510 citations · 775 across the 39 of their papers we have counts for
42 papers
Holistic Survey of Privacy and Fairness in Machine Learning
Sina Shaham, Arash Hajisafi, Minh K Quan +6
Privacy and fairness are two crucial pillars of responsible Artificial Intelligence (AI) and trustworthy Machine Learning (ML). Each objective has been independently studied in the…
Towards Mobility Data Science (Vision Paper)
Mohamed Mokbel, Mahmoud Sakr, Li Xiong +45
Mobility data captures the locations of moving objects such as humans, animals, and cars. With the availability of GPS-equipped mobile devices and other inexpensive location-tracki…
On Distribution Dependent Sub-Logarithmic Query Time of Learned Indexing
Sepanta Zeighami, Cyrus Shahabi
A fundamental problem in data management is to find the elements in an array that match a query. Recently, learned indexes are being extensively used to solve this problem, where t…
Learning Dynamic Graphs from All Contextual Information for Accurate Point-of-Interest Visit Forecasting
Arash Hajisafi, Haowen Lin, Sina Shaham +4
Forecasting the number of visits to Points-of-Interest (POI) in an urban area is critical for planning and decision-making for various application domains, from urban planning and…
Fair Spatial Indexing: A paradigm for Group Spatial Fairness
Sina Shaham, Gabriel Ghinita, Cyrus Shahabi
Machine learning (ML) is playing an increasing role in decision-making tasks that directly affect individuals, e.g., loan approvals, or job applicant screening. Significant concern…
Supporting Secure Dynamic Alert Zones Using Searchable Encryption and Graph Embedding
Sina Shaham, Gabriel Ghinita, Cyrus Shahabi
Location-based alerts have gained increasing popularity in recent years, whether in the context of healthcare (e.g., COVID-19 contact tracing), marketing (e.g., location-based adve…
Unveiling and Mitigating Bias in Ride-Hailing Pricing for Equitable Policy Making
Nripsuta Ani Saxena, Wenbin Zhang, Cyrus Shahabi
Ride-hailing services have skyrocketed in popularity due to the convenience they offer, but recent research has shown that their pricing strategies can have a disparate impact on s…
NeuroSketch: Fast and Approximate Evaluation of Range Aggregate Queries with Neural Networks
Sepanta Zeighami, Cyrus Shahabi, Vatsal Sharan
Range aggregate queries (RAQs) are an integral part of many real-world applications, where, often, fast and approximate answers for the queries are desired. Recent work has studied…
A Neural Approach to Spatio-Temporal Data Release with User-Level Differential Privacy
Ritesh Ahuja, Sepanta Zeighami, Gabriel Ghinita +1
Several companies (e.g., Meta, Google) have initiated "data-for-good" projects where aggregate location data are first sanitized and released publicly, which is useful to many appl…
Models and Mechanisms for Spatial Data Fairness
Sina Shaham, Gabriel Ghinita, Cyrus Shahabi
Fairness in data-driven decision-making studies scenarios where individuals from certain population segments may be unfairly treated when being considered for loan or job applicati…
Differentially-Private Publication of Origin-Destination Matrices with Intermediate Stops
Sina Shaham, Gabriel Ghinita, Cyrus Shahabi
Conventional origin-destination (OD) matrices record the count of trips between pairs of start and end locations, and have been extensively used in transportation, traffic planning…
Gaussian Process for Trajectories
Kien Nguyen, John Krumm, Cyrus Shahabi
The Gaussian process is a powerful and flexible technique for interpolating spatiotemporal data, especially with its ability to capture complex trends and uncertainty from the inpu…
HAGEN: Homophily-Aware Graph Convolutional Recurrent Network for Crime Forecasting
Chenyu Wang, Zongyu Lin, Xiaochen Yang +3
The crime forecasting is an important problem as it greatly contributes to urban safety. Typically, the goal of the problem is to predict different types of crimes for each geograp…
Quantifying Intrinsic Value of Information of Trajectories
Kien Nguyen, John Krumm, Cyrus Shahabi
A trajectory, defined as a sequence of location measurements, contains valuable information about movements of an individual. Its value of information (VOI) may change depending on…
Integer-arithmetic-only Certified Robustness for Quantized Neural Networks
Haowen Lin, Jian Lou, Li Xiong +1
Adversarial data examples have drawn significant attention from the machine learning and security communities. A line of work on tackling adversarial examples is certified robustne…
SemiFed: Semi-supervised Federated Learning with Consistency and Pseudo-Labeling
Haowen Lin, Jian Lou, Li Xiong +1
Federated learning enables multiple clients, such as mobile phones and organizations, to collaboratively learn a shared model for prediction while protecting local data privacy. Ho…
A Neural Database for Differentially Private Spatial Range Queries
Sepanta Zeighami, Ritesh Ahuja, Gabriel Ghinita +1
Mobile apps and location-based services generate large amounts of location data that can benefit research on traffic optimization, context-aware notifications and public health (e.…
HTF: Homogeneous Tree Framework for Differentially-Private Release of Location Data
Sina Shaham, Gabriel Ghinita, Ritesh Ahuja +2
Mobile apps that use location data are pervasive, spanning domains such as transportation, urban planning and healthcare. Important use cases for location data rely on statistical…
NeuroDB: A Neural Network Framework for Answering Range Aggregate Queries and Beyond
Sepanta Zeighami, Cyrus Shahabi
Range aggregate queries (RAQs) are an integral part of many real-world applications, where, often, fast and approximate answers for the queries are desired. Recent work has studied…
An Efficient and Secure Location-based Alert Protocol using Searchable Encryption and Huffman Codes
Sina Shaham, Gabriel Ghinita, Cyrus Shahabi
Location data are widely used in mobile apps, ranging from location-based recommendations, to social media and navigation. A specific type of interaction is that of location-based…
Estimating Spread of Contact-Based Contagions in a Population Through Sub-Sampling
Sepanta Zeighami, Cyrus Shahabi, John Krumm
Physical contacts result in the spread of various phenomena such as viruses, gossips, ideas, packages and marketing pamphlets across a population. The spread depends on how people…
Kartta Labs: Collaborative Time Travel
Sasan Tavakkol, Feng Han, Brandon Mayer +4
We introduce the modular and scalable design of Kartta Labs, an open source, open data, and scalable system for virtually reconstructing cities from historical maps and photos. Kar…
Spatial Privacy Pricing: The Interplay between Privacy, Utility and Price in Geo-Marketplaces
Kien Nguyen, John Krumm, Cyrus Shahabi
A geo-marketplace allows users to be paid for their location data. Users concerned about privacy may want to charge more for data that pinpoints their location accurately, but may…
A Secure Location-based Alert System with Tunable Privacy-Performance Trade-off
Gabriel Ghinita, Kien Nguyen, Mihai Maruseac +1
Monitoring location updates from mobile users has important applications in many areas, ranging from public safety and national security to social networks and advertising. However…