Contact info: joel.ostblom@proton.me

On the web: GitHub, GitLab, StackOverflow, LinkedIn

Professional Experience

Assistant Professor of Teaching
since Aug 2022

University of British Columbia | Department of Statistics
Teaching, curriculum development, and educational leadership initiatives. Mainly for the Masters of Data Science Program, but also for undergrad courses. Courses include computing platforms, data science ethics and privacy, version control, data visualization, supervised learning, and introduction to programming. I also serve as the adviser for the Data Science Minor at UBC.

Teaching Fellow
July 2020 - Aug 2022

University of British Columbia | Department of Computer Science
Postdoctoral instructor position mainly for the Masters of Data Science Program, but I also teach MBAN and undergrad students. Courses include computing platforms, data science ethics and privacy, version control, data visualization, supervised learning, and introduction to programming.

Data Scientist
Mar 2021 - June 2021

SBX BioSciences | Contractor
Performed literature review and advised on state of the art machine learning solutions for image analysis of pluripotent stem cell cultures.

Data Scientist
July 2020 - Dec 2020

Notch Therapeutics | Contractor
Developed workshops and notebook-based data analysis workflows for the research team with a focus on intuitive use for those with little coding experience.

Data Science Intern
May 2019 - Dec 2019

Generac Power Systems | Neurio Division
Clustered households based on energy consumption patterns to improve modeling strategies and to create consumer incentive for lower energy usage through gamification. Created interactive dashboards for internal use and learnt about project structure and code design.

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Data Analyst
Mar 2016 - Dec 2016

Ghana Medical Health | Contractor
Analyzed operational and market data. Published in the end of year report to donors.

Platform Developer
Feb 2015 - Oct 2015

FundingFinder | Startup
Designed an early prototype of a university scholarship SQL database & query form.

Research Assistant
Jul 2015

Tokyo Systems Biology Institute | Dr. Ayako Yachie
Constructed an RNA-sequencing pipeline with R (DeSeq2) & STAR and applied it to study differential gene expression in mouse stem cells.

Research Assistant
Jan 2014 - Jan 2015

Karolinska Institute | Department of Physiology & Pharmacology
Performed bioinformatic analyses of data from various biophysical-oriented stem cell projects in the lab of Dr. Michael Andäng.

Research Assistant
Aug 2013 - Dec 2013

University of Toronto | Institute of Biomaterials & Biomedical Engineering
Refined and enhanced the software I developed during my Master thesis project in the lab of Dr. Peter Zandstra.

Research Assistant
Sep 2011 - Jan 2013

Karolinska Institute | Department of Medical Biochemistry & Biophysics
Investigated inhibitory mechanisms for cancer stem cell growth and metastasis in the lab of Dr. Theresa Vincent.

Summer Internship
Jun 2010 - Aug 2010

Karolinska Institute | Department of Physiology & Pharmacology
Developed an in vitro training model for mouse skeletal muscle in the lab of Drs. Abram Katz & Håkan Westerblad.

Education

Ph.D. Biomedical Eng.
Jan 2014 - Aug 2020

University of Toronto | Institute of Biomaterials & Biomedical Engineering
Thesis: “Controlled Organization of Cell Fates in Spatially Confined Stem Cell Populations”. Investigated stem cell phenotypic heterogeneity and spatial organization, and developed software for novel analysis methods of high content imaging data in the lab of Dr. Peter Zandstra.
Courses: Stem cell engineering, bioengineering, applied bioinformatics, effective leadership.

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M.Sc. Biomedicine
Aug 2011 - Aug 2013

Karolinska Institute (courses & thesis) | University of Toronto (thesis)
Thesis 2nd year: Developed analysis software and applied it to highlight how the microenvironment impinge on early stem cell fate decisions in the lab of Dr. Peter Zandstra.
Thesis 1st year: Identified key genes in cell cycle driven gene expression fluctuations in pluripotent stem cells in the lab of Dr Michael Andäng.
Courses: Stem cell & developmental biology, regenerative medicine, bioinformatics, biostatistics, science communication, entrepreneurship.

B.Sc. Biomedicine
Aug 2008 - June 2011

Karolinska Institute (courses) | A*STAR Genome Institute of Singapore (thesis)
Thesis: Increased the reprogramming efficiency of fibroblasts five-fold through single amino acid mutagenesis of Sox17 in the lab of Drs. Prasanna Kolatkar & Larry Stanton.
Courses: Stem cell biology, immunology, neuroscience, cell biology, biostatistics, physiology, molecular oncology, biochemistry.

Publications

.

Two books, twelve articles, one manuscript in preparation, three acknowledgements, two invited talks, five poster presentations, and three reviewed papers. Authorship contribution is indicated in the left column.

Educational Leadership

Books

4th
Feb 2024

Data Science - A First Introduction with Python | 978-1032572239
Timbers, Campbell, Lee, Ostblom, Heagy. Freely available online. I co-led the adoption of the R textbook and its assessments to Python, including navigating the challenging task of translating concepts and code patterns from R into a different programming language and package ecosystem. As part of this effort, I contributed to the improvement of the R textbook and its assessments.

2nd
Oct 2021

Research Software Engineering with Python | 978-0367698348
Irving, Hertweck*, Johnston*, Ostblom* (shared second), Wickham*, Wilson. Freely available online. I was one of the main contributors to this software engineering resource, equivalent to two semester-long courses.

Acknowledgement
Jul 2018

Teaching Tech Together | 978-0-9881137-0-1
Wilson (ed.). Freely available online. Acknowledged (for content review & feedback) in this book on how to effectively teach computational topics.

Scientific Articles

1st
Jun 2022

Journal of Statistics and Data Science Education | 10.1080/26939169.2022.2074922
Opinionated practices for teaching reproducibility: motivation, guided instruction and practice. Ostblom* & Timbers* (shared first).

3rd
Jun 2019

Journal of Open Source Education | 10.21105/jose.00049
A graduate student-led participatory live-coding quantitative methods course in R: Experiences on initiating, developing, and teaching. Johnston, Bonsma-Fisher, Ostblom, Hasan, Santangelo, Coome, Tran, Andrade, Mahallati.

Talks & Posters

Invited Speaker
Sep 2023

UW Interactive Data Lab | Vega Developer Conference
I co-presented recent developments in Altair, and participated in discussion and descicion making on the future directions for the larger Vega ecosystem.

Poster Contributions
May 2023

Celebrate Learning Week via the Teaching and Learning Enhancement Fund (TLEF)
Bringing Accessible Data Science Training to Undergraduates.

Invited Panelist
Jul 2021

SciPy | Birds of a Feather
I represented Altair in this discussion on the current state and future opportunities for the Python visualization ecosystem together with the developers of HoloViews, Matplotlib, Seaborn, Plotly, Cartopy, VTK, Streamlit, Bokeh, and VisPy.

Biomedical Research

Scientific Articles

1st
In preparation

Not submitted
Control of spontaneous symmetry-breaking patterning in mPSC adherent colonies. Ostblom* (shared first), Aguilar-Hidalgo*, Siu, McMaster, Werschler, Tewary, Zandstra.

7th
Nov 2022

Stem Cell Reports | 10.1016/j.stemcr.2022.10.004
Virtual cells in a virtual microenvironment recapitulate early development-like patterns in human pluripotent stem cell colonies. Kaul, Werschler, Jones, Siu, Tewary, Hagner, Ostblom, Aguilar-Hidalgo, Zandstra.

6th
Mar 2021

Scientific Reports | 10.1038/s41598-021-85447-4
Endogenous suppression of WNT signalling in human embryonic stem cells leads to low differentiation propensity towards definitive endoderm. Dziedzicka, Tewary, Keller, Tilleman, Prochazka, Ostblom, (7 authors), Zandstra.

1st
Jan 2019

PLOS Computational Biology | 10.1371/journal.pcbi.1006384
Context-explorer: Analysis of spatially organized protein expression in high-throughput screens. Ostblom, Nazareth, Tewary, Zandstra. Awarded “editor’s pick” among all PLOS journals in the open source toolkit section.

3rd
Oct 2019

PLOS Biology | 10.1371/journal.pbio.3000081
High-throughput micropatterning platform reveals Nodal-dependent bisection of peri-gastrulation–associated versus preneurulation-associated fate patterning. Tewary, Dziedzicka, Ostblom, (13 authors), Zandstra.

13th
Mar 2019

Scientific Reports | 10.1038/s41598-020-62955-3
Functional arrays of human pluripotent stem cell-derived cardiac microtissues. Thavandiran, (11 authors), Ostblom, (10 authors), Zandstra.

3rd
Jan 2018

Molecular Systems Biology | 10.15252/msb.20177952
Modeling signaling-dependent pluripotent cell states with boolean logic can predict cell fate transitions. Yachie-Kinoshita, Onishi, Ostblom, Langley, Posfai, Rossant.

2nd
Dec 2017

Development | 10.1242/dev.149658
A stepwise model of Reaction-Diffusion and Positional-Information governs self-organized human peri-gastrulation-like patterning. Tewary, Ostblom, Prochazka, Zulueta-Coarasa, Shakiba, Fernando-Gonzalez, Zandstra.

Acknowledgement
Apr 2017

Nature Methods | 10.1038/nmeth.4258
Progenitor T-cell differentiation from hematopoietic stem cells using Delta-like-4 and VCAM-1. Shukla, Langley, Singh, Edgar, Mohtashami, Zuniga-Pflucker, Zandstra. Acknowledged for programming training and data analysis advice.

Acknowledgement
Jun 2015

Development | 10.1242/dev.117598
LIF signaling in stem cells and development. Onishi & Zandstra. Acknowledged for content review, literature research and discussions.

2nd
Dec 2013

Nature Methods | 10.1038/nmeth.2684
High-throughput finger-printing of human pluripotent stem cell fate responses & lineage bias. Nazareth, Ostblom, Lucker, Shukla, Alvarez, Oh, Yin, Zandstra.

2nd
Oct 2012

Seminars in Cancer Biology | 10.1016/j.semcancer.2012.05.007
Blebbing as a physical force in cancer EMT: Parallels with mitosis. Sekyrova, Ostblom, Andäng.

Talks & Posters

Invited Speaker
July 2021

The Biomedical Imaging and AI Cluster | Research Exchange Seminar
Control of symmetry-breaking in mammalian developmental models. Joint talk for a university-wide seminar.

Poster Presenter
May 2019

BC RegMed
Adherent pluripotent stem cells recapitulate symmetry breaking cell fate acquisitions of differentiating three-dimensional cell aggregates. 2nd place poster prize.

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Poster Presenter
Nov 2017

Till & McCulloch Meetings
Spatially organized gene expression heterogeneity in mouse pluripotent stem cells.

Poster Presenter
Jun 2015

International Society of Stem Cell Research | Annual Meeting
Emergence of distinct spatial expression patterns in human pluripotent stem cell colonies of confined sizes.

Poster Presenter
Jun 2014

International Society of Stem Cell | Research Annual Meeting
ContextExplorer: Exposing spatial organization of phenotypic heterogeneity in human pluripotent stem cell colonies.

Poster Presenter
Apr 2014

Institute of Biomaterials & Biomedical Engineering | Scientific Day
ContextExplorer: Exposing spatial organization of phenotypic heterogeneity in human pluripotent stem cell colonies.

Teaching Experience

.

The approximate number of students and the average of their offical course evaluation scores are listed in the left column as a rough indication of how each course was received (the max score is five and only the instructor-related evalutation questions are included).

Assistant Professor & Teaching Fellow

Lead Instructor
2022-23, 2x
10 weeks
160 undergrads
Rating: 4.1, 4.1

DSCI 100: Introduction to Data Science | Course site
This course covers data wrangling, visualization, classification, regression, clustering, inference, and version control. I’ve taught the course in both R and Python and was the second instructor to teach the Python version of the course. I co-led the development of the Python version including how to navigate the challenging task of translating concepts and code patterns from R into a different programming language and package ecosystem. I have also made multiple improvements to the course’s technical infrastructure and the R textbook and assignments.

Lead/Lab Instructor
2022-23, 2x
5 weeks
Undergrad level
Rating: 4.6, 4.3

DSCI 573: Feature and Model Selection | Course site
This course covers evaluation metrics for classification and regression, feature engineering, feature selection, feature importances, ensembles, and regularization. In 2022, I taught the lab sections and re-developed the assignments to adapt to the new content added to the course this year and to have more engaging scenarios for students to work with. In 2023, I taught both lectures and labs, and developed new slides for the course to illustrate concepts in an intuitive way and to incorporate active learning excerices in the classroom.

Lead Instructor
2020-23, 4x
8 lec | 4 labs | 5 weeks
160 master students
Rating: 4.7, 4.8, 4.8, 4.8

DSCI 531: Data Visualization 1 | Course site
Topics include effective data visualization with graphical grammars via Altair and ggplot. My first year as a teaching fellow I redeveloped the curriculum and turned this into a highly appreciated course after several years of receiving mixed feedback from students. Students especially appreciated the engaging assignment narratives (I storified all the assignments in this course based on both real and fictional scenarios), hand-drawn schematics, and learning R and Python in parallel. The second year I taught this course I added worksheets and developed autograding for all the lab assignments which led to both quicker student feedback, reduced TA workload, and more active student enagement during lecture as students were working on their worksheets for part of the lecture time. For the third iteration of the course I added additional questions during the lecture to have student engage more actively in thinking about visualization problems by discussing with each other in small groups during lecture time.

Lead Instructor
2021-23, 3x
8 lec | 4 labs | 5 weeks
90 master students
Rating: 4.5, 4.9, 4.6

DSCI 541: Privacy, Ethics, and Security
Topics include ethical considerations in topics related to data science and technology, such as the spreading of disinformation through recommendation systems, privacy concerns in collected data sets, and the fairness issues and bias in algorithms and datasets. My first year as a teaching fellow I redeveloped the curriculum and turned this into a highly appreciated course after several years of receiving mixed feedback from students. To address previous year’s concerns from students about such an important topic being taught from a single perspective, I curated content and assigned readings/videos from diverse stakeholders in data science fairness issues, which was appreciated by many of the students. The second offering of this course I further improved it by including plenty of student discussion questions during lectures and iClicker participation, which further increased the student engagement. The third iteration of the course, I addressed the need to have more data-based assigments and programming questions during the labs to improve the relevance and make the knowledge more applied and less prone to copy-pasting from chatGPT and similar tools.

Supporting Developer
2022
5 weeks
Undergrad level
Rating: 4.2

DSCI 430: Responsible Applications of Data Science
Based on my development of DSCI 541, I am now involved in a supporting role for the development of DSCI 430, which is an undergraduate course in Data Science Ethics.

Co-Developer
2021-22
10 weeks
Undergrad level
Rating: N/A

DSCI 320: Visualization for Data Science | Course site
I co-developed this new undergraduate course drawing from my DSCI 531 material and expertise in Altair. I worked together with a professor in the CS-department to combine our expertise on visualization both from a data-driven perspective with more theoretical CS knowledge about the underlying visualization techniques. Topics include analysis, design, and implementation of static and interactive visual representations; visualization literacy; data communication; exploratory data analysis; application of theoretical principles to visualization development.

Lead Instructor
2022
10 lec | 6 weeks
70 MBA students
Rating: 4.1

BAIT 509: Business Applications of Machine Learning | Course site
I taught this graduate course in the Master of Business analytics and further developed the teaching material from previous years. Topics include introduction to machine learning concepts, such as supervised learning, model training, model testing, and overfitting.

Co-Instructor
2021
16 lec | 10 weeks
320 undergrads
Rating: 3.7

APSC 160: Introduction to Computation in Engineering Design
This was the first time I taught a large undergraduate level course and I found it educational to learn about the differences between teaching at the undergraduate and graduate level. I had no impact on the content development of this course, but after noticing that there were several aspects of the course that hindered students’ learning, I wrote up and submitted feedback to the course directors with suggestions for improvements in the future. Topics include introductory programming with C.

Co-Instructor
2021-23, 3x
2 lec | 2 weeks
7 master students
Rating: 4.9, 5.0, 5.0

MEDI 504a: Emerging Topics in Experimental Medicine
I developed and taught the two ethics lectures of this one-semester course focusing on fairness and bias in data science. We explored ethical considerations in topics related to data science and technology, where the main areas of focus were what fairness means in a data science context, how to control for bias in algorithms and datasets, and privacy concerns in collected data.

Guest Lecturer
2021
1 lec | 1 weeks
40 undergrads
Rating: N/A

CPSC 330: Applied Machine Learning
I taught a data science ethics lecture in this course, similar to the material used for MEDI 504a, but adapted to an undergrad audience. The course instructor shared that they had received very positive feedback on the lecture from the students.

Co-Instructor
2021-23, 3x
Project-based | 8 weeks
12 master students
Rating: 4.9, 4.1, 4.8

DSCI 591: Capstone Project | Course site
The capstone project is a mentored group project based on real data and questions from a partner within or outside the university. I mentored three groups of four students focusing on visualization, unsupervised and supervised machine learning, and exploratory data analysis. Two of these groups were selected among the best capstone presentations by their peers, and all three capstone partners viewed the projects as highly successful.

Co-Instructor
2020-21
Online-based | Development
160 students/iteration
Rating: N/A

KCDS VIZ: Data Visualization | Course site
Part of the Key Capabilities in Data Science Program from UBC Extended Learning. I co-developed and taught this visualization course, which extends the material from DSCI 531 for a more general audience. This involved building the course into an open framework to distribute material and assess student performance, as well as recording videos to guide students through the curriculum. This course is repeatedly offered via the UBC extended learning platform

Lead Instructor
2020
8 lec | 4 labs | 5 weeks
90 master students
Rating: 4.9

DSCI 532: Data Visualization 2 | Course site
In this course students work in teams to design a dashboard (via Dash in R and Python) for interactive data visualization, exploration, and communication through iterative milestone-based progress. My first year as a teaching fellow I redeveloped large parts of this course and turned this into a highly appreciated course after several years of receiving mixed feedback from students. Since I taught this course during the pandemic there was no natural opportunity for students to engage with each other and see what inspiring dashboards their peers were developing. To address this I created a script that scraped all the student GitHub repos and put together a showcase gallery of all their work, and encouraged them to exchange suggestions and complements with their peers.

Lead Instructor
2020
8 lec | 4 labs | 5 weeks
130 master students
Rating: 4.8

DSCI 521: Computing Platforms for Data Science | Course site
This course teaches students how to install, maintain, and use software for the Unix command line, version control, and integrated development environments such as JupyterLab and RStudio. My first year as a teaching fellow I redeveloped half of the material in this course to address feedback that students had been struggling with version control concepts in previous years. I also created a script to verify that students have correctly installed our software stack, which alleviated the need to manually check this as in previous years, and improved a large part of the program’s installation documentation. I participated in the further development of these two resources and assisted throughout the course during my second year as a teaching fellow.

PhD Student

Teaching Assistant
Jan 2019 - May 2020

University of British Columbia
Assisting in three courses in the Masters of Data Science (Data Visualization; Data Wrangling; Privacy, Ethics, and Security), including leading a group of fours TAs for Data Visualization and assisting with content development for Data Wrangling. Created and taught a one hour seminar on intermediate pandas. Recognized with a TA award for outstanding work.

Course Creator
Dec 2019 - May 2020

University of Toronto | BME1478H
Co-developed and TAed the graduate level course “BME1478H: Coding for Biomedical Engineers”. Our curriculum allowed students to learn tidy data principles, develop a proficiency in coding while doing data analysis in Python, apply common statistical and basic machine learning techniques to biomedical data, and recognize the importance of and ensure reproducibility of analysis documents. This course was a success and has been further developed and taught in the department since we created it.

Student Supervisor
Jan 2019 - Dec 2019

University of British Columbia
Mentored two incoming PhD students, one during ten months and the other for a four months summer project. Taught wetlab techniques, microscopy imaging, data analysis, presentation skills, and scientific reasoning and writing.

Instructor
Jun 2018 - Oct 2018

Datacamp
Developed three teaching projects on data-wrangling, supervised and unsupervised learning using Python and R. Later made publicly available for free.

Workshop Developer
2018

UofTCoders
Lead the content development for three 2-day workshops on using Python for reproducible data analysis (based on data carpentry). Co-taught each session to ~30 participants.

Course Creator
2017 - 2018

Department of Ecology & Evolutionary Biology & UofTCoders | EEB313
As part of the student organization UofT coders I lead the development and teaching of a 4th year undergraduate course on how to conduct reproducible statistical analysis using R: “EEB313: Quantitative Methods in R for Biology”. We took initiative for the creation of this course since we identified these topics as important and lacking the graduate level university curriculum, and reached out to several departments to collaborate with. The course was positively received, the class size expanded, and incorporated into the department’s long-term curriculum. We published our experience in the form of a paper describing the course implementation.

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Workshop Instructor
2017

Digital Humanities Network & UofTCoders
Taught graduate students intro to computing and programming with Bash.

Workshop Instructor
2017-2018

UofTCoders & The Carpentries
Taught graduate students at six workshops. Topics including automation via the Unix shell, programming with Bash, & data analysis and visualization in Python.

Session Instructor
2018

University of British Columbia
Created a tutorial on interactive, reproducible reporting of scientific results using Jupyter Notebooks and plotly express. Taught as a two hour session for graduate students and postdocs.

Session Instructor
2017-2018

UofTCoders
Taught eight sessions for graduate students with topics including bash, Python, data analysis and visualization, vim, pandoc, and tmux.

Guest Lecturer
2017

University of Toronto | APS106
Taught high level overview of image analyses with Python.

Teaching Volunteer
2015-2017

Let’s Talk Science & Stem Cell Talks
Taught basic stem cell science to high school students, elementary students, kids, and parents (four separate occasions).

Teaching Volunteer
2016

University of Toronto | BME346H1
Taught high-throughput microscopy & image analyses to undergrads as part of BME346H1-Omics.

Student Supervisor
2014

University of Toronto
Co-supervised a 4th year thesis student, primarily in data analyses techniques of high throughput imaging data.

Teaching Merits

Course Design Intensive
May 2023

Centre for the Integration of Research, Teaching, and Learning at UBC
An intensive week-long program, where we learned about and worked on re-designing a course of our choice. Focus on both learner activities, assessment strategies, and learning outcomes.

Curriculum Developer
Apr 2022 - Sep 2022

Curriculum Lead for Plotly (pro bono)
I co-lead the development of a one semester long dashboarding curriculum at Plotly based on the DSCI 532 course we created at UBC. We were invited by Plotly due to our expertise in this area.

CIRTL Associate
2021

Centre for the Integration of Research, Teaching, and Learning at UBC
Eight lectures over eight weeks on the Foundations of Pedagogy. Specifically how to design and teach effective lessons using evidence-based teaching concepts with emphasis on alignment of learning objectives, activities and assessment.

Hackathon Mentor
2021

ESDC Integrity | Hackathon
Teams worked with Service Canada to identify and collect useful business information from openly available sources and extract valuable insights from it. I mentored the winning team in the competition, and assisted several other teams as well.

Ally Skills Workshop
2020

University of British Columbia | Master of Data Science
One day training in how to best act as an ally when responding to and preventing racism, sexism, transphobia, and other kinds of oppression.

Instructor Training
2019

University of British Columbia | Master of Data Science
Two days of lectures and hands-on training on effective teaching as a teaching fellow at MDS.

Host & Mentor
2018

Mozilla | Open Leadership Program
Hosting sessions for 30 participants and closely mentoring one student in how to develop for, work in, and lead open projects.

Data Science Teacher
2016 - 2018

Personal Project
Created several narrative teaching notebooks for data science.

IT & Education Lead
2015 - 2016

Engineering World Health | UofT Chapter
Involved in founding this UofT student chapter and lead the IT and Education teams. Our chapter sent members to work in low-resource hospitals and developed a low-cost vaccine carrier project. We received the chapter of the year award in 2016 outperforming 43 other university chapters worldwide.

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TA Training
2018 & 2019

University of Toronto & University of British Columbia
Attended two lectures on how to effectively communicate with students and resolve conflicts.

Workshop Helper
2017-2018

UofTCoders & The Carpentries
Assisted at seven workshops for graduate students. Topics included Unix, git & GitHub, image analysis, data analysis in R & Python.

Study Buddy
2013

Stiftelsen Läxhjälpen
Assisted students in socio-economically vulnerable areas to increase their high school enrollment rates.

Openness & Software

Steering Committee
since 2023

Vega | Website
I am on the steering committee for the Vega ecosystem, which decides the future direction for the Vega, Vega-Lite, and Vega-Altair visualization packages.

Core Maintainer
since 2022

Vega-Altair | Website
I co-maintain the popular Pyton visualiztion library Vega-Altair, which produces effective interactive visualizations with a minimal amount of code. This is one of the most downloaded visualization packages for Python with ~14M downloads/month.

Dashboard Developer
since 2018

Nutrimap | Website (wait for the page to load initially)
Interactive dashboard for visualization of nutritional data to facilitate comparison of food items and make them easier to understand to a broader audience and promote healthy food choices. This is deployed on static web server by using pyscript, and pyodide via panel.

Open Source Contributor
since 2015

I value openly sharing knowledge and code and giving back to projects that benefit me, which I have done through contributing (opening or commenting) to ~2000 issues and PRs on GitHub and GitLab. I have also created the following software:
• altair-ally a Altair companion package that facilitates exploratory data visualization.
• canvascli A CLI to reformat and review Canvas grades.
• session-info A minimal measure to increase reproducibility notebooks and scripts.
• context-explorer Aggregates and visualizes high throughput microscopy data.
• spiral-tile Stitches and normalizes microscopy images.
• Minor to intermediate contributions to several well-known software packages: altair, vega-lite, plotly, seaborn, pandas, matplotlib, jupyterlab, jupyter-book, jupytext, nbconvert, otter-grader, shap, holoviews, watson, zotero-cli, the ranger file browser, vim-pandoc, vim-rmarkdown, csv.vim, pdf-annots, quarto, phageParser, python java-bridge, and the Python social sciences data carpentry lecture.

StackOverflow Contributor
since 2013

Volunteer
Top 0.5% of contributors with an estimated 23 million people reached since 2013 through commenting on and answering ~1100 questions and voting on ~4,000. I contribute to StackOverflow because I value openly sharing knowledge to make it accessible to all.

Open Science Advocate
2019 - 2022

ROStools | Website
I was one of the lead developers of the ROStools specification (and future toolkit) for structured analytical workflows in open reproducible scientific projects. Many of the principles developed here created a foundation for the R-cubed data analysis courses.

Topic Expert
2019 - 2020

Mozilla | Open Leadership Program
Provided support as needed for participants in the open leadership program.

Openness Mentee
2018

Mozilla | Open Leadership Program
Four months mentorship and training on how to work openly and lead open access projects. Lead a global sprint session for my project with several contributors.

Other merits & training

Framework Developer
since 2023

BC Cancer | Research Ethics Office
Assisted in the development of a framework to evaluate clinical trial proposals involving machine learning.

Infrastructure Lead
2016 - 2020

University of Toronto | Zandstra Stem Cell Bioengineering Lab
Responsible for evaluating and purchasing $400,000 imaging and computational equipment (saving $600,000 compared to competing suggestions). Setup and management of the lab’s computational infrastructure, including three Linux workstations, reproducible Google Suits workflows for 30 people, identifying proper backup solutions for ~100TB data, and designing a data management plan.

Project Management
Feb 2018 - Mar 2018

MITACS | Foundations of Project Management 1 & 2
Four days of hands-on courses on project management, team dynamics and leadership.

Team Productivity
Feb 2018

MITACS | Essentials of Productive Teams
A one-day hands-on course on how to participate in and lead an effective team unit.

Time Management
Mar 2018

MITACS | Time Management
One day workshop on how to effectively manage time during project-based work.

Case Finalist
2016

IMS Brogan
Performed data analysis in a team of three for a consulting case competition. We reached the final round and were accredited as the team with the most data-driven insights.

Leadership
Jan 2016 - June 2016

University of Toronto | APS1010H
One semester course in the cognitive and psychological foundations of effective leadership.

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Student Ambassador
2014 - 2017

Karolinska Institute
Assisting exchange students from Karolinska Institute at the University of Toronto.

RNA-seq analysis
Mar 2016

Stem Cell Network
Two day workshop on how to analyze RNA-sequencing data in R.

Commercialization
Feb 2016

NSERC | M3 Create
A two-day workshop in public speaking, collaboration, negotiation and IP/patent law.

Translation Volunteer
2015

SCOPE
Translated stem cell blog post to Swedish.

Communication
Jun 2014

Stem Cell Network
One day workshop on effective scientific communication to both professional and lay audiences.

Prewriting
Oct 2013

University of Toronto
Eight lectures on strategies for developing & organizing ideas.

Vice President
2012

Biomedical Student Section
Coordinated program-wide activities to improve the student environment.

Board Member
2011

BRO
Worked to connect Biomedical students across Sweden. Also served as webmaster.

Board Member
2010

Biomedical Program Committee
Assisted in program development to improve the education at Karolinska Institute.

Hockey Player
1995 - 2008

Various teams
Played competitive ice hockey until age 21, including in the Swedish J20 SuperElit division and ACHA college hockey in the US. Provided leadership at youth and competitive levels as team captain and assistant captain on several teams.

Grants

.

Total amount: CAD 249,000

OER Implementation Grant
2024

University of British Columbia
Lead applicant. For creating and publishing an open access textbook on data visualization.

Teaching and Learning Enhancement Fund
2023

University of British Columbia
Co-applicant. Promote AI literacy, Renew curricula to teach AI skills, and combat AI cheating in courses at UBC.

Skylight Grant
2023

University of British Columbia
Lead applicant. For investigation of generative AI performance on different assessments and development of guidlines.

OER Implementation Grant
2023

University of British Columbia
Co-applicant. For creation and publishing of open access textbook on introductory data science in Python.

Awards

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Total amount: CAD 140,000

OER Excellence and Impact Team Award
2024

University of British Columbia
For outstanding work done by faculty at both UBC campuses who materially advance the use and impact of open educational resources in credit courses at UBC.

Open Source Peer Bonus
2023

Google
For going above and beyond in making great open source contributions during my work on the Altair visualization package.

Editor’s pick
2019

Public Library of Science
Picked among all PLOS journals in the open source toolkit section.

TA Award
2019

University of British Columbia
For outstanding contributions to the Master of data science program.

NSERC M3 Create
2015 & 2018

Natural Sciences & Engineering Research Council of Canada
To streamline translational research training among students.

International Scholar
2014-2017

University of Toronto
In support of excellent international students at IBBME, University of Toronto.

Gålö Higher Education
2014 & 2016

Gålö Foundation
In support of outstanding students participating in higher education outside of Sweden.

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Loo Geok Award
2015

University of Toronto
For outstanding academic achievement & extra-curricular leadership.

Milligan Award
2014

University of Toronto
In recognition of the student’s research accomplishments.

Essay Award
2013

Karolinska Institute
Second place exchange studies essay competition.

INK Scholarship
2013

Karolinska Institute
Master Thesis exchange studies in Toronto.

Research Scholarship
2011-2013

Karolinska Institute
Support for part time research in parallel with my Master studies.

INK Scholarship
2011

Karolinska Institute
Support for Bachelor Thesis exchange studies in Singapore.

Inspirational Poster
2011

Karolinska Institute
Master thesis poster selected as inspirational poster for incoming students.

Inspirational Article
2009

Karolinska Institute
Summer internship article selected as inspirational article for incoming students.

Research Scholarship
2009

Karolinska Institute
Financial support for summer laboratory internship.