Democratizing science education & training, leveling playing fields, and improving access to (& entry into) our work are intertwined core values of our group.
We actively engage in a number of education and outreach activities such as teaching non-traditional courses, offering professional development workshops to graduate students & postdocs, supporting diversity/inclusion initiatives, and giving public talks/lectures about our research.
Find out more
Teaching: Courses, Workshops
Bioinformatics and Computational Biology
Spring 2018 – Present | This course is an introduction to the inner workings of methods in bioinformatics and computational biology: analytical techniques, algorithms, and statistical/machine-learning approaches developed to address key questions in biology and medicine. In this course, students will also learn how to formulate problems for quantitative inquiry, design computational projects, think critically about data & methods, do reproducible research, and communicate findings.
Gaps, Missteps, and Errors in Statistical Data Analysis
Fall 2018 – Present | This is a short (1-credit) intermediate-to-advanced course designed to:
1) Discuss common misunderstandings & typical errors in the practice of statistical data analysis.
2) Provide a mental toolkit for critical thinking and inquiry of analytical methods and results.
This course builds on your introductory knowledge of statistics and programming. Topics include: Underpowered statistics • Pseudoreplication • P-hacking & multiple hypothesis correction • Difference in significance & significant differences • Base rates & permutation tests • Regression to the mean • Descriptive statistics & spurious correlations • Estimation of error and uncertainty
Modular Courses in Bioinformatics
We offer several modular bioinformatics courses each semester including:
R Programming for Bioinformatics
Python & HPCC for Bioinformatics
Statistical Analysis and Visualization
Transcriptomic Data Analysis
The bioinformatics modules are a set of introductory courses that help life science students learn basic skills in computation and bioinformatics. These modules are 1 graduate credit, one month long, and (mostly) flipped classroom (students watch video lectures online for homework and then come to class to solve problems and ask questions). Postdocs, staff, visiting scholars, faculty, and other MSU-affiliates who are not students can audit these modules for a nominal fee. Contact the Bioinformatics Program Coordinator to register. Undergraduates at the junior/senior level who wish to take the modules should also contact the Coordinator to discuss their eligibility. Undergraduates who are taking the CMSE minor and wish to take the modules should contact the CMSE Undergraduate Director.
[Past] Introduction to Computational Modeling & Data Analysis
In Fall 2019, Arjun taught one of CMSE’s flagship undergraduate courses that uses the flipped class model to teach various aspects of computational science, a variety of practical, fundamental computational skills, and application-driven modeling of various systems, with applications to the physical, life, and social sciences, and also to engineering and mathematics. Each class throughout this course involves a range of activities – primarily by writing software both individually and in small groups, but also through discussion, presentations, and other types of exercises.
[Past] University-wide Bioinformatics Workshops at MSU
In Spring 2017, Arjun helped design the Modular Courses in Bioinformatics at CMSE and then piloted all the materials by conducting three 1-week Bioinformatics Workshops in Summer 2017. These bioinformatics workshops provided hands-on training in Linux/R/Python programming, Statistical data analysis and visualization, and Analysis of various types of genomic data (e.g. RNA-seq) to 32 members of the MSU community including undergraduates, PhD students, and faculty members. These course materials form the basis of the 1-credit Bioinformatics modular course subsequently taught every semester by others starting Fall 2017, which up to now has been taken by 142 students.
Surviving and excelling in your PhD
This is a workshop for graduate students, organized as three parts:
Part 1: Ten things to do as a student that will set you up for a great PhD experience.
Part 2: Good Lab Practices - to foster well-rounded development of graduate students.
Part 3: Career Development Week - to define and measure immediate, tangible growth opportunities.
Planning and executing an effective postdoc
This is a workshop for postdocs, organized in three parts:
Part 1: Postdoc Career Planning Document: a plan for where you're going next
Part 2: Yearly Planning Meeting: a plan for year-round research progress and professional development
Part 3: Career Development Week: an activity to define and measure immediate, tangible growth opportunities.
Faculty job search
This is a presentation and discussion on the lessons Arjun learned from his faculty job search. It includes: i) The things I did and the things I didn’t, but wish I did, ii) The timeline, iii) What a good application package looks like, iv) How to apply effectively, and v) How to navigate the interview process.
R-Ladies East Lansing
R-Ladies EL – a local chapter of R-Ladies Global – is a non-profit organization that provides a safe space for women and gender-minorities to learn and discuss R (a popular programming language) and data science. The EL chapter was founded in July 2018 (by Dr. Janani Ravi) and this grassroots organization has grown rapidly and become an integral and essential part of the broader MSU community, collectively training, connecting, and inspiring more than 500 members of the broader MSU community. Members of the Krishnan Lab, Kayla Johnson and Dr. Stephanie Hickey, are part of the leadership team of R-Ladies EL and Arjun serves as the chapter's faculty advisor. Thus far, R-Ladies EL has conducted >25 events – Workshops, Lightning Talks, Co-coding/Help Sessions, Coding Challenges, and Data Science Journeys. All events are open to and well-attended by everyone (members of all genders) while each event is led by women and gender-minorities.
Arjun routinely gives public talks and lectures at various public venues on topics related to genetics, complex diseases, big data, algorithms, data science, machine learning, and statistics education.
The Krishnan Lab routinely engages students from local schools (Okemos and East Lansing) in its research program. The group also works with the amazing High School Honors Science, Math and Engineering Program at MSU to host a high school student from across the country every Summer.
Group members also lead interactive sessions in programs such as Introduce a Girl to Engineering. Arjun has led discussions in classrooms across the world on topics related to computational biology and disease genetics via the Skype a Scientist program. He also gives talks and leads sessions on career and research path as a computaional biologist with local student groups like the awesome Females in STEM student club at the East Lansing High School and students in the Latinos-2-College Program from the Lansing School District.
During grad school, Arjun has been part of several hands-on demoson “Mutant plants!” at the Kid’s Tech University, Virginia Tech and at the USA Science & Engineering Festival.