Research Focus

As a Postdoctoral Fellow at the University of Alberta, my research primarily involves:

• Reinforcement Learning (RL): Developing RL techniques for real-world sequential decision-making problems. My research aims to apply these techniques in robotics to make robots more adaptive to Out-of-distribution situations (e.g., novel environments or tasks).
• Bayesian Optimization (BO): Leveraging BO to optimize sensor/device placements in real-world systems, such as smart grids.
• Large Language Models (LLMs): Exploring the use of LLMs to better understand and improve decision-making processes in robotic systems for safety-critical applications.

Collaboration and Mentorship

In addition to my research, I am actively collaborating with various academic members and mentoring graduate students, researchers, and interns.

Current Projects

• Adaptive Robotics for Safety-Critical Applications: Designing novel techniques, using RL and LLM for adaptation in robots facing unforeseen faults or dynamic changes.
• Phasor measurement units (PMU) Placement in Smart Grids: Applying BO to optimize PMU placement in real-world smart grids.

Research Focus

As a Data Scientist Intern at Visier Inc., my research primarily focused on:

• Explainability in Machine Learning: Investigating methods to explain the performance of machine learning models for churn prediction. This involved analyzing the importance of features specific to different companies and how these influenced the predictive models' outcomes.

Collaboration and Mentorship

During this internship, I collaborated closely with my mentors Anton Smessaert and Stephanie Finkenwirth.

Research Focus

As a Machine Learning Engineer Intern at ShopHopper, my work primarily involved:

• Image Recognition: Leading a project to develop models for recognizing fashion product features such as type, color, and style.
• Natural Language Processing (NLP): Extracting useful information from the descriptions of fashion products to improve data accuracy and product recommendations.

Collaboration and Mentorship

During this internship, I was the lead and mentor for five undergraduate ML interns. We worked on two key projects and had weekly progress reports with our manager, Ryan Lancaster.

This internship was part of a Mitacs program, in collaboration with Professor Irene Cheng from the University of Alberta.

golestan@ualberta.ca golestan@amii.ca

Machine Learning Scientist
Alberta Machine Intelligence Institute (Amii)