Baruch Schieber

Baruch Schieber is a Professor in the Department of Computer Science at New Jersey Institute of Technology (NJIT), part of the Ying Wu College of Computing. Previously, he served as a Distinguished Research Staff Member at IBM Research and a member of the IBM Academy of Technology. His research focuses on the mathematical foundations of AI, algorithm design, optimization, scheduling, and resource allocation, with applications in machine learning, deep learning, and real-world systems like airport security and fleet optimization.

Education:

• Ph.D., Computer Science, Tel Aviv University (1987)
• M.S., Computer Science, Israel Institute of Technology (1984)
• B.S., Computer Science, Israel Institute of Technology (1980)

Research Interests: Schieber’s work bridges theoretical computer science and practical applications. He has pioneered advancements in fair resource allocation, real-time scheduling, and algorithmic fairness. His contributions include optimizing AI-driven systems, minimizing tardiness in job scheduling, and leveraging mathematical programming for interpretable machine learning models. Recent projects include securing private keys via public methods and developing fairness-aware algorithms for voting systems and data queries.

Publications & Impact: With over 140 publications and five patents, Schieber’s research spans algorithms, optimization, and distributed systems. His work on fleet optimization was featured in major media outlets. Current trends in his articles emphasize fairness in AI, efficient scheduling mechanisms, and energy-aware systems. His algorithms address challenges in parallel computing, graph analysis, and real-time resource management.

Awards & Recognition: While no specific awards are listed, his IBM Research tenure and patented innovations highlight his impactful contributions to industry and academia.

Grants & Advising: Schieber’s IBM projects involved high-impact collaborations, though specific grants or advising details are not detailed. His work often involves interdisciplinary teams tackling complex computational challenges.

Labs & Teams: He leads NJIT’s research in AI foundations and collaborates with IBM’s Mathematics of AI group, focusing on foundational AI algorithms and their real-world applications.