COURSE INSTRUCTORS / FACULTY

  • Regina Barzilay is a Delta Electronics Professor in the Department of Electrical Engineering and Computer Science and a member of the Computer Science and Artificial Intelligence Laboratory at the Massachusetts Institute of Technology. Her research interests are in natural language processing, applications of deep learning to chemistry and oncology.

    Regina Barzilay

    EECS
    MIT Professor
    Machine Learning

  • Dimitri Bertsekas is a Professor with the Department of Electrical Engineering and Computer Science, and a member of the National Academy of Engineering. His research focuses on optimization theory and algorithms, with an emphasis on stochastic systems and their applications in various domains, such as data networks, transportation, and power systems.

    Dimitri Bertsekas

    EECS
    MIT Professor
    Probability

  • Karene Chu is leading the effort in the production and running of the IDSS Micromasters Program in Statistics and Data Science. As a digital learning lab fellow at MIT, she made major and significant contribution to the MITx courses in mathematics, including the Calculus series and Differential equations series.

    Karene Chu

    Lecturer and Research Scientist
    MM SDS

  • Esther Duflo is the Abdul Latif Jameel Professor of Poverty Alleviation and Development Economics in the Department of Economics at the Massachusetts Institute of Technology and a co-founder and co-director of the Abdul Latif Jameel Poverty Action Lab (J-PAL). In her research, she seeks to understand the economic lives of the poor, with the aim to help design and evaluate social policies. She has worked on health, education, financial inclusion, environment, and governance.

    Esther Duflo

    Dept. of Economics
    MIT Professor, Nobel Prize Winner
    Data Analysis in Social Science

  • Sara Fisher Ellison is a Senior Lecturer in the MIT Economics Department. She has been a fellow at both the Institute for Advanced Study and the Hoover Institute. Her recent research has investigated a number of questions in industrial organization, with a focus on the pharmaceutical industry and ecommerce.

    Sara Fisher Ellison

    Dept. of Economics
    MIT Professor
    Data Analysis in Social Science

  • Tommi S. Jaakkola received M.Sc. in theoretical physics from Helsinki University of Technology and Ph.D. from MIT in computational neuroscience. His research covers theory, algorithms, and applications of machine learning, from statistical inference and estimation to natural language processing, computational biology, as well as recently machine learning for chemistry.

    Tommi S. Jaakkola

    EECS and IDSS
    MIT Professor
    Machine Learning

  • Dr. Patrick Jaillet holds a joint appointment in the Operation Research and Statistics Group at MIT Sloan. Dr. Jaillet's research interests include online optimization and learning; machine learning; and decision making under uncertainty.

    Patrick Jaillet

    EECS
    MIT Professor
    Probability

  • Philippe Rigollet is an associate professor in the Department of Mathematics at MIT. He works at the intersection of statistics, machine learning, and optimization, focusing primarily on the design and analysis of statistical methods for high-dimensional problems.

    Philippe Rigollet

    Dept. of Mathematics
    Professor
    Fundamentals of Statistics

  • John Tsitsiklis is a Professor with the Department of Electrical Engineering and Computer Science, and a member of the National Academy of Engineering. His research focuses on the analysis and control of stochastic systems, including applications in various domains, from computer networks to finance.

    John Tsitsiklis

    EECS
    MIT Professor
    Probability

ADMINISTRATIVE TEAM

  • Devavrat Shah is a Professor with the Department of Electrical Engineering and Computer Science at Massachusetts Institute of Technology since 2005. He is a member of the Laboratory for Information and Decision Sciences (LIDS) and the Institute for Data, Systems, and Society (IDSS). He directs the Statistics and Data Science Center (SDSC). He is a visiting Adjunct Professor at the Tata Institute of Fundamental Research (TIFR) since March 2018.

    Devavrat Shah

    EECS and IDSS, MIT Faculty Director, MM SDS

  • Karene Chu is leading the effort in the production and running of the IDSS Micromasters Program in Statistics and Data Science. As a digital learning lab fellow at MIT, she made major and significant contribution to the MITx courses in mathematics, including the Calculus series and Differential equations series.

    Karene Chu

    Lecturer and Research Scientist, MM SDS

  • Susana Kevorkova is the Project Manager with MicroMaster Program in Statistics and Data Science at the MIT Institute for Data, Systems, and Society.

    Susana Kevorkova

    Project Manager, MM SDS

  • Jeremy Rossen is the Senior Program Assistant with MicroMasters Statistics and Data Science at and the Institute for Data, Systems, and Society (IDSS), MIT.

    Jeremy Rossen

    Senior Program Assistant, MM SDS

COURSE CONTRIBUTORS

  • Ravichandra is a third-year PhD student in CSAIL, MIT under the supervision of Prof Mohammad Alizadeh. His research is in the field of machine learning, and most recently in the intersection of reinforcement learning and neural networks.

    Ravichandra Addanki

  • Yuheng Bu is a Postdoctoral Associate at the MIT Institute of Data, Systems, and Society (IDSS).

    Yuheng Bu

  • Wangzhi Winston Dai is currently a Ph.D. student in Department of Electrical Engineering and Computer Science at MIT. He is primarily interested in developing computational tools involving signal processing and machine learning to help clinical decision making. Before coming to MIT, He earned his Bachelor’s from Peking University in 2017. Wangzhi will be the lead TA answering your questions on the forum and made major and significant contributions to 6.86x Machine Learning with Python: from Linear Models to Deep Learning.

    Wangzhi Winston Dai

  • Qing He received her PhD in the MIT Department of Electrical Engineering & Computer Science. Her research interests include inference, signal processing, and wireless communications -- all of which rely on the fundamental concepts taught in 6.041x/6.431x. Qing has taken several probability classes at MIT, and has been a teaching assistant for this course for two semesters. Jeremy Rossen is the Senior Program Assistant with MicroMasters Statistics and Data Science at and the Institute for Data, Systems and Society (IDSS), MIT.

    Qing He

  • Jan-Christian Huetter received his PhD in the Mathematics department at MIT. His research in Mathematical Statistics is about shape constrained estimation and causal discovery. He was a teaching assistant for High-Dimensional Statistics (18.657) in 2017. You will see him in many recitation videos in this course.

    Jan-Christian Huetter

  • Yan Jin is a PhD student in the Social and Engineering Systems program at the MIT Institute for Data, Systems, and Society.

    Yan Jin

  • Younhun is a current Ph.D. student at Massachusetts Institute of Technology, studying Applied Mathematics. His focus is on combinatorics and statistics, with an emphasis on mathematical frameworks used as a means of studying real-world problems, such as Cancer Biology and Population Genetics

    Younhun Kim

  • Eren Kizildag is a graduate student in the Electrical Engineering and Computer Science department at MIT, carrying out research in the Laboratory for Information and Decision Systems (LIDS) and the Research Laboratory of Electronics (RLE).

    Eren Can Kizildag

  • Dimitris is a second-year PhD student at MIT IDSS, primarily interested in financial mathematics and applications of machine learning to the financial world.

    Dimitris Konomis

  • Guang-he is a third-year Ph.D. student working with Professor Tommi S. Jaakkola in the Computer Science and Artificial Intelligence Laboratory (CSAIL) at Massachusetts Institute of Technology (MIT).

    Guanghe Lee

  • Jimmy Li received his PhD from MIT’s Department of Electrical Engineering and Computer Science. His research focused on applying the tools taught in this and related courses to problems in marketing.

    Jimmy Li

  • Lang Li is currently a Master's Student, Technology & Policy, at the Institute for Data, Systems, and Society (IDSS) at MIT.

    Liang Li

  • Tyler is an Instructor of Applied Mathematics at MIT. His current research interests span statistics, machine learning, computer vision, and nonconvex optimization.

    Tyler Maunu

  • Philip Martin received his PhD from the Department of Political Science at MIT and is now an assistant professor at George Mason University. His research focuses on the legacies of conflict and political violence. He has previously worked as a teaching assistant at MIT for 17.800 ("Quantitative Methods I: Regression") and 17.571 ("Engineering Democratic Development in Africa").

    Philip Martins

  • Nicholas graduated with a Master's in Engineering from CSAIL, MIT, in 2018. He is currently a software engineer in the New York City area and is a co-founder of Posh Development, a software application development, and consulting company.

    Nicholas Matthews

  • Tiffany is a master's candidate in computer science at MIT, where she also received her B.S. in electrical engineering and computer science. She is currently conducting research in machine learning in healthcare, ranging from clinical question answering, knowledge graph embedding, and reinforcement learning with wearable technologies.

    So Yeon Tiffany Min

  • Yaroslav is a postdoctoral associate at the Institute for Data, Systems, and Society (IDSS) at MIT. He obtained a PhD in Economics and Statistics from MIT Economics in 2019. His current research interests are in the intersection of semiparametric efficiency, information geometry, optimal transport and counterfactual analysis of econometric models.

    Yaroslav Muhkin

  • Uyiosa is a master’s student in the Technology and Policy Program in the MIT Institute for Data, Systems, and Society. His research involves the quantification of uncertainty in the life cycle emissions and associated greenhouse gas abatement costs of renewable aviation fuels. Uyiosa has taken probability and machine learning classes at MIT and has a great interest in using applied mathematics to help better our world.

    Uyiosa Mark Oriakhi

  • Victor Quach graduated from Ecole Polytechnique in France, where he received his B.Sc and his M.Sc in Mathematics and Computer Science. He is currently a second-year PhD student at CSAIL, MIT, under Prof. Regina Barzilay’s supervision.

    Victor Quach

  • Soumya is a junior at MIT, studying Computer Science and Engineering. She's passionate about machine learning and teaching.

    Soumya P. Ram

  • Jagdish Ramakrishnan received his PhD from MIT’s Department of Electrical Engineering and Computer Science. His general research interests include systems modeling, optimization, and resource allocation.

    Jagdish Ramakrishnan

  • Sudarsan is a postdoctoral associate at the Institute for Data, Systems, and Society (IDSS) at MIT. Sudarsan's main research interests are algorithmic and combinatorial problems in coding and information theory, data science, and machine learning. At IDSS, Sudarsan is focused on problems in these areas and is also actively involved in course development for the IDSS Micromasters program in Data Science and Statistics.

    Sudarsan V S Ranganathan

  • Master's Student, Technology & Policy, at the Institute for Data, Systems, and Society (IDSS) at MIT.

    Saeyoung Rho

  • Katie Szeto received her Bachelor and Master of Engineering degrees from MIT. Her Master’s thesis explored applications of probabilistic rank aggregation algorithms.

    Katie Szeto

  • Paxton Turner is a third-year graduate student in mathematics at MIT studying probability and statistics, advised by Philippe Rigollet. In particular, he is interested in discrete models as well as high-dimensional probability.

    Paxton Turner

  • Farrell Eldrian Wu is a second-year undergraduate at MIT majoring in Computer Science, Data Science, and Economics. He has a wide variety of academic interests, encompassing math, computer science, economics, and finance, tied together with a focus on modeling societal phenomena using mathematical techniques.

    Farrell Eldrian Wu

  • Kuang Xu received his PhD from MIT’s Department of Electrical Engineering and Computer Science. His research focused on the design and performance analysis of large-scale networks, such as data centers and the Internet, which involve a significant amount of uncertainties and randomness.

    Kuang Xu

Course TAs

  • Yuheng Bu is a Postdoctoral Associate at the MIT Institute of Data, Systems, and Society (IDSS). Yuheng will be making a significant contribution to the Machine Learning course.

    Yuheng Bu

    Machine Learning with Python: from Linear Models to Deep Learning

  • Sudarsan is a postdoctoral associate at the Institute for Data, Systems, and Society (IDSS) at MIT. Sudarsan's main research interests are algorithmic and combinatorial problems in coding and information theory, data science, and machine learning. At IDSS, Sudarsan is focused on problems in these areas and is also actively involved in course development for the IDSS Micromasters program in Data Science and Statistics. He will a major contributor to the Probability course.

    Sudarsan V S Ranganathan

    Probability - The Science of Uncertainty and Data