Calendar

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

  • Carlo Ciliberto: iCub: An overview
  • Alessandro Roncone: Multi-sensory integration for the iCub robot
  • Raffaello Camoriano: Large-scale incremental learning for robotics
  • Giulia Pasquale: Teaching iCub to recognize objects
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

Course Info

Learning Resource Types

theaters Other Video
theaters Lecture Videos
notes Lecture Notes
group_work Projects
co_present Instructor Insights