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.
* co-first author·† alphabetical order
Boussioux, L.†, Doshi, A., Hauser, O., Hosanagar, K.
MIT Sloan Management Review (To Appear)
Lane, J.N.*, Boussioux, L.*, Ayoubi, C., Chen, Y.H., Lin, C., Spens, R., Wagh, P., Wang, P.H.
Management Science
Cunningham, C., Baik, R., Nageswaran, L., Boussioux, L.
Preprint (SSRN)
Narad, R., Boussioux, L., Wagner, M.
Preprint
Boussioux, L.*, Jacquillat, A.*, Reger, R., Wachspress, J.
Preprint, under review at Operations Research
Liu, S., Boussioux, L., Xu, J.
Work in progress
Boussioux, L., Poulidis, S.
Work in progress
Siqueira, A.C.O., Agafonow, A., Perez, M., Boussioux, L.
Submitted to HICSS
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
Boussioux, L.*, Zhao, Z.*, Cho, S.*
Work in progress
Cunningham, C., Baik, R., Boussioux, L., Nageswaran, L.
Major revision at Management Science
Boussioux, L.*, Zhao, Z.*, Cho, S.*
In preparation for MIS Quarterly
Das, S., Boussioux, L., Shunko, M.
In preparation for M&SOM
Boussioux, L., Kc, J., Valecha, R.
In preparation for MIS Quarterly
Wasserkrug, S., Boussioux, L., den Hertog, D., Mirzazadeh, F., Birbil, I., Kurtz, J., Maragno, D.
AAAI 2025, 39(27)
Wang, Y., You, T.G., Boussioux, L., Liu, S.
NeurIPS 2025 — ML & Optimization Workshop
Narad, R., Boussioux, L., Wagner, M.
NeurIPS 2025 — ML & Optimization Workshop
Bao, J., Wu, B., Impink, S. M., Koning, R., Boussioux, L.
Academy of Management Proceedings, 2025(1)
Boussioux, L.*, Lane, J.*, Zhang, M., Jacimovic, V., Lakhani, K.
Organization Science, 35(5), 1589-1607
Wasserkrug, S.*, Boussioux, L.*, Sun, W.
Tutorials in Operations Research, 1-49
Bertsimas, D., Carballo, K., Boussioux, L., Li, M., Paskov, A., Paskov, I.
Machine Learning, 113, 159–183
Boussioux, L., Chen, H., Fan, M., Jain, A.
ICIS 2025 Proceedings
Choi, S. Y., Lifshitz‐Assaf, H., Lazar, M., Mateja, D., Raisch, S., Randazzo, S., Lee, D., Lane, J. N., Ayoubi, C., Emuna, H., Dell’Acqua, F., Kellogg, K. C., Lakhani, K. R., Mollick, E., Candelon, F., Zhou, E., Boussioux, L., Zhang, M., Jaćimović, V., Rüffer, F., Heinzl, A.
Academy of Management Proceedings, 2024(1)
Boussioux, L.*, Ma, Y.*, Thomas, N., Bertsimas, D., et al.
International Journal of Radiation Oncology, 117(3), 738-749
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
Boussioux, L.*, Zeng, C.*, Guénais, T., Bertsimas, D.
Weather and Forecasting, 37(6), 817-831
Bertsimas, D., Boussioux, L.†, Zeng, C.
Preprint, in prep for INFORMS Journal of Applied Analytics
Bertsimas, D., Boussioux, L.†
Reject and Resubmit at JMLR
Carballo, K., Ma, Y., Na, I., Boussioux, L., Zeng, C., Soenksen, L., Bertsimas, D.
Under review at The Lancet
Boussioux, L.*, Kantor, C.*, Skreta, M.*, et al.
CVPR 2022 — CV4Animals
Żołna K.*, Saharia, C.*, Boussioux, L.*, Hui, D.Y., Chevalier-Boisvert, M., Bahdanau, D., Bengio, Y.
AAAI 2020 / IJCNN 2021
Kantor, C. A., Boussioux, L., Rauby, B., Talbot, H.
Proceedings of the AAAI Conference on Artificial Intelligence, 35(18), 15807-15808
Kantor, C. A., Boussioux, L., Rauby, B., Talbot, H.
Proceedings of the AAAI Conference on Artificial Intelligence, 35(17), 15316-15322
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)
Bertsimas, D., Boussioux, L.†, Cory-Wright, R., Delarue, A., Digalakis, V., Jacquillat, A., et al.
Health Care Management Science, 24(2), 253–272
Kantor, C., Rauby, B., Boussioux, L., Talbot, H.
AAAI 2020 — Fall Symposium on AI for Social Good
Venuto, D., Chakravorty, J., Boussioux, L., Wang, J., McCracken, G., Precup, D.
arXiv (Cornell University)
Boussioux, L., Giro-Larraz, T., Guille-Escuret, C., Cherti, M., Kégl, B.
arXiv (Cornell University)
Venuto, D., Boussioux, L., Wang, J., Dali, R., Chakravorty, J., Bengio, Y., Precup, D.
arXiv (Cornell University)
The same papers, three other ways to wander them — as a transit network, a night sky of embeddings, and a river through time.
Each line is a research area; each station a paper, placed chronologically. Capsule stations are interchanges — papers connecting several areas. Dashed stations are under construction (work in progress); the dotted stub rides into what's next. ★ marks awards. Click a line's name plate to board a train — it stops at every station and unveils each paper along the way. Click a station to open the paper.