97 citations · 136 across the 19 of their papers we have counts for
19 papers
Towards Personalized Quantum Federated Learning for Anomaly Detection
Ratun Rahman, Sina Shaham, Dinh C. Nguyen
Anomaly detection has a significant impact on applications such as video surveillance, medical diagnostics, and industrial monitoring, where anomalies frequently depend on context…
Differentially Private Publication of Electricity Time Series Data in Smart Grids
Sina Shaham, Gabriel Ghinita, Bhaskar Krishnamachari +1
Smart grids are a valuable data source to study consumer behavior and guide energy policy decisions. In particular, time-series of power consumption over geographical areas are ess…
ILB: Graph Neural Network Enabled Emergency Demand Response Program For Electricity
Sina Shaham, Bhaskar Krishnamachari, Matthew Kahn
Demand Response (DR) programs have become a crucial component of smart electricity grids as they shift the flexibility of electricity consumption from supply to demand in response…
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…
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…
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…
Multi-modal Misinformation Detection: Approaches, Challenges and Opportunities
Sara Abdali, Sina shaham, Bhaskar Krishnamachari
As social media platforms are evolving from text-based forums into multi-modal environments, the nature of misinformation in social media is also transforming accordingly. Taking a…
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…
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…
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…
When Machine Learning Meets Privacy: A Survey and Outlook
Bo Liu, Ming Ding, Sina Shaham +3
The newly emerged machine learning (e.g. deep learning) methods have become a strong driving force to revolutionize a wide range of industries, such as smart healthcare, financial…
Extended Kalman Filter Beam Tracking for Millimeter Wave Vehicular Communications
Sina Shaham, Matthew Kokshoorn, Ming Ding +2
Millimeter-wave (mmWave) communication is a promising technology to meet the ever-growing data traffic of vehicular communications. Unfortunately, more frequent channel estimations…
On the Importance of Location Privacy for Users of Location Based Applications
Sina Shaham, Saba Rafieian, Ming Ding +2
Do people care about their location privacy while using location-based service apps? This paper aims to answer this question and several other hypotheses through a survey, and revi…
Privacy Preserving Location Data Publishing: A Machine Learning Approach
Sina Shaham, Ming Ding, Bo Liu +3
Publishing datasets plays an essential role in open data research and promoting transparency of government agencies. However, such data publication might reveal users' private info…
Fast Channel Estimation and Beam Tracking for Millimeter Wave Vehicular Communications
Sina Shaham, Ming Ding, Matthew Kokshoorn +3
Millimeter wave (mmWave) has been claimed to be the only viable solution for high-bandwidth vehicular communications. However, frequent channel estimation and beamforming required…
Privacy Preservation in Location-Based Services: A Novel Metric and Attack Model
Sina Shaham, Ming Ding, Bo Liu +2
Recent years have seen rising needs for location-based services in our everyday life. Aside from the many advantages provided by these services, they have caused serious concerns r…
RAF: Robust Adaptive Multi-Feedback Channel Estimation for Millimeter Wave MIMO Systems
Sina Shaham, Matthew Kokshoorn, Zihuai Lin +1
Millimeter wave is a promising technology for the next generation of wireless systems. As it is well-known for its high path loss, the systems working in this spectrum tend to expl…