Before joining Media Computing Group, I obtained my Master's degree in Media Informatics from RWTH Aachen. Previously, I obtained my Bachelor's degree in Computer Science from Amrita University, India.
At Media Computing Group, my responsibilities included contributing to development and UX projects; mentoring junior researchers and developers; teaching courses, labs, and seminars about UX; and fulfilling administrative roles. See my work webpage for details about the courses and labs I helped teach/organize, student theses I supervised, and administrative duties I took on during my time as a Research Assistant.
My dissertation is centered around HCI. I use design principles and novel interaction techniques to support data workers' workflows. I acted as a TA for our introductory HCI course and mentored various UX projects.
This is the main focus of my dissertation. To understand how data workers learn and perform data science, I needed to have a good understanding of hypothesis-driven data science methods. I also hold data science lectures, and promote ethical, transparent practices in my lab.
As a part of my research, I have conducted numerous studies and analyzed the resulting data using qualitative methods. I am familiar with contextual inquiries, affinity diagrams, qualitative coding, and interaction analysis.
I have worked on several web-based, desktop, and mobile projects. I am proficient in Angular, D3, R, Swift, Python, and C++.
- Krishna Subramanian, Johannes Maas, Jan Borchers, and Jim Hollan. From Detectables to Inspectables: Understanding Qualitative Analysis of Audiovisual Data. (Honorable Mention Award.) In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, CHI '21, May 2021.
- Krishna Subramanian, Nur Hamdan and Jan Borchers. Casual Notebooks and Rigid Scripts: Understanding Data Science Programming. In Proceedings of the 2020 IEEE Conference on Visual Languages/Human-Centered Computing, VL/HCC '20. IEEE, Dunedin, New Zealand.
- Krishna Subramanian, Johannes Maas and Jan Borchers. TRACTUS: Understanding and Supporting Source Code Experimentation in Hypothesis-Driven Data Science. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, CHI '20, pages 10, ACM, New York, NY, USA, April 2020.
- Krishna Subramanian, Jeanine Bonot, Radu A. Coanda and Jan Borchers. StatPlayground: A Sandbox for Learning Practical Statistics. In Human-Computer Interaction -- INTERACT 2019, pages 156–165, Springer International Publishing, Cham, September 2019.
- Krishna Subramanian, Ilya Zubarev, Simon Voelker and Jan Borchers. Supporting Data Workers to Perform Exploratory Programming. In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems, CHI EA '19, pages 6, ACM, New York, NY, USA, May 2019.
- Krishna Subramanian. Position Paper: HUSDAT Workshop, CHI 2019. In CHI '19 Workshop on Human-Centered Study of Data Science Work Practices, CHI '19, ACM, New York, NY, USA, May 2019.
- Krishna Subramanian, Johannes Maas, Michael Ellers, Chat Wacharamanotham, Simon Voelker and Jan Borchers. StatWire: Visual Flow-based Statistical Programming. In Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems, CHI EA '18, pages LBW104:1–LBW104:6, ACM, New York, NY, USA, April 2018.
- Krishna Subramanian and Jan Borchers. StatPlayground: Exploring Statistics through Visualizations. In CHI '17: Extended Abstracts of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems, pages 401–404, ACM, New York, NY, USA, May 2017.
- Krishna Subramanian. Position Statement for ‘Workshop: Moving Transparent Statistics Forward’ at CHI 2017. In CHI '17 Workshop "Moving Transparent Statistics Forward", ACM, New York, NY, USA, May 2017.
- Chat Wacharamanotham, Krishna Subramanian, Sarah Theres Völkel and Jan Borchers. Statsplorer: Guiding Novices in Statistical Analysis. In CHI '15: Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, pages 2693–2702,New York, NY, USA, April 2015.
- Krishna Subramanian. VisiStat: Visualization-driven, Interactive Statistical Analysis. In CHI ’14: Extended Abstracts on Human Factors in Computing Systems, pages 987—992, April 2014.
- Krishna Subramanian. VisiStat: Visualization-driven, Interactive Statistical Analysis. Master's Thesis, RWTH Aachen University, Aachen, March 2014.