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portfolio
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research
"Monotonically Constrained Polynomial Regression: An Application of Sum of Squares Techniques and Semidefinite Programming " Princeton University Senior Thesis,
Operations Research and Financial Engineering Senior Thesis, Winner of Procter & Gamble Prize for Outstanding Senior Thesis
"BitFunnel: Revisiting Signatures for Search " Bob Goodwin, Michael Hopcroft, Dan Luu, Alex Clemmer, Mihaela Curmei, Sameh Elnikety, and Yuxiong He. Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval,
Best Paper Award Winner
"Shape-Constrained Regression using Sum of Squares Polynomials " Mihaela Curmei, Georgina Hall. Under review @ Operations Research Journal,
"Do Offline Metrics Predict Online Performance in Recommender Systems? " Karl Krauth, Sarah Dean, Alex Zhao, Mihaela Curmei, Wenshuo Guo, Benjamin Recht, Michael I. Jordan. In submission,
"Identification of Patterns in Cystic Fibrosis Physiotherapy with Unsupervised Learning " Olga Liakhovich, Tempest van Schaik, Bianca Furtuna, Mihaela Curmei, Emma Raywood, Helen Douglas, Kunal Kapoor, Nicole Filipow, Eleanor Main. Healthcare Systems, Population Health, and the Role of Health-Tech Workshop @ ICML Workshop,
"Finding Equilibrium in Multi-Agent Games with Payoff Uncertainty " Wenshuo Guo, Mihaela Curmei, Serena Wang, Benjamin Recht, Michael I. Jordan Theoretical Foundations of Reinforcement Learning Workshop @ ICML,
"Designing Recommender Systems with Reachability in Mind " Sarah Dean, Mihaela Curmei, Benjamin Recht Participatory Aproaches to Machine Learning Workshop @ ICML,
"Constructing and adjusting estimates for household transmission of SARS-CoV-2 from prior studies, widespread-testing and contact-tracing data " Mihaela Curmei, Andrew Ilyas*, Owain Evans, Jacob Steinhardt International Journal of Epidemiology,
"Quantifying Availability and Discovery in Recommender Systems via Stochastic Reachability " Sarah Dean*, Mihaela Curmei*, Benjamin Recht International Conference on Machine Learning; ICML,
"Multi-learner risk reduction under endogenous participation dynamics " Sarah Dean, Mihaela Curmei, Lillian J Ratliff, Jamie Morgenstern, Maryam Fazel Under Review,
"Towards Psychologically-Grounded Dynamic Preference Models " Mihaela Curmei, Andreas Haupt, Dylan Hadfield-Menell, Benjamin Recht 16th ACM Conference on Recommender Systems, RecSys,
"Private Matrix Factorization with Public Item Features " Mihaela Curmei, Walid Krichene, Li Zhang, Mukund Sundararajan Proceedings of the 17th ACM Conference on Recommender Systems,
talks
"Talk 1 on Relevant Topic in Your Field " UC San Francisco, Department of Testing,
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"Tutorial 1 on Relevant Topic in Your Field " UC-Berkeley Institute for Testing Science,
"Talk 2 on Relevant Topic in Your Field " London School of Testing,
"Conference Proceeding talk 3 on Relevant Topic in Your Field " Testing Institute of America 2014 Annual Conference,
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teaching
"Teaching experience 1 " University 1, Department,
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Undergraduate course, University 1, Department, 2014
"Teaching experience 2 " University 1, Department,
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Workshop, University 1, Department, 2015