publications

Contracting for AI and Innovation Services

Research on contracting, pricing, and service design for AI-enabled and innovation-intensive settings.

1. Hold Back, Team Up, or Take Over? Optimal Timing of AI Access

   Mojtaba Abdolmaleki and Izak Duenyas

   Abs Paper

   When should a firm withhold AI access from an employee, allow human-AI collaboration, or take the project over with AI? We study this question in a continuous-time principal-agent model of stochastic project completion with hidden effort and privately observed success. The principal chooses success rewards, the timing of AI access, and termination among three modes: human-only work, human-AI collaboration, and principal-run AI. The optimal contract has an ordered phase structure: the phases always appear in the order human-only work, human-AI collaboration, and principal-run AI, but any phase may have zero duration. We characterize the optimal policy in all primitive parameter regions: the firm may use principal-run AI immediately, rely on human-only work before AI takeover, begin with collaboration before takeover, or use all three phases for positive duration. This contrasts with the first-best static operating benchmark, in which effort and reporting are contractible and the principal uses a single mode with the highest static operating value. The structure of the optimal contract yields several implications. Upon granting AI access the worker’s success reward decreases; a higher shirking benefit for human component accelerates AI access; a more capable standalone AI can delay and shorten collaboration; and allowing collaboration can reduce the worker’s initial information rent. We also characterize the optimal contract in presence of shadow AI: unauthorized AI tools that the agent can use before the firm authorizes AI access. Shadow AI has two forms: a cheap shadow tool that complements human input and a costly firm-grade shadow tool that can be privately financed only by diverting enough project resources.

2. Pricing Delayed Agentic AI Services: When High-Value Jobs Wait Longer

   Mojtaba Abdolmaleki, Izak Duenyas, and Roman Kapuscinski

   Abs Paper

   We study pricing and scheduling mechanisms for agentic AI services operated on capacity-constrained compute pipelines. Inference-time compute is endogenous: more compute improves output quality but delays completion and creates congestion. We characterize optimal mechanisms when customers value quality and dislike delay, showing that higher-value customers may optimally receive more compute and higher-quality outputs while being served later. Numerical experiments show that reverse priority can increase profit relative to first-come-first-served and conventional forward-priority policies. Thus, in compute-constrained AI services, premium need not mean faster. It may mean better but slower.

3. Multi-Stage Contracting Without Sandbagging or Hype

   Mojtaba Abdolmaleki, Izak Duenyas, Roman Kapuscinski, and Curtis R. Taylor

   Abs Paper

   Many ventures create value only upon delivery, but progress and completion are privately observed by the agent running the project. We study a model with moral hazard and limited liability: working generates stochastic breakthroughs while shirking yields private benefits. The agent may exaggerate or delay reporting progress and may strategically sit on completion. We characterize the optimal dynamic contract in this setting. Absent inspections, it delivers truthful reporting via a soft deadline, a probation phase with increasing termination risk during silence, and a short deadline after progress is reported. With inspections, oversight combines random audits during silence to incentivize reporting of breakthroughs, a report-triggered check that the agent is not sitting on a completed project, and late-stage inspections to verify milestone claims.

Revenue Management

Research on pricing, revenue management, search frictions, privacy, and platform operations.

1. Homomorphic Encrypted Revenue Management

   Mojtaba Abdolmaleki and Ruslan Momot

   Minor revision at Management Science.

   Award Abs Paper

   Finalist, IBM student paper award

   We develop a homomorphic encryption-based approach to privacy preservation in a dynamic personalized pricing setting. The firm encrypts incoming and historical customer data, estimates demand, and personalizes prices directly on encrypted data without decrypting them. The approach protects all customers, both incoming and historical, and provides perfect privacy protection with no expected-revenue loss, though it is computationally expensive. We also develop a hybrid privacy-preservation approach that reduces computational cost without significant compromise in expected revenue.

2. Joint Pricing and Delayed Empty Relocation Policies for Ride-sourcing Systems

   Mojtaba Abdolmaleki, Xiuli Chao, Tara Radvand, and Yafeng Yin

   R&R at Management Science. Presentations: INFORMS RMP Conference (2024), UCI (2024), NYU Stern (2024), MIT IDSS (2023), UMN ISyE (2023)

   Abs Paper

   We develop a near-optimal dynamic pricing and empty vehicle relocation mechanism for a ride-sourcing system with limited customer patience. The system is modeled as a network of double-ended queues. We establish a fluid limit in a large market regime, show that the fluid-based solution provides an upper bound on performance, and develop a simple dynamic policy based on the fluid solution that nearly achieves that bound. The policy balances supply utilization and customer waiting times under the Square Root Safety staffing rule and is evaluated using empirical data from DiDi Chuxing.

3. A Training-free Method for LLM Text Attribution

   Tara Radvand, Mojtaba Abdolmaleki, Mohamed Mostagir, and Ambuj Tewari

   Abs Paper Demo Code

   Verifying the provenance of content is crucial for educational institutions, social media platforms, firms, and other organizations. As LLM-generated text becomes almost indistinguishable from human-generated content, we design zero-shot statistical tests to distinguish text generated by different known sets of LLMs and to identify whether text was generated by a known LLM or an unknown source. We prove that Type I and Type II errors decrease exponentially with text length, extend the theory to black-box access via sampling, and validate the method numerically under adversarial post-editing.

4. Price Restraining Policies and Search Costs: Economic Analysis and Implications

   Mojtaba Abdolmaleki, Ozge Sahin, and Roman Kapuscinski

   Presentations: INFORMS RMP Conference (2025). Invited for INFORMS Annual Meeting (2024)

Transportation

Research on ride-sourcing, vehicle relocation, transit, electrification, platooning, and traffic control.

1. Itinerary Planning for Cooperative Truck Platooning

   Mojtaba Abdolmaleki, Maryam Shahabi, Yafeng Yin, and Neda Masoud

   Transportation Research Part B: Methodological, 2021

   Paper
2. A Unifying Graph-Coloring Approach for Intersection Control in a Connected and Automated Vehicle Environment

   Mojtaba Abdolmaleki, Yafeng Yin, and Neda Masoud

   Presentation: MIT Mobility Initiative (2021)

   Paper
3. Transit Timetable Synchronization for Transfer Time Minimization

   Mojtaba Abdolmaleki, Neda Masoud, and Yafeng Yin

   Transportation Research Part B: Methodological, 2020

   Paper
4. Vehicle-to-vehicle Wireless Power Transfer: Paving the Way toward an Electrified Transportation System

   Mojtaba Abdolmaleki, Neda Masoud, and Yafeng Yin

   Transportation Research Part C: Emerging Technologies, 2019

   Paper
5. Proactive Shuttle Dispatching in Large-scale Dynamic Dial-a-ride Systems

   Amirmahdi Tafreshian, Mojtaba Abdolmaleki, Neda Masoud, and H. Wang

   Transportation Research Part B: Methodological, 2021

   Paper
6. Investigating the Potential of Truck Platooning on Energy Savings: An Empirical Study on the US National Highway Freight Network

   X. Sun, H. Wu, Mojtaba Abdolmaleki, Yafeng Yin, and B. Zou

   Transportation Research Record, 2021

   Paper
7. Approximation Algorithms and Hardness of Approximation for Itinerary Planning of Cooperative Truck Platooning

   Mojtaba Abdolmaleki

   Under preparation

Graph Theory

Research on graph coloring, graph decompositions, and related combinatorial structures.

1. On Uniquely k-list Colorable Planar Graphs, Graphs on Surfaces, and Regular Graphs

   Mojtaba Abdolmaleki, Joan P. Hutchinson, S. Gh. Ilchi, E. S. Mahmoodian, N. Matsumoto, and M. A. Shabani

   Graphs and Combinatorics, 2018

   Paper arXiv
2. On Decomposing Complete Tripartite Graphs into 5-cycles

   Mojtaba Abdolmaleki, S. Gh. Ilchi, E. S. Mahmoodian, and M. A. Shabani

   2019

   Paper