Management of Technology
Brian Cozzarin - Management Sciences
Selcuk Onay - Management Sciences
Margaret Dalziel - CBET
Jonathan Fugelsang - Psychology
Bonwoo Koo - Management Sciences
Jean-Pierre Hickey - Mechanical & Mechatronics Engineering
Qi-Ming He - Management Sciences
Fatih Erenay - Management Sciences
Elizabeth M. Jewkes - Management Sciences
Stanko Dimitrov - Management Sciences
David Landriault - Statistics and Actuarial Science
ExpecTAtions is a two-day workshop that prepares Waterloo Engineering students to undertake a teaching assistantship. To serve as a TA, you are required to complete the ExpecTAtions workshop. After full attendance and successful completion of all required activities you will receive a certificate noting your achievement.
Perry Chou - Chemical Engineering
Fatma Gzara - Management Sciences
Samir Elhedhli - Management Sciences
Houra Mahmoudzadeh - Management Sciences
Ricardo Fukasawa - Combinatorics and Optimization
This study examines how duration of patent examination is affected by technological diversity of patent applications, using a sample of all pharmaceutical patent applications filed between 1985 and 2017 at China’s State Intellectual Property Office (SIPO). Patent examination is a crucial process to evaluate the patentability of technological inventions. To understand what factors influence patent examination duration can offer strategic insights for both patent applicants and patent system designers.
In this talk, we discuss a discrete-time model where the underlying asset price is subject to stochastic volatility and liquidity for optimal trade execution. This model is an extension of Almgren and Chriss' model. Instead of the mean-variance criterion, we consider the mean-quadratic criterion for choosing the optimal strategy through applications of Markov decision processes. We carry out a numerical analysis by Monte Carlo simulation and provide detailed comparison results under various risk aversion criteria.
We compare two models of a multi-server queueing system with state-dependent service rates and return probabilities. In both models, upon completing service, customers are delayed prior to possibly returning to service. In one model, the determination of whether a customer will return occurs immediately upon service completion, at the beginning of the delay. In the other, that determination is made at the end of the delay, capturing the idea that it takes time for the customer’s condition and needs to evolve or assess, before it becomes known whether a return to service is needed.
Bed shortages in hospitals usually have a negative impact on patient satisfaction and medical outcomes. In practice, healthcare managers often use bed occupancy rates (BOR) as a metric to understand bed utilization, which is insufficient in capturing the risk of bed shortages. Based on the riskiness index of Aumann and Serrano (2008), we propose the entropic bed shortage metric, which captures more facets of bed shortage risk than traditional metrics such as the occupancy rate, the probability of shortages and expected shortages.
Is communicating via Skype or other video media equivalent to a face-to-face meeting? We have known for some time that after interacting face-to-face, people can predict the cooperative behaviour of strangers with better-than-chance accuracy. But is this ability affected when communications are mediated by video technology? This study reports four laboratory experiments examining how different communication conditions affect cooperation prediction efficacy.
Mark Hancock, Management Sciences
Miguel Nacenta, Management Sciences
Dr. John S. Gero
This paper investigates the impacts of two environmental policies: pollution abatement subsidy and emission tax, on a three-tier supply chain, where the manufacturer distributes via multiple competitive retailers and invests in a pollution abatement technology in manufacturing. The government pursues social welfare maximization, while the manufacturer and retailers are profit driven. We find that the subsidy policy offers the manufacturer greater incentives to abate pollution and yields higher profits for channel members.
To ensure we have space and refreshments for everyone, please make sure to register.
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.
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).
Supervisor: Fatih Erenay
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.
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.
Dr. Prokopyev will be discussing ‘Sequential Interdiction with Incomplete Information and Learning’ on the June 19th. Graduate students have an opportunity to meet with our distinguished speaker before the seminar.
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.