis with Python.

Honestly, I simply imagined that it would be one of those boring compact lectures in a few sessions. However, later events brought me a completely different view. At first, it motivated me to start a three-week online Python course. Then, I went on with the webinars and became familiar with all sets of new tools and websites such as Hydroshare workflow, Jupyter notebook, GitHub online version control, Google Earth Engine, and GeoPandas.

In the workshop week, we continued on those materials in detail and had a hands-on project. The final project was set up in a way that each person in each group, took part in their own personal interest and ability. There was no peer pressure of being obliged to do something for the sake of not just being left behind. Even the title of the projects was chosen by each group which made us start collaboration and negotiation from a smaller society.

The major interesting point for me was that the instructors were ranged from professors to students. In addition, the workshop had various types of participants, from undergrads to faculty members. Therefore, I thought I could also be an instructor if I have anything special to contribute.

Apart from that, the diverse milieu of the workshop in both terms of culture and science, and the welcoming nature of Seattle let me have this notion that organizers are not only proficient in technology, but also experts in social sciences. To my mind, Waterhackweek 2019 was an amalgamation of innovation, expression, learning, friendship, and joy, and I would be delighted to be part of this community once again.


A photo of Zhen Han
Zhen Han

Zhen Han, Big Water Consultants, Seattle

I had a wonderful time at the Waterhackweek. Within five days, I was able to pick up a lot of new data science techniques and directly apply those skills through hands-on project work. The instructors and organizations clearly put a lot of thoughts on the structure of the events to strike a balance between learning sections and project time.

Although there are a lot of contents to learn and practice within a short period of time, the learning environment during the hack week was extremely friendly and low-stress. I appreciate that at the onset of the event, all participants were reminded to get prepared to feel a little bit at loss, stay open-hearted to seek help and help each out, and appreciate the diversity of the participants.

The weekly one-hour cyber-seminars were great lead-ins for the hack week. It was great that we could get an overview of the contents and start to implement the tools before the event started. The learning sessions during the week were also well-structured and greatly expanded my horizon on tools and techniques for data science and water research.

More importantly, it was great to get exposure to a variety of projects and work in a diverse team on a hands-on project. My teammates came from consulting firms, academia, government, and non-government organizations. Everyone brought their own experience into the discussion and problem-solving process. I felt extremely grateful for the opportunity to learn from our team leads and my teammates.


Katya Cherukumilli, postdoctoral researcher, University of Washington

A photo of Katya Cherukumilli
Katya Cherukumilli

I am a postdoctoral researcher in Environmental Engineering at the UW and the founder and CEO of a nonprofit called Global Water Labs. My research focus is on the design and deployment of low-cost technologies for drinking water treatment in resource-constrained regions. My expertise is in analytical aquatic chemistry, material characterization, groundwater geochemistry, field-relevant technology design, and social entrepreneurship.

I do not have formal training in data science or programming but was recently introduced to Python and R/ggplot. So when I first heard the announcement for proposing projects for Waterhackweek (WHW), I was a bit hesitant because I thought that I did not think I had the adequate data science skillset to participate. However, having completed my first WHW experience, I am so happy that I did. I would recommend the experience to anyone who has a general interest in learning more about how data science skills can be applied to their research.

I had the privilege of leading a team of data scientists to work towards a common goal: to build a “map app” that visualized multiple groundwater contaminants, with the added user-friendly features of observing trends over time and space (including depth). This experience gave me a brief insight into the vast power of numerous tools and software packages, including Hydroshare, GitHub, Tethys, Google Earth Engine, and GeoPandas. It also taught me about the concepts of workflow, database wrangling/cleaning, and version control. These concepts, although quite rudimentary to experienced data scientists, were novel to an experimentalist like me.

Learning these concepts taught me how to do very interdisciplinary and highly productive collaborative research in a short period of time. Overall, through this experience, I was introduced to a unique and powerful network of data scientists passionate about water issues. I was also encouraged (and supported) to push my own intellectual boundaries and to learn new methods that will greatly contribute to my future research and humanitarian work.