Bayesian Models for Node-Based Inference Techniques
Cyber attackers often use passive reconnaissance to collect information about target networks. This technique can be used to identify systems and plan attacks, making it an …
Nazia Sharmin
Aron Laszka
Associate Professor
Pennsylvania State University
Aron Laszka is an Associate Professor in the College of Information Sciences and Technology at the Pennsylvania State University. Previously, he was an Assistant Professor at the University of Houston, a Research Assistant Professor at Vanderbilt University, and a Postdoctoral Scholar at the University of California, Berkeley.
His research interests revolve around artificial intelligence and cyber-physical systems, focusing on machine learning for decision making and optimization, with applications in smart and connected communities, critical infrastructure, and cybersecurity.
His research is funded by the National Science Foundation, the Department of Energy, the Department of Transportation, and other agencies.
•
Rolling Horizon based Temporal Decomposition for the Offline Pickup and Delivery Problem with Time Windows
The offline pickup and delivery problem with time windows (PDPTW) is a classical combinatorial optimization problem in the transportation community, which has proven to be very …
Youngseo Kim
Principled Data-Driven Decision Support for Cyber-Forensic Investigations
In the wake of a cybersecurity incident, it is crucial to promptly discover how the threat actors breached security in order to assess the impact of the incident and to develop and …
Strategic Cyber Camouflage
One of the most fundamental tasks for an AICA agent will be to manipulate information that an adversary can observe, either about a network or the AICA agent itself. This includes …
Christopher Kiekintveld
Decentralized Computation Market for Stream Processing Applications
While cloud computing is the current standard for outsourcing computation, it can be prohibitively expensive for cities and infrastructure operators to deploy services. At the same …
Scott Eisele
Offline Vehicle Routing Problem with Online Bookings: A Novel Problem Formulation with Applications to Paratransit
Vehicle routing problems (VRPs) can be divided into two major categories: offline VRPs, which consider a given set of trip requests to be served, and online VRPs, which consider …
Neural Architecture and Feature Search for Predicting the Ridership of Public Transportation Routes
Accurately predicting the ridership of public-transit routes provides substantial benefits to both transit agencies, who can dispatch additional vehicles proactively before the …
An Online Approach to Solve the Dynamic Vehicle Routing Problem with Stochastic Trip Requests for Paratransit Services
Many transit agencies operating paratransit and microtransit ser-vices have to respond to trip requests that arrive in real-time, which entails solving hard combinatorial and …
Michael Wilbur
A Taxonomy of Blockchain Oracles: The Truth Depends on the Question
Blockchains benefit from guarantees of immutability and reliability due to their high redundancy and distributed nature. They show their value especially when operating between …
Michael Bartholic
Data-Driven Prediction and Optimization of Energy Use for Transit Fleets of Electric and ICE Vehicles
Due to the high upfront cost of electric vehicles, many public transit agencies can afford only mixed fleets of internal-combustion and electric vehicles. Optimizing the operation …