Talks

Following is a list of public talks I have given in the past.

Characterizing Feedback Statements in ML Jupyter Notebooks

2026-10-09

Paper presentation at International Symposium on Empirical Software Engineering and Measurement (ESEM) 2026

It Comes in Notebooks: Changes and Challenges of Operationalizing ML Prototypes

2026-09-18

Paper presentation at International Conference on Software Maintenance and Evolution (ICSME) 2026

Data vs. Model Fairness Testing: An Empirical Study

2024-04-20

Paper presentation at International Workshop on Deep Learning for Testing and Testing for Deep Learning (DeepTest) 2024 workshop.

Towards Automatic Translation of Machine Learning Visual Insights to Analytical Assertions

2024-04-20

Paper presentation at International Workshop on Natural Language-Based Software Engineering (NLBSE) 2024.

Data vs. Model Fairness Testing: An Empirical Study

2024-04-18

Poster presentation at International Conference of Software Engineering (ICSE) 2024.

Bridging the Gap Between Visual and Analytical Machine Learning Testing

2023-06-02

Lightening talk at SEN Symposium 2023.

Towards Understanding Machine Learning Testing in Practice

2023-05-15

Poster presentation at International Conference on AI Engineering (CAIN) 2023.

Data Validation with TFDV

2022-05-16

Guest lecture for Release Engineering for Machine Learning Applications course at TU Delft. Materials for the hands-on tutorial on using Tensorflow Data Validation, instructions & code can be found in this github repo.

Data Smells in Public Datasets

2022-05-04

Paper presentation at the International Conference on AI Engineering (CAIN) 2022.

Privacy Preserving Deep Learning

2021-09-07

A talk on Privacy Preserving Deep Learning (PPDL) I gave to my research group. It was largly based on a literature review I did during my Msc.

Research Workflow in Plaintext

2021-07-12

Talk on using Emacs and org-mode to craft a research workflow.