Daniel Bienstock

About Daniel Bienstock

Daniel Bienstock, With an exceptional h-index of 41 and a recent h-index of 26 (since 2020), a distinguished researcher at Columbia University in the City of New York, specializes in the field of operations research, optimization, applied mathematics, algorithms.

His recent articles reflect a diverse array of research interests and contributions to the field:

Optimizing ventilation in medium-and short-term mine planning

Accurate and Warm-Startable Linear Cutting-Plane Relaxations for ACOPF

Accurate Linear Cutting-Plane Relaxations for ACOPF

Risk-Aware Security-Constrained Unit Commitment

Virtual Trading in a Multi-Settlement Electricity Market

Incentivizing Investment and Reliability: A Study on Electricity Capacity Markets

Physics-Informed Machine Learning for Electricity Markets: A NYISO Case Study

Surface Coal Mine Production Scheduling under Time-of-Use Power Rates

Daniel Bienstock Information

University

Position

Liu Family Professor of Operations Research

Citations(all)

7412

Citations(since 2020)

2319

Cited By

6126

hIndex(all)

41

hIndex(since 2020)

26

i10Index(all)

87

i10Index(since 2020)

49

Email

University Profile Page

Google Scholar

Daniel Bienstock Skills & Research Interests

operations research

optimization

applied mathematics

algorithms

Top articles of Daniel Bienstock

Optimizing ventilation in medium-and short-term mine planning

Optimization and Engineering

2024/3/9

Accurate and Warm-Startable Linear Cutting-Plane Relaxations for ACOPF

arXiv preprint arXiv:2403.08800

2024/2/4

Daniel Bienstock
Daniel Bienstock

H-Index: 24

Accurate Linear Cutting-Plane Relaxations for ACOPF

arXiv preprint arXiv:2312.04251

2023/12/7

Daniel Bienstock
Daniel Bienstock

H-Index: 24

Risk-Aware Security-Constrained Unit Commitment

arXiv preprint arXiv:2311.17254

2023/11/28

Virtual Trading in a Multi-Settlement Electricity Market

Available at SSRN 4641966

2023/11/23

Incentivizing Investment and Reliability: A Study on Electricity Capacity Markets

arXiv preprint arXiv:2311.06426

2023/11/10

Physics-Informed Machine Learning for Electricity Markets: A NYISO Case Study

IEEE Transactions on Energy Markets, Policy and Regulation

2023/9/22

Surface Coal Mine Production Scheduling under Time-of-Use Power Rates

2023/9

Andrea Brickey
Andrea Brickey

H-Index: 4

Daniel Bienstock
Daniel Bienstock

H-Index: 24

Principled deep neural network training through linear programming

Discrete Optimization

2023/8/1

Daniel Bienstock
Daniel Bienstock

H-Index: 24

Gonzalo Muñoz
Gonzalo Muñoz

H-Index: 20

On a computationally ill-behaved bilevel problem with a continuous and nonconvex lower level

Journal of Optimization Theory and Applications

2023/7

Complexity, exactness, and rationality in polynomial optimization

Mathematical Programming

2022/5/16

Power network design with line activity

2022/3/2

Integer Programming and Combinatorial Optimization (IPCO) 2020

2023/5/21

Robust streaming PCA

Advances in Neural Information Processing Systems

2022/12/6

Daniel Bienstock
Daniel Bienstock

H-Index: 24

Mathematical programming formulations for the alternating current optimal power flow problem

Annals of Operations Research

2022/7

On inequalities with bounded coefficients and pitch for the min knapsack polytope

Discrete Optimization

2022/5/1

Optimal Protective and Mitigation Strategies Against Flooding and Future Climate Risk

AGU Fall Meeting Abstracts

2021/12

Optimization of coastal protections in the presence of climate change

Frontiers in Climate

2021/8/5

Cardinality minimization, constraints, and regularization: a survey

arXiv preprint arXiv:2106.09606

2021/6/17

A methodological framework for determining an optimal coastal protection strategy against storm surges and sea level rise

Natural Hazards

2021/6

See List of Professors in Daniel Bienstock University(Columbia University in the City of New York)

Co-Authors

academic-engine