Papers, preprints,
and work in progress.

My research sits at the intersection of generative AI, machine learning, and optimization, with one unifying goal: designing human and AI systems that make better decisions on the problems that matter, from innovation to healthcare to the climate.

Methodologically, I build frameworks that fuse the predictive power of modern machine learning with the rigor of operations research: combining multimodal deep learning with gradient boosted models to forecast hurricane tracks and intensity, integrating tabular, imaging, text, and time series data into clinical pipelines that outperform single source models by 6 to 33 percent, and coupling prediction with prescriptive optimization to suppress wildfires, cut industrial air pollution by a third, and reallocate scarce resources during COVID-19.

A second, increasingly central thread asks how people and large language models should actually collaborate. Through field and behavioral experiments, I find that human guided AI partnerships can augment creativity and innovation at scale, yet how AI advice is delivered proves decisive: black box recommendations can sharpen evaluation quality while persuasive narrative explanations quietly erode it. The consistent message across every domain is that AI delivers the most value not as a replacement for human or analytical expertise, but as a carefully engineered complement to it, from the internals of neural solvers up to the organizations, workflows, and future of work they reshape.

The research atlas

I love seeing data across different dimensions and in more artistic ways. Here are five fun ways to take in all of my research at a glance.

GenAI & Human-AI CollaborationGenAI & Human-AIOptimizationOptimizationDeep Learning FoundationsDeep LearningMultimodal AIMultimodal AIHealthcareHealthcareSustainabilitySustainability201820192020202120222023202420252026★★★★★★★★★

Research output as a river. Each stream is an area, and its width reflects all the years I spent on the projects flowing through it. Hover a stream to follow it, or a dot to find a paper, then click to open it.

All work

* co-first author·† alphabetical order

Area
Type
Sort
journal2026

The Hidden Cost of AI-Assisted Creativity

Boussioux, L.†, Doshi, A., Hauser, O., Hosanagar, K.

MIT Sloan Management Review (To Appear)

GenAI & Human-AI Collaboration
journal2026

The Narrative AI Advantage? A Field Experiment on Generative AI-Augmented Evaluations of Early-Stage Innovations

Lane, J.N.*, Boussioux, L.*, Ayoubi, C., Chen, Y.H., Lin, C., Spens, R., Wagh, P., Wang, P.H.

Management Science

  • 1st Place, Wharton People Analytics 2025
  • Best in Track Paper, ICIS 2025
Slides
GenAI & Human-AI Collaboration
preprint2026

Decision Making on Draft: Human-AI Collaboration in Supply Chains

Cunningham, C., Baik, R., Nageswaran, L., Boussioux, L.

Preprint (SSRN)

GenAI & Human-AI CollaborationOptimization
preprint2026

Beyond Solving: Prescriptive Probing for Neural Combinatorial Optimization

Narad, R., Boussioux, L., Wagner, M.

Preprint

Deep Learning FoundationsOptimization
preprint2026

Predictive and Prescriptive Analytics toward Optimizing Wildfire Suppression

Boussioux, L.*, Jacquillat, A.*, Reger, R., Wachspress, J.

Preprint, under review at Operations Research

Slides
SustainabilityOptimizationMultimodal AI
wip2026

Creating Quality of Care Indices for Trauma Patients Using Machine Learning and LLMs

Liu, S., Boussioux, L., Xu, J.

Work in progress

HealthcareDeep Learning Foundations
wip2026

Use-Side Governance in AI Skill Ecosystems

Boussioux, L., Poulidis, S.

Work in progress

GenAI & Human-AI Collaboration
wip2026

When Detailed Rubrics Backfire: Example Calibration and Checklist Conflict in LLM-Based Innovation Review

Huang, S., Liang, J., Lu, L., Mao, S., Boussioux, L.

Work in progress

GenAI & Human-AI Collaboration
preprint2026

AI for Ethical Governance: Generative and Ontological Approaches to Institutionalizing Mission and Social Responsibility in Enterprises

Siqueira, A.C.O., Agafonow, A., Perez, M., Boussioux, L.

Submitted to HICSS

GenAI & Human-AI Collaboration
preprint2026

NollaMD: A Foundational Joint-Embedded Multimodal Reasoning Model for Automated Clinical Interviewing, Differential Diagnosis, and SOAP Note Generation with Robust Medical Vision and Conversational Capabilities

Soenksen, L.R.*, Grasby, L.*, Geiger, S.*, Pierce, M.*, Stokes, J., Dao, D.Q., Wenus, L., Badri, O., Groh, M., Boussioux, L., Havele, S., Tamez, M., Mina, M.J.

Submitted to The New England Journal of Medicine

GenAI & Human-AI CollaborationDeep Learning FoundationsMultimodal AIHealthcare
wip2026

Mapping the AI Boom: A Displacement Field of How Startups Reposition After ChatGPT

Wang, M.†, Boussioux, L.†, Kotha, S.†

Work in progress

GenAI & Human-AI Collaboration
wip2026

Organizational Digital Twins: An LLM-Powered Multi-Agent Framework for Strategic Decision Simulation

Boussioux, L.*, Doshi, A.*

In preparation for Information Systems Research

GenAI & Human-AI Collaboration
wip2026

Writing for Two Readers: Human–Agent Co-Production and the Convergence–Divergence Paradox in an Agentic Skill Commons

Boussioux, L.*, Zhao, Z.*, Cho, S.*

Work in progress

GenAI & Human-AI Collaboration
preprint2025

Agreeing to Disagree: Human–AI Collaboration in Ethical Decision-Making

Cunningham, C., Baik, R., Boussioux, L., Nageswaran, L.

Major revision at Management Science

Slides
GenAI & Human-AI Collaboration
wip2025

One Tool, One Taste? Vibe Coding and the Homogenization of the Visual Web

Boussioux, L.*, Zhao, Z.*, Cho, S.*

In preparation for MIS Quarterly

GenAI & Human-AI Collaboration
wip2025

Climate-Smart Seasonal Staffing: Forecast-Driven Batch Hiring for Perishable Harvests

Das, S., Boussioux, L., Shunko, M.

In preparation for M&SOM

SustainabilityOptimization
wip2025

Automating Urgency Triage in Crisis Mapping: A Multi-Stage Human-AI Collaboration Framework

Boussioux, L., Kc, J., Valecha, R.

In preparation for MIS Quarterly

GenAI & Human-AI CollaborationSustainability
conference2025

Enhancing Decision Making through the Integration of Large Language Models and Operations Research Optimization

Wasserkrug, S., Boussioux, L., den Hertog, D., Mirzazadeh, F., Birbil, I., Kurtz, J., Maragno, D.

AAAI 2025, 39(27)

GenAI & Human-AI CollaborationOptimization
workshop2025

SOLID: a Framework of Synergizing Optimization and LLMs for Intelligent Decision-Making

Wang, Y., You, T.G., Boussioux, L., Liu, S.

NeurIPS 2025 — ML & Optimization Workshop

GenAI & Human-AI CollaborationOptimization
workshop2025

Mechanistic Interpretability for Neural TSP Solvers

Narad, R., Boussioux, L., Wagner, M.

NeurIPS 2025 — ML & Optimization Workshop

Deep Learning FoundationsOptimization
journal2024

The Crowdless Future? Generative AI and Creative Problem Solving

Boussioux, L.*, Lane, J.*, Zhang, M., Jacimovic, V., Lakhani, K.

Organization Science, 35(5), 1589-1607

Slides
GenAI & Human-AI Collaboration
journal2024

Combining Large Language Models and OR/MS to Make Smarter Decisions

Wasserkrug, S.*, Boussioux, L.*, Sun, W.

Tutorials in Operations Research, 1-49

GenAI & Human-AI CollaborationOptimization
journal2024

Holistic Deep Learning

Bertsimas, D., Carballo, K., Boussioux, L., Li, M., Paskov, A., Paskov, I.

Machine Learning, 113, 159–183

Deep Learning Foundations
conference2024

Socratic Iterative Reasoning: Enhancing LLM Decision-Making in the Beer Game Supply Chain

Boussioux, L., Chen, H., Fan, M., Jain, A.

ICIS 2025 Proceedings

GenAI & Human-AI CollaborationOptimization
journal2023

Automated Segmentation of Sacral Chordoma Tumors and Surrounding Muscles Using Deep Learning Ensemble

Boussioux, L.*, Ma, Y.*, Thomas, N., Bertsimas, D., et al.

International Journal of Radiation Oncology, 117(3), 738-749

HealthcareDeep Learning Foundations
PhD thesis2023

Multimodality: Models, Algorithms, and Applications

Boussioux, L.

Massachusetts Institute of Technology, Operations Research Center · Advised by Dimitris Bertsimas

Multimodal AIHealthcareSustainabilityDeep Learning Foundations
journal2022

Integrated Multimodal Artificial Intelligence Framework for Healthcare Applications

Soenksen, L.*, Ma, Y.*, Zeng, C.*, Boussioux, L.*, Carballo, K.*, Na, I.*, Wiberg, H., Li, M., Fuentes, I., Bertsimas, D.

npj Digital Medicine, 5(1), 1-10

  • 1st Place, MIT Cognex Poster Competition, 2022
Multimodal AIHealthcare
journal2022

Hurricane Forecasting: A Novel Multimodal Machine Learning Framework

Boussioux, L.*, Zeng, C.*, Guénais, T., Bertsimas, D.

Weather and Forecasting, 37(6), 817-831

Multimodal AISustainability
preprint2022

Reducing Air Pollution through Machine Learning

Bertsimas, D., Boussioux, L.†, Zeng, C.

Preprint, in prep for INFORMS Journal of Applied Analytics

  • 2nd Place, INFORMS' Doing Good with Good OR, 2023
  • Zetta Prize Winner, 2023
SustainabilityDeep Learning Foundations
preprint2022

Ensemble Modeling for Time Series Forecasting: an Adaptive Robust Optimization Approach

Bertsimas, D., Boussioux, L.†

Reject and Resubmit at JMLR

Deep Learning FoundationsOptimization
preprint2022

TabText: a Systematic Approach to Aggregate Knowledge Across Tabular Data Structures

Carballo, K., Ma, Y., Na, I., Boussioux, L., Zeng, C., Soenksen, L., Bertsimas, D.

Under review at The Lancet

Multimodal AIHealthcareDeep Learning Foundations
workshop2022

Multimodal Artificial Intelligence for Wildlife Analytics

Boussioux, L.*, Kantor, C.*, Skreta, M.*, et al.

CVPR 2022 — CV4Animals

  • 1st Place, INFORMS Poster Competition, 2021
  • 3rd Place, MIT Generator Research Competition, 2021
Multimodal AISustainability
conference2021

Combating False Negatives in Adversarial Imitation Learning

Żołna K.*, Saharia, C.*, Boussioux, L.*, Hui, D.Y., Chevalier-Boisvert, M., Bahdanau, D., Bengio, Y.

AAAI 2020 / IJCNN 2021

Multimodal AIDeep Learning Foundations
conference2021

Gradient-Based Localization and Spatial Attention for Confidence Measure in Fine-Grained Recognition using Deep Neural Networks

Kantor, C. A., Boussioux, L., Rauby, B., Talbot, H.

Proceedings of the AAAI Conference on Artificial Intelligence, 35(18), 15807-15808

Deep Learning FoundationsMultimodal AI
conference2021

Over-MAP: Structural Attention Mechanism and Automated Semantic Segmentation Ensembled for Uncertainty Prediction

Kantor, C. A., Boussioux, L., Rauby, B., Talbot, H.

Proceedings of the AAAI Conference on Artificial Intelligence, 35(17), 15316-15322

Deep Learning FoundationsMultimodal AI
workshop2021

Geo-Spatiotemporal Features and Shape-Based Prior Knowledge for Fine-grained Imbalanced Data Classification

Kantor, C. A., Skreta, M., Rauby, B., Boussioux, L., Jehanno, E., Luccioni, A. S., Rolnick, D., Talbot, H.

HAL (Le Centre pour la Communication Scientifique Directe)

Deep Learning FoundationsSustainability
journal2020

From Predictions to Prescriptions: A Data-Driven Response to COVID-19

Bertsimas, D., Boussioux, L.†, Cory-Wright, R., Delarue, A., Digalakis, V., Jacquillat, A., et al.

Health Care Management Science, 24(2), 253–272

  • INFORMS' William Pierskalla Best Paper Award, 2020
HealthcareOptimization
workshop2020

Asymptotic Cross-Entropy Weighting and Guided-Loss in Supervised Hierarchical Setting Using Deep Attention Network

Kantor, C., Rauby, B., Boussioux, L., Talbot, H.

AAAI 2020 — Fall Symposium on AI for Social Good

Deep Learning Foundations
preprint2020

oIRL: Robust Adversarial Inverse Reinforcement Learning with Temporally Extended Actions

Venuto, D., Chakravorty, J., Boussioux, L., Wang, J., McCracken, G., Precup, D.

arXiv (Cornell University)

Deep Learning Foundations
workshop2019

InsectUp: Crowdsourcing Insect Observations to Assess Demographic Shifts and Improve Classification

Boussioux, L., Giro-Larraz, T., Guille-Escuret, C., Cherti, M., Kégl, B.

arXiv (Cornell University)

Deep Learning FoundationsSustainability
workshop2019

Avoidance Learning Using Observational Reinforcement Learning

Venuto, D., Boussioux, L., Wang, J., Dali, R., Chakravorty, J., Bengio, Y., Precup, D.

arXiv (Cornell University)

Deep Learning Foundations