Milad Memarzadeh

Milad Memarzadeh
Universities Space Research Association · NASA Ames Research Center

Doctor of Philosophy

About

34
Publications
8,708
Reads
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661
Citations
Introduction
My research focuses on the development of theoretical and computational methods for understanding, monitoring, and controlling real-world complex dynamical systems. I develop and deploy methods based on artificial intelligence and decision theory to solve challenging problems related to the dynamics of our built environment as well as our coupled human-natural systems. My research lies at the scientific interface of Civil & Environmental Engineering, Computer & Data Sciences, and Sustainability.
Additional affiliations
July 2018 - present
University of California, Berkeley
Position
  • PostDoc Position
Description
  • Reducing the Environmental Impacts of Food-Energy-Water (FEW) Systems In and Around Cities
August 2017 - December 2017
University of California, Berkeley
Position
  • Instructor
Description
  • Data Science for Smart Cities: http://www.miladmemarzadeh.com/ce88.html
January 2016 - June 2018
University of California, Berkeley
Position
  • PostDoc Position
Education
January 2013 - May 2016
Carnegie Mellon University
Field of study
  • Civil and Environmental Engineering - Advanced Infrastructure Systems
August 2011 - December 2012
Virginia Polytechnic Institute and State University
Field of study
  • Civil Engineering - Construction Engineering and Management
August 2007 - May 2011
University of Tehran
Field of study
  • Civil Engineering

Publications

Publications (34)
Article
Full-text available
Identifying safety anomalies and vulnerabilities in the aviation domain is a very expensive and time-consuming task. Currently, it is accomplished via manual forensic reviews by subject matter experts (SMEs). However, with the increase in the amount of data produced in airspace operations, relying on such manual reviews is impractical. Automated ap...
Conference Paper
Full-text available
AI and Machine Learning are becoming particularly useful for the exploration of the design alternatives and can offer a range of advantages when applied to the exploration of innovative forms of extra-terrestrial infrastructure under uncertain environmental conditions. This paper focuses on building an unsupervised machine learning model (convoluti...
Conference Paper
View Video Presentation: https://doi.org/10.2514/6.2022-2542.vid Anomaly detection in commercial aviation is an extremely challenging yet crucial task. Accurately detecting operationally significant anomalies in operational data can save civilian lives and/or result in significant savings in aircraft/maintenance cost. The current practice uses manu...
Article
Full-text available
The identification of precursors to safety incidents in aviation data is a crucial task, yet extremely challenging. The main approach in practice leverages domain expertise to define expected tolerances in system behavior and flags exceedances from such safety margins. However, this approach is incapable of identifying unknown risks and vulnerabili...
Article
1- In the last decade, artificial intelligence (AI) has increasingly been applied to help solve applied ecology problems. Partially Observable Markov Decision Processes (POMDPs) are one such example. POMDPs have been applied in conservation, applied ecology and natural resource management to solve problems such as deciding when to stop managing or...
Article
Full-text available
System-level integration and optimization of food-energy-water systems (FEWS) require coordination of multiple agencies and decision-makers and incorporating their interdependence. In general, such coordination might be hard to achieve. As a result, the literature in FEWS management either optimize the operations for one sector (or one decision-mak...
Article
Full-text available
The modern National Airspace System (NAS) is an extremely safe system and the aviation industry has experienced a steady decrease in fatalities over the years. This is in part due the airlines, manufacturers, FAA, and research institutions all continually working to improve the safety of the operations. However, the current approach for identifying...
Article
Extreme events represent not only some of the most damaging events in our society and environment, but also the most difficult to predict. Model-based predictions of the disruptions induced by extreme events on urban infrastructure systems are often unreliable, as these events are unlikely by their very definition. Specifically, characterizing the...
Article
Current and future prospects for successfully rebuilding global fisheries remain debated due to uncertain stock status, variable management success, and disruptive environmental change. While scientists routinely account for some of this uncertainty in population models, the mechanisms by which this translates into decision-making and policy are pr...
Article
Full-text available
Integrated management of Food-Energy-Water Systems (FEWS) requires a unified, flexible and reproducible approach to incorporate the interdependence between sectors, and include the risk of non-stationary environmental variations due to climate change. Most of the recently developed methods in the literature fall short of one or more aspects in such...
Article
Ecological management and decision-making typically focus on uncertainty about the future, but surprisingly little is known about how to account for uncertainty of the present: that is, the realities of having only partial or imperfect measurements. Our primary paradigms for handling decisions under uncertainty—the precautionary principle and optim...
Preprint
Full-text available
Ecological management and decision-making typically focus on uncertainty about the future, but surprisingly little is known about how to account for uncertainty of the present: that is, the realities of having only partial or imperfect measurements. Our primary paradigms for handling decisions under uncertainty -- the precautionary principle and op...
Article
Adaptive management has a long history in ecology and conservation. Uncertainty in both the state of a system and the model defining its dynamics are fundamental challenges in adaptive management of complex ecological systems. Traditional approaches in conservation biology often ignore one or both sources of uncertainty due to the computational com...
Conference Paper
Full-text available
Decision making about the management of infrastructure systems is based on models of cost, degradation, effectiveness of maintenance actions. These models can be informed by data collected in the past, and progressively updated as more data becomes available. While parametric models are suitable when an appropriate statistical form is assumed, non-...
Article
Predictions of climate change can significantly affect the optimization of measures reducing the long-term risk for assets exposed to extreme events. Although a single climate model can be represented by a Markov stochastic process and directly integrated into the sequential decision-making procedure, optimization under epistemic uncertainty about...
Conference Paper
Full-text available
In this work, an optimal planning under uncertainty framework relating to structural life-cycle management is analyzed. Optimizing long-term objectives of structures and/or infrastructure systems taking into consideration informative but uncertain data about their condition, becoming available in time, is approached herein as a sequential decision-...
Conference Paper
Full-text available
We investigate how sequential decision making analysis can be used for modeling system resilience. In the aftermath of an extreme event, agents involved in the emergency management aim at an optimal recovery process, trading off the loss due to lack of system functionality with the investment needed for a fast re-covery. This process can be formula...
Article
We illustrate how to assess the Value of Information (VoI) in sequential decision making problems modeled by Partially Observable Markov Decision Processes (POMDPs). POMDPSs provide a general framework for modeling the management of infrastructure components, including operation and maintenance, when only partial or noisy observations are available...
Preprint
Full-text available
Over the past 30 years, researchers have used various approximations to address the impact of measurement uncertainty on optimal management policy.This literature has consistently suggested the counter-intuitive proposition that increasing harvest levels in the presence of measurement error is often optimal. Here, we use state-of-the art algorithms...
Article
System management includes the selection of maintenance actions depending on the available observations: when a system is made up by components known to be similar, data collected on one is also relevant for the management of others. This is typically the case of wind farms, which are made up by similar turbines. Optimal management of wind farms is...
Article
Operation and maintenance of an infrastructure system rely on information collected on its components, which can provide the decision maker with an accurate assessment of their condition states. However, resources to be invested in data gathering are usually limited and observations should be collected based on their Value of Information (VoI). Ass...
Article
Full-text available
Wind energy is a key renewable source, yet wind farms have relatively high cost compared with many traditional energy sources. Among the life cycle costs of wind farms, operation and maintenance (O&M) accounts for 25–30%, and an efficient strategy for management of turbines can significantly reduce the O&M cost. Wind turbines are subject to fatigue...
Conference Paper
Full-text available
Degradation process of many infrastructure systems, such as road networks, water and wastewater networks can be modeled in a probabilistic framework, incorporating the effect of the maintenance policy based on the information collected. Information helps the decision maker to reduce uncertainty about the components' condition and minimize the corre...
Conference Paper
Identifying optimal management policies for systems made up by similar components is a challenging task, due to dependence in the components' behavior. In this setting, observations collected on one component are also relevant for learning the behavior of others. Probabilistic graphical models allow for consistent inference using all available data...
Conference Paper
Full-text available
Many spatially distributed phenomena relevant to the management of civil infrastructure, from temperature in buildings to earthquake ground excitation, can be modeled as Gaussian Processes (GPs). GPs generalize the concept of multivariate Gaussian distributions in the continuous domain. They can be used for obtaining consistent predictions by model...
Article
Full-text available
In this paper, a methodology is proposed for evaluating sampling locations in an existing river water quality monitoring network. The Dynamic Factor Analysis is utilized to extract the independent dynamic factors from time series of water quality variables. Then, the entropy theory is applied to the independent dynamic factors to construct transinf...
Article
Full-text available
Wind energy is a renewable energy source that has been growing rapidly in recent years. However, wind farms have relatively high cost, of which operation and maintenance (O&M) cost takes up 25-35%. An optimal strategy for O&M can significantly reduce this cost. Wind turbines are subject to fatigue-induced degradation and need periodic inspections a...
Conference Paper
Full-text available
This paper presents an automated and real-time algorithm for recognition and 2D tracking of construction workers and equipment from site video streams. In recent years, several research studies have proposed semi-automated vision-based methods for tracking of construction workers and equipment. Nonetheless, there is still a need for automated initi...
Conference Paper
Full-text available
Benchmarking and monitoring are critical steps toward improving operational efficiency of earthmoving equipment and minimizing their environmental impacts. Despite the importance, the relationship between operational efficiency and total pollutant emissions of these operations has not been fully understood. To establish such relationship and find w...
Conference Paper
Full-text available
This paper presents a new carbon footprint monitoring tool that enables contractors and managers to reliably and effectively benchmark, monitor, and visualize expected and released embodied carbon footprint of a construction project. The proposed method is based on generating DnAR - n dimensional augmented reality - models in which the expected and...
Article
The effect of CRM aspects on rheological properties of asphalt binder such as improvement in the performance grade (PG) for low, intermediate, and high service temperatures are evaluated and the binder’s dynamic viscosity changes were studied in this research. Enhancement also resulted in the binder’s fatigue and rutting indices. At the same time,...

Questions

Question (1)
Question
I need to get more details on how to define the belief state and discretize it.

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Projects

Project (1)
Project
We are developing fundamental insights into high-value opportunities to “close loops” within the FEWS network and to prioritize technology upgrades. Taken together, we envision that mathematical modeling, uncertainty quantification, and optimization methods could spur an entirely new field of FEWS systems analysis. Such a new multidisciplinary field would provide the fundamental tools to understand and engineer sustainable and resilient interconnected FEWS of the future.