Hyemin Bang

PhD in Computer Science

Massachusetts Institute of Technology

Advisor: Mitchell Gordon, CSAIL

MEng in Computer Science

Massachusetts Institute of Technology

Advisor: Arvind Satyanarayan, Visualization Group, CSAIL
Concentration: Artificial Intelligence · GPA: 4.8 / 5

SB in Computer Science

Massachusetts Institute of Technology

GPA: 4.4 / 5

MIT CSAIL

Mentor: Mitchell Gordon

Developing frameworks to evaluate and enhance human–AI interactions.

Visualization Group, MIT CSAIL

Mentor: Arvind Satyanarayan

Researching methods to interpret and align model learning behavior with human reasoning.

Iterative Rubric Refinement from User Disagreement at Inference Time

Hyemin Bang, Mitchell Gordon

Under review

Abstraction Alignment: Comparing Model-Learned and Human-Encoded Conceptual Relationships

Angie Boggust, Hyemin Bang, Hendrik Strobelt, Arvind Satyanarayan

ACM Conference on Human Factors in Computing Systems (CHI) · Project · Paper · Code

Explanation Alignment: Quantifying the Correctness of Model Reasoning At Scale

Hyemin Bang, Angie Boggust, Arvind Satyanarayan

European Conference on Computer Vision (ECCV) Explainable Computer Vision Workshop · Project · Paper · Code

6.8510 (6.871): Intelligent Multimodal User Interfaces

Graduate Teaching Assistant, MIT

Professor: Randall Davis

Break Through Tech AI

Graduate Teaching Assistant, MIT

• Mentored undergraduate women, non-binary, and underrepresented students in data science, machine learning, and AI.

6.7930 (6.871) / HST.956: Machine Learning for Healthcare

Graduate Teaching Assistant, MIT

Professor: Peter Szolovits

• Delivered a lecture on explainability and interpretability in healthcare ML to 100 students.

6.4100 (6.034): Artificial Intelligence

Graduate Teaching Assistant, MIT

Principal Lecturer: Kimberle Koile

Refugee Learning Accelerator

Undergraduate Researcher, MIT Media Lab

• Mentored Middle Eastern computer scientists and engineers in developing technologies for refugee education.

InterSystems

Systems Developer

• Integrated H2O and DataRobot, third-party machine learning platforms, into InterSystems IRIS, the company's high-performance database platform, simplifying and streamlining the development and deployment of machine learning models.
• Designed and implemented Kafka and AmazonSQS connectors for InterSystems IRIS, enabling seamless data integration between systems.