Recep Bekci

Research

Inventory Control and Learning for One-Warehouse Multistore System with Censored Demand

Probabilistic Models for Manufacturing Lead Times

Arxiv

Visualizing the Loss Landscape of
Actor-Critic Methods with Applications in
Inventory Optimization

Arxiv

• Showed the characteristics of the actor loss function which is the essential part of the optimization
• Exploited low dimensional visualizations of the loss function and provide comparisons for loss landscapes of various algorithms
• Applied this approach to multi- store dynamic inventory control, a notoriously difficult problem in supply chain operations, and explored the shape of the loss function associated with the optimal policy

Image-based Forecasting for Fast-Fashion ⁽²⁰¹⁹⁾

PRESENTED AT INFORMS 2019/ SEATTLE

• Utilized computer vision techniques to retrieve the information from images
• Implemented transfer learning techniques to effectively use convolutional neural networks to predict product sales performances from their images
• Collaborated with Koton, hence used the data from one of the largest Fast-Fashion retail companies in Europe

Autism Prediction from Genetics ⁽²⁰¹⁹⁾

Comp 766: Graph Representation Learning Project

• We model genomic mutations in families with at least one child with Autism Spectrum Disorder (ASD) in a graph
• Utilized a heterogeneous graph neural network (GNN) variant to perform a node classification task
• Compared the GNN's performance with a gradient boosting baseline

Optimization of Customer Retention Rate in Life
Insurances Renewal and Exit Processes ^(2017-2018)

• Predicted the churn probabilities of customers using their socio-economic features and transaction history
• Used the predicted probabilities to optimize the actions and promotions to increase retention of life insurance customers via mathematical programming
• Collaborated with Aviva

Risk-Averse Airline Revenue Management with
Coherent Measures of Risk ⁽²⁰¹⁷⁾

Link for the project

• Modelled the problem using Markov Decision Processes
• Showed whether a control limit policy exists for single-leg risk-averse model with overbooking, cancellation and no-shows under risk-averse setting

Work Experience

Amazon ⁽²⁰²³⁾

Ivado Labs ⁽²⁰²³⁾

Oracle Labs ⁽²⁰²²⁾

Axya ⁽²⁰²¹⁾

Aviva-Sa Insurance ^(2017-2018)

Turkish Aerospace Industries, Inc. (TAI) ⁽²⁰¹⁸⁾

ASELSAN Electronics ⁽²⁰¹⁷⁾

Teaching

MSCI 609: Quantitative Data Analysis (University of Waterloo) ⁽²⁰²⁴⁾

MSCI 131: Work Design and Facilities Planning (University of Waterloo) ⁽²⁰²⁴⁾

MGCR 472: Operations Management (McGill University) ⁽²⁰²²⁾

MGSC 695: Deep Learning (McGill University) ^(2019,2020)

• Teaching Assistant

About

Hello! I am an Assistant Professor of Operations Research in the Department of Management Science and Engineering at the University of Waterloo.

My research focuses on the development of data-driven optimization models for decision-making under uncertainty. I am particularly interested in applications within supply chain management, revenue management, assortment optimization, and inventory control.

I received my Ph.D. in Operations Management from McGill University in 2023, where I was fortunate to be advised by Professor Mehmet Gümüş and Professor Sentao Miao. I also hold a BSc in Industrial Engineering from Bilkent University.

Contact

• GitHub
• LinkedIN
• Mail
• Faculty Profile

Elements

i = 0;

while (!deck.isInOrder()) {
    print 'Iteration ' + i;
    deck.shuffle();
    i++;
}

print 'It took ' + i + ' iterations to sort the deck.';