Probabilistic Machine Learning Group, Aalto University, Finland
GPA: 5/5
Thesis Title: "Probabilistic user modelling methods for improving human-in-the-loop machine learning for prediction" [link]
Supervisor: Prof. Samuel Kaski, Advisor: Tomi Peltola.
Description: Working on probabilistic user modelling, regression, experimental design, and multi-armed bandit problem (See publications).
Other duties: Coordinator of the European project MindSee for the partner Aalto University (PI Samuel Kaski).
University of Tehran, Tehran, Iran
GPA: 18.17/20
Honors Ranked 3rd, in cumulative GPA, in class of 2011.
Thesis Title: "A Developmental Method for Multimodal Sensory Integration"
Advisors: Prof. Majid Nili Ahmadabadi, Prof. Maryam S. Mirian
Description: I worked on mathematical modeling of multisesnory decision making of human using reinforcement learning (see Plos One 2014 and [link])
Thesis grade: 20/20
Ferdowsi University of Mashhad, Mashhad, Iran
GPA: 17.82/20 (last two years GPA: 18.87/20)
Honors: Ranked 3rd, in cumulative GPA, in class of 2007.
Thesis: "Using Genetic Algorithm to Solve The University Course Timetabling problem"
Thesis grade: 20/20
Advisor: Prof. Saeid Abrishami
Mashhad, Iran
GPA: 18.96/20
Jacucci, G., Daee, P., Vuong, T., Andolina, S., Klouche, K., Sjöberg, M., Ruotsalo, T. and Kaski, S., 2021. Entity Recommendation for Everyday Digital Tasks. ACM Transactions on Computer-Human Interaction (TOCHI), 28(5), pp.1-41. [link].
Jacucci, G., Barral, O., Daee, P., Wenzel, M., Serim, B., Ruotsalo, T., Pluchino, P., Freeman, J., Gamberini, L., Kaski, S. and Blankertz, B., 2019. Integrating neurophysiological relevance feedback in intent modeling for information retrieval. Journal of the Association for Information Science and Technology (JASIST), 70(9), pp.917-930. [link].
Sundin, I., Peltola, T., Micallef, L., Afrabandpey, H., Soare, M., Mamun Majumder, M., Daee, P., He, C., Serim, B., Havulinna, A. and Heckman, C., 2018. Improving genomics-based predictions for precision medicine through active elicitation of expert knowledge. Bioinformatics, 34(13), pp.i395-i403. [link] [code].
Daee, P., Peltola, T., Soare, M. and Kaski, S., 2017. Knowledge elicitation via sequential probabilistic inference for high-dimensional prediction. Machine Learning, 106(9-10), pp.1599-1620. [link] [code].
Daee, P., Mirian, M.S. and Ahmadabadi, M.N., 2014. Reward maximization justifies the transition from sensory selection at childhood to sensory integration at adulthood. PLOS ONE, 9(7), p.e103143. [link].
Colella, F., Daee, P., Jokinen, J., Oulasvirta, A., and Kaski, S. 2020. Human Strategic Steering Improves Performance of Interactive Optimization. In 28th International Conference on User Modeling, Adaptation and Personalization. [preprint][Demo][code]. (24% Acceptance Rate)
Peltola, T., Celikok, M., Daee, P., and Kaski, S., 2019. Machine Teaching of Active Sequential Learners. In 33rd Conference on Neural Information Processing Systems (NeurIPS 2019). [blog][paper][code]. (21% Acceptance Rate)
Celikok, M., Peltola, T., Daee, P., and Kaski, S., 2019. Interactive AI with a Theory of Mind. In ACM CHI 2019 Workshop on Computational Modeling in Human-Computer Interaction. [link].
Daee, P., Peltola, T., Vehtari, A. and Kaski, S., 2018, March. User Modelling for Avoiding Overfitting in Interactive Knowledge Elicitation for Prediction. In 23rd International Conference on Intelligent User Interfaces (pp. 305-310). ACM. [link] [preprint] [code]. (23% Acceptance Rate)
Daee, P., Peltola, T., Soare, M. and Kaski, S., 2016. Probabilistic Expert Knowledge Elicitation of Feature Relevances in Sparse Linear Regression. In FILM 2016, NIPS Workshop on Future of Interactive Learning Machines.
Daee, P., Pyykkö, J., Glowacka, D. and Kaski, S., 2016, March. Interactive intent modeling from multiple feedback domains. In Proceedings of the 21st International Conference on Intelligent User Interfaces (pp. 71-75). ACM. [link] [poster] [slides][preprint]. (25% Acceptance Rate)
Daee, P., Taheri, K. and Moradi, H., 2014, May. A sampling algorithm for reducing the number of collision checking in probabilistic roadmaps. In 22nd Iranian Conference on Electrical Engineering (pp. 1313-1316). IEEE. [link] (Best paper award in the control field).
Two book chapters in: Y. Neuvo. (ed.), E. Ormala (ed.), and M. Kuikka (ed.), "Bit Bang 8: Digitalization,". ISBN 978-952-60-1100-4 (printed), ISBN 978-952-60-1101-1 (pdf). Aalto University; Aalto-yliopisto 2016. [link]
"Subjective Context Awareness: Machines That Understand Personal Accounts, Feelings, and Emotions", pp. 81-110.
"The Digital Health Society: Perspectives on Real, Predictive, and Preventive Care", pp. 131-158.
Peltola, T., Celikok, M., Daee, P., and Kaski, S., 2019. Modelling User's Theory of AI's Mind in Interactive Intelligent Systems. [arXiv preprint].
Machine Teaching of Active Sequential Learners [GitHub Link].
Knowledge Elicitation for Linear Regression [GitHub Link].
Human Overfitting in Interactive Machine Learning [GitHub Link].
Awarded 5,000 euros Nokia Scholarship from Nokia Foundation, intended to encourage efficient, fast-progressing doctoral studies and research, 2019.
Awarded 3m Toman (~1000$) support from The Cognitive Science and Technology Council of Iran (CSTC) for the paper "Reward Maximization Justifies the Transition from Sensory Selection at Childhood to Sensory Integration at Adulthood", 2014.
Best paper award in 22nd Iranian Conference on Electrical Engineering (ICEE), 2014.
Ranked 3rd, in cumulative GPA, among MSc students (Artificial Intelligence), class of 2011, University of Tehran.
Ranked 3rd, in cumulative GPA, among BSc students of Computer Engineering (Software), class of 2007, Ferdowsi University of Mashhad.
Ranked 1st, in average GPA, among BSc students of Computer Engineering (Software), Ferdowsi University of Mashhad, Fall 2009 and Spring 2010.
Natural Language Processing, personalized recommender systems
Probabilistic modelling, interactive machine learning, high dimensional prediction
Sequential decision making, experimental design, multi-armed bandit, Cognitive science, reinforcement learning
"Bayesian Optimization", guest lecturer in the course ELEC-E7851 - Computational User Interface Design, Aalto University. November 2019.
“Gaussian Mixture Models” and "Gaussian Processes Regression", guest lecturer in the course ELEC-E8122 - Multivariate regression methods L, Aalto University, November 2015 and November 2016.
"Introduction to Dempster-Shafer Theory" and "Introduction to Fuzzy Classification", workshop on "Fuzzy Logic, Fuzzy Mathematics, and their Applications", Iranian Fuzzy Systems Society, University of Tehran, Iran, January 2013.
Aalto University:
Advanced Probabilistic Methods. Prof. Pekka Marttinen. Spring 2019.
Advanced Probabilistic Methods. Prof. Pekka Marttinen and Pekka Parviainen. Spring 2017.
Machine Learning. Prof. Alexander Jung and Markus Heinonen. Fall 2016.
Advanced Probabilistic Methods. Prof. Pekka Marttinen. Spring 2016.
Bayesian Data Analysis. Prof. Aki Vehtari. Fall 2015.
Machine Learning. Prof. Jorma Laaksonen. Fall 2015.
University of Tehran
Machine Learning (Reinforcement Learning). Prof. Majid Nili Ahmadabadi. Fall 2013.
Artificial Intelligence. Prof. Hadi Moradi. Spring 2013.
Pattern Recognition. Prof. Maryam Mirian. Fall 2012.
Farsi (Persian): Native.
English: Fluent.
TOEFL IBT (November 2013): 107 (R29, L29, S26, W23)