Research

Work addresses queueing theory, pricing and revenue management, AI-enabled decision systems, and institutional design.

Publications

Business Schools as Learning Organizations in the Age of AI

P. Cardon, R. S. Randhawa

In F. A. Csaszar and N. Jia (eds.), Handbook of Artificial Intelligence and Strategy. Edward Elgar Publishing, pp. 218–226, 2026

Examines how business schools can adapt as learning organizations in response to AI-driven transformations in management education and practice.

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Service Operations for Justice-On-Time: A Data-Driven Queueing Approach

N. Bakshi, J. Kim, R. S. Randhawa

Manufacturing & Service Operations Management, 27(1), 305-321, 2024

2025 MSOM Service SIG Best Paper Award

Data-driven queueing framework for judicial systems. Demonstrates operational interventions reducing case delays while maintaining fairness.

SSRN →
Predicting Response of Triple-Negative Breast Cancer to Neoadjuvant Chemotherapy Using a Deep Convolutional Neural Network–Based Artificial Intelligence Tool

S. Krishnamurthy, P. Jain, D. Tripathy, R. Basset, R. Randhawa, H. Muhammad, W. Huang, H. Yang, S. Kummar, G. Wilding, R. Roy

JCO Clinical Cancer Informatics, vol. 7, 2023

Deep learning model predicting chemotherapy response in triple-negative breast cancer from histopathology images.

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Optimally Scheduling Heterogeneous Impatient Customers

A. Bassamboo, R. Randhawa, C. Wu

Manufacturing & Service Operations Management, 25(3), 1066-1080, 2023

Optimal scheduling policies for service systems with customer heterogeneity in patience and service requirements.

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A Novel Artificial Intelligence-Powered Method for Prediction of Early Recurrence of Prostate Cancer After Prostatectomy and Cancer Drivers

W. Huang, R. Randhawa, P. Jain, S. Hubbard, J. Eickhoff, S. Kummar, G. Wilding, H. Basu, R. Roy

JCO Clinical Cancer Informatics, Feb:6, 2022

AI-powered platform predicting prostate cancer recurrence and identifying molecular drivers.

PubMed →
Why Perfect Tests May Not be Worth Waiting For: Information as a Commodity

K. Drakopoulos, R. S. Randhawa

Management Science (Fast Track), 67(11), 6678-6693, 2021

Models optimal timing of decisions under evolving information quality. Application to COVID-19 testing demonstrates value of imperfect but timely information.

SSRN → INFORMS Podcast → Watch presentation →
Development and Validation of an Artificial Intelligence-Powered Platform for Prostate Cancer Grading and Quantification

W. Huang, R. Randhawa, P. Jain, K. A. Iczkowski, R. Hu, S. Hubbard, J. Eickhoff, H. Basu, R. Roy

JAMA Network Open, 4(11), 2021

AI platform for automated Gleason grading and cancer quantification in prostate pathology.

PubMed →
Dynamic Pricing for Heterogeneous Time-Sensitive Customers

N. Golrezaei, H. Nazerzadeh, R. S. Randhawa

Manufacturing & Service Operations Management, 22(3), 562-581, 2020

Dynamic pricing strategies for service systems with heterogeneous customer time sensitivity and strategic behavior.

SSRN →
Persuading Customers to Buy Early: The Value of Personalized Information Provisioning

K. Drakopoulos, S. Jain, R. S. Randhawa

Management Science, 67(2), 828-853, 2020

Strategic information disclosure to influence customer purchase timing. Shows personalized information can shift demand patterns and improve revenue.

SSRN → Interview → Implications for startups → Watch presentation →
Improving Boundary Classification for Brain Tumor Segmentation and Longitudinal Disease Progression

R. S. Randhawa, A. Modi, P. Jain, P. Warier

Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2016

Deep learning approach for brain tumor boundary detection and tracking disease progression.

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Topic Modeling Using Distributed Word Embeddings

R. S. Randhawa, P. Jain, G. Madan

arXiv preprint, Feb 2016

Novel topic modeling approach leveraging distributed word embeddings for improved semantic coherence.

arXiv →
The Value of Dynamic Pricing in Large Queueing Systems

J. Kim, R. S. Randhawa

Operations Research, 66(2), 409-425, 2017

Asymptotically optimal dynamic pricing policies for observable queues. Shows value of state-dependent pricing in large systems.

SSRN →
The Value of Confession: Admitting Mistakes to Build Reputation

C. Corona, R. S. Randhawa

The Accounting Review, 93(3), 133-161, 2018

Strategic value of transparency and confession in building institutional reputation. Applications to auditing and regulatory oversight.

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Dynamic Scheduling in a Many-Server Multi-Class System: The Role of Customer Impatience in Large Systems

J. Kim, R. S. Randhawa, A. R. Ward

Manufacturing & Service Operations Management, 20(2), 285-301, 2018

Asymptotically optimal scheduling policies for multi-class systems with customer abandonment. Characterizes impact of impatience on optimal rules.

SSRN →
Near-Optimality of Coarse Service Grades for Customer Differentiation in Queueing Systems

H. Nazerzadeh, R. S. Randhawa

Production and Operations Management, 27(3), 578-595, 2018

Shows simple service grade structures capture most value of fine-grained customer differentiation. Practical implications for priority system design.

SSRN →
Optimality Gap of Asymptotically-derived Prescriptions with Applications to Queueing Systems

R. S. Randhawa

Queueing Systems, 83, 131-155, 2016

Quantifies performance of asymptotically-optimal policies in finite systems. Provides theoretical bounds on optimality gaps.

arXiv →
Scheduling Homogeneous Impatient Customers

A. Bassamboo, R. S. Randhawa

Management Science, 62(7), 2129-2147, 2016

Optimal scheduling in service systems with customer abandonment. Characterizes conditions favoring FIFO versus priority policies.

SSRN →
Pricing in Queues without Demand Information

M. Haviv, R. S. Randhawa

Manufacturing & Service Operations Management, 16(3), 401-411, 2014

Robust pricing strategies for queueing systems under demand uncertainty.

SSRN →
Optimal Per-Use Rentals and Sales of Durable Products and Their Distinct Roles in Price Discrimination

S. Gilbert, R. S. Randhawa, H. Sun

Production and Operations Management, 23(3), 393–404, 2014

Joint optimization of rental and sales channels for durable goods. Shows how dual channels enable effective price discrimination.

SSRN →
Designing Flexible Systems using a New Notion of Supermodularity

A. Bassamboo, L. Y. Chu, R. S. Randhawa

Operations Research Letters, 41(1), 107-111, 2013

New theoretical framework for analyzing flexibility in production and service systems.

PDF →
Accuracy of Fluid Approximations for Queueing Systems with Congestion-Sensitive Demand and Implications for Capacity Sizing

R. S. Randhawa

Operations Research Letters, 41(1), 27-31, 2013

Analyzes accuracy of fluid models when demand responds to congestion. Implications for capacity planning.

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A Little Flexibility is All You Need: On the Value of Flexible Resources in Queueing Systems

A. Bassamboo, R. S. Randhawa, J. Van Mieghem

Operations Research, 60(6), 1423-1435, 2012

Shows limited flexibility can capture most benefits of full flexibility in service systems. Establishes diminishing returns.

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Capacity Sizing under Parameter Uncertainty: Safety Staffing Principles Revisited

A. Bassamboo, R. S. Randhawa, A. Zeevi

Management Science, 56(10), 1668-1686, 2010

Robust staffing rules accounting for parameter uncertainty in demand and service rates.

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On the Accuracy of Fluid Models for Capacity Sizing in Queueing Systems with Impatient Customers

A. Bassamboo, R. S. Randhawa

Operations Research, 58(5), 1398-1413, 2010

Third place, 2010 INFORMS JFIG Competition

Theoretical bounds on fluid model accuracy for systems with customer abandonment. Guides when approximations are reliable.

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Optimal Flexibility Configurations in Newsvendor Networks: Going beyond Chaining and Pairing

A. Bassamboo, R. S. Randhawa, J. Van Mieghem

Management Science, 56(8), 1285-1303, 2010

Characterizes optimal flexibility structures in production networks. Extends classical chaining results.

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The Auditor's Slippery Slope: An Analysis of Reputational Incentives

C. Corona, R. S. Randhawa

Management Science, 56(6), 924-937, 2010

Models auditor reputation dynamics and strategic reporting behavior.

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Exploiting Market Size in Service Systems

S. Kumar, R. S. Randhawa

Manufacturing & Service Operations Management, 12(3), 511-526, 2010

Shows how firms can exploit large markets through pricing and capacity decisions in service operations.

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Dynamics of New Product Introduction in Closed Rental Systems

A. Bassamboo, S. Kumar, R. S. Randhawa

Operations Research, 57(6), 1347–1359, 2009

Optimal timing and allocation strategies for introducing new products in rental systems like Netflix.

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Multi-Server Loss Systems with Subscribers

R. S. Randhawa, S. Kumar

Mathematics of Operations Research, 34(1), 142-179, 2009

Theoretical analysis of loss systems with subscription-based access.

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Usage Restriction and Subscription Services: Operational Benefits with Rational Users

R. S. Randhawa, S. Kumar

Manufacturing & Service Operations Management, 10(3), 429–447, 2008

Demonstrates operational benefits of usage restrictions in subscription services with strategic customers.

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Combining Importance Sampling and Temporal Difference Control Variates to Simulate Markov Chains

R. S. Randhawa, S. Juneja

ACM: Transactions on Modeling and Computer Simulation, 14(1), 1-30, 2004

Variance reduction techniques for efficient simulation of Markov chain models.

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