Data Science & Analytics
This field, situated at the intersection of technology, statistics, and business strategy, is dedicated to extracting valuable insights from diverse datasets. Utilizing advanced algorithms and machine learning techniques, data scientists analyze information to uncover patterns, trends, and correlations, driving innovation across industries.
Quasispecies Analysis of SARS-CoV-2 via Non-convex Tensor Completion
Lin Meixia (2023)
GPU-Accelerated Algorithms for Multi-Sensor Data Association for Multi-Target Tracking.
Nagi Rakesh (2023)
Hybrid AI/ML-Optimization Approaches to Cloud Native Workflow Scheduling,” IBM-Illinois Discovery Accelerator Institute
Nagi Rakesh (2023)
Mitigating the Harm of Fentanyl through Holistic Demand/Supply-Chain Interventions and Equitable Resource Allocations,” National Science Foundation (USA)
Nagi Rakesh (2023)
The Impacts of On-demand Platforms under Individual Choice Endogeneity
Xu Ying (2023)
Building Proposal Development Evaluation with Artificial Intelligence
Varvitsiotis Antonios (2022)
Towards Co-clustering in Big Data: An optimization perspective
Lin Meixia (2022)
Towards Co-clustering in Big Data: An Optimization Perspective
Lin Meixia (2022)
Airfield and Airspace Management
Antunes Ribeiro Nuno (2022)
Computer Science Approaches to Quantum Computing for Finance
Varvitsiotis Antonios (2022)