Events

In this talk I will present an overview of my research on chronic care services.  I will then focus on the problem of care delivery for complex patients, with multiple comorbidities. In this project, we develop a Markov Decision Process framework to manage care for individual patients with multiple chronic conditions through a complex care hub. Complex care provision influences the evolution of Patient Activation Measure (PAM), an indicator for healthy behavior, which affects the evolution of health state of patients.

Supervisor

Jatin Nathwani

We will discuss a few examples from healthcare, where quantitative models embedded in decision-support tools can improve the quality of decision-making (for patients, physicians, or caregivers) and patient outcomes.

Supervisors

Samir Elhedhli

Fatih Erenay

Dr. Prokopyev will be discussing ‘Sequential Interdiction with Incomplete Information and Learning’ on the June 19^th. Graduate students have an opportunity to meet with our distinguished speaker before the seminar.

We present a framework for a class of sequential decision-making problems in the context of max-min bi-level programming, where a leader and a follower repeatedly interact. At each period, the leader allocates resources to disrupt the performance of the follower (e.g., as in defender-attacker or interdiction problems), who in turn minimizes some cost function over a set of activities that depends on the leader’s decision.

The transportation of hazardous materials (hazmat) has drawn significant attention from various stakeholders due to the undesirable impacts on the environment and public health. Focusing on the connection between the traffic and the risk associated with the hazmat shipments, the present research aims to assist the regulator in designing a policy of dual tolls, imposed on both hazmat and non-hazmat shipments, to mitigate the hazmat risk in a road network.

Supervisor: Fatih Erenay

Automatic generation of text is an important topic in natural language processing with applications in tasks such as machine translation and text summarization. In this thesis, we explore the use of deep neural networks for generation of natural language. Specifically, we implement two sequence-to-sequence neural variational models - variational autoencoders (VAE) and variational encoder-decoders (VED).

A Cross-Dock (CD) is a synchronized unit of a supply chain network, used to sort the goods received from inbound trucks (from a warehouse or factory), and load those products to outbound trucks (for delivery of the goods to retail stores in the supply chain network). Most cross-docks use forklifts, and other manual material handling equipment (MHE) to process the goods on pallets received from inbound trucks. Those pallets are sorted and loaded onto outbound trucks.