Course Schedule
Following a short introduction, the lectures are organized into 9 units that include lectures by course instructors and guest speakers. Some units also include a panel or debate. Tutorials on useful background topics appear at the end of the table. Although the sessions are listed in the table in a particular order, the units and their component lectures are somewhat independent, providing the flexibility to explore topics in a different order.
Session Key
L = Lecture by course instructor
S = Seminar by guest speaker
T = Tutorial by course instructor or TA
P = Panel discussion
D = Debate
See the Instructors page for a list of each instructor’s institutional and department affiliation.
| SES # | INSTRUCTORS | TOPICS |
|---|---|---|
| Introduction | ||
| L0 | Tomaso Poggio | Introduction to the study of intelligence in brains, minds and machines |
| Unit 1. Neural Circuits of Intelligence | ||
| L1.1 | Nancy Kanwisher | Introduction to human cognitive neuroscience |
| L1.2 | Gabriel Kreiman | Computational roles of feedback and recurrent connections in visual cortex |
| L1.3 | James DiCarlo | Neural mechanisms underlying visual object recognition: The convergence of computer vision and biological vision (Part 1) |
| L1.4 | James DiCarlo | Neural mechanisms underlying visual object recognition: The convergence of computer vision and biological vision (Part 2) |
| L1.5 | Winrich Freiwald | Of primates, faces, and intelligence |
| L1.6 | Matt Wilson | Hippocampus, memory, and sleep (Part 1) |
| L1.7 | Matt Wilson | Hippocampus, memory, and sleep (Part 2) |
| S1 | Larry Abbott | A mind in the fly brain |
| Unit 2. Modeling Human Cognition | ||
| L2.1 | Josh Tenenbaum | Computational cognitive science: Generative models, probabilistic programs, and common sense (Part 1) |
| L2.2 | Josh Tenenbaum | Computational cognitive science: Generative models, probabilistic programs, and common sense (Part 2) |
| L2.3 | Josh Tenenbaum | Computational cognitive science: Generative models, probabilistic programs, and common sense (Part 3) |
| Unit 3. Development of Intelligence | ||
| L3.1 | Liz Spelke | Cognition in infancy (Part 1) |
| L3.2 | Liz Spelke | Cognition in infancy (Part 2) |
| L3.3 | Alia Martin | Developing an understanding of communication |
| L3.4 | Laura Schulz | Children’s sensitivity to the cost and value of information |
| S3 | Jessica Sommerville | Infants’ sensitivity to cost and benefit |
| L3.5 | Josh Tenenbaum | The child as scientist |
| D3 | Tomer Ullman & Laura Schulz | Debate: Theories, imagination, and the generation of ideas |
| Unit 4. Visual Intelligence | ||
| L4.1 | Shimon Ullman | From simple innate biases to complex visual concepts |
| L4.2 | Shimon Ullman | Atoms of recognition in human and computer vision |
| L4.3 | Aude Oliva | Predicting visual memory: Behavioral, neuroscience, and computational accounts |
| S4.1 | Eero Simoncelli | Probing sensory representations with metameric stimuli |
| S4.2 | Amnon Shashua | Computer vision, wearable computing, and the future of transportation |
| Unit 5. Vision and Language | ||
| L5.1 | Boris Katz | Vision and language |
| L5.2 | Andrei Barbu | From language to vision and back again |
| L5.3 | Patrick Winston | The story understanding story: The truth about human intelligence |
| S5 | Tom Mitchell | Neural representations of language meaning |
| Unit 6. Social Intelligence | ||
| L6.1 | Nancy Kanwisher | Social intelligence |
| L6.2 | Ken Nakayama | The social mind |
| L6.3 | Rebecca Saxe | MVPA: Opening a new window on the mind via fMRI (Part 1) |
| L6.4 | Rebecca Saxe | MVPA: Opening a new window on the mind via fMRI (Part 2) |
| Unit 7. Audition and Speech | ||
| L7.1 | Josh McDermott | Introduction to biological audition (Part 1) |
| L7.2 | Josh McDermott | Introduction to biological audition (Part 2) |
| L7.3 | Nancy Kanwisher | Functional specialization in human auditory cortex |
| L7.4 | Hynek Hermansky | Auditory perception in speech technology (dealing with unwanted information) (Part 1) |
| L7.5 | Hynek Hermansky | Auditory perception in speech technology (dealing with unwanted information) (Part 2) |
| P7 | Panel discussion | Similarities and differences between hearing and vision, with Alex Kell (moderator), Josh Tenenbaum, Hynek Hermansky, Josh McDermott, Gabriel Kreiman, Dan Yamins |
| Unit 8. Robotics | ||
| L8.1 | Russ Tedrake | MIT’s entry in the DARPA robotics challenge |
| L8.2 | John Leonard | Mapping, localization, and self-driving vehicles |
| L8.3 | Tony Prescott | Layered control architecture in mammals and robots |
| L8.4 | Stefanie Tellex | Human-robot collaboration |
| L8.5 | Giorgio Metta | iCub: An open source platform for research in robotics & AI |
| L8.6 | iCub Team |
Research on the iCub platform
|
| P8 | Panel discussion | Future research directions in robotics and motor control in biological systems, with Patrick Winston (moderator), John Leonard, Giorgio Metta, Stefanie Tellex, Tony Prescott, Russ Tedrake |
| Unit 9. Theory of Intelligence | ||
| L9.1 | Tomaso Poggio | iTheory: Visual cortex and deep networks |
| S9 | Surya Ganguli | The statistical physics of deep learning |
| L9.2 | Haim Sompolinsky | Sensory representations in cortex-like deep architectures |
| Background Tutorials | ||
| T1 | Leyla Isik | Basic neuroscience |
| T2 | Daniel Zysman | MATLAB® programming (* with additional content development by Ellen Hildreth) |
| T3 | Lorenzo Rosasco | Machine learning |
| T4 | Ethan Meyers | Neural decoding |
| T5 | Tomer Ullman | Church programming |
| T6 | Tomer Ullman | Amazon Mechanical Turk |
