Slava Gerovitch
Date TBD | Time TBD | Location TBD |
Enrollment: Limited: Advance sign-up required
Sign-up by 11/04
Prereq: at least two math courses at 18.100 level or higher.
For undergraduates wanting to learn mathematical topics through guided self-study. Application deadline for Jan 2017 IAP is: FRIDAY, NOVEMBER 4, 2016.
After you get admitted, we'll pair you up with a graduate student mentor with similar interests. You two will agree on a topic to explore, and find a suitable textbook. The math department pays for copies of the book (a good deal, since advanced math textbooks can be pretty expensive).
During IAP, you and your mentor will meet on campus at least 3 times per week to discuss the material. This is *directed reading* - don't expect to be taught! Instead, you have the opportunity to ask in-depth questions, discuss your impressions, and receive feedback. There's no credit for taking it, and you won't get paid.
Instructions for applying, and more information, can be found here:
http://math.mit.edu/research/undergraduate/drp
Sponsor(s): Mathematics
Contact: Slava Gerovitch, 2-231C, 4-1459, slava@mit.edu
Samuel Elder
Enrollment: Unlimited: No advance sign-up
Attendance: Contestants must qualify. See Tues, Jan. 24
Prereq: need to pass the qualifying test on 1/24 to enter the bee
See individual session descriptions below.
Sponsor(s): Mathematics
Contact: Samuel Elder, 2-340A, same@math.mit.edu
Jan/24 | Tue | 04:00PM-06:00PM | 4-153 |
Stop by at any point during the session, for a quick test of your single variable integration skills. Top scorers qualify for the Integration Bee. No knowledge beyond 18.01 necessary.
http://www.mit.edu/~same/integrationbee.html
Jan/26 | Thu | 06:30PM-10:00PM | 26-100 |
No enrollment limit. No advance sign up (but contestants must qualify, see Tuesday, Jan. 24). Come watch your fellow students match wits and single variable integration skills for prizes and the title of "Grand Integrator".
http://www.mit.edu/~same/integrationbee.html
Sylvain Carpentier
Enrollment: to perform, send email to (syl_car@mit.edu)
Attendance: Participants must attend all sessions
This annual concert gives those in the mathematics community, together with family and friends, a chance to perform for each other. Come to play or listen.
Sponsor(s): Mathematics
Contact: Sylvain Carpentier, 2-341A, syl_car@mit.edu
Jan/30 | Mon | 02:00PM-04:00PM | Killian Hall |
Feb/03 | Fri | 02:00PM-04:00PM | Killian Hall |
Jeremy Kepner, Fellow & Head MIT Supercomputing Center
Enrollment: Limited: Advance sign-up required
Sign-up by 01/06
Limited to 30 participants
Attendance: Participants must attend all sessions
Prereq: Linear Algebra
"Big Data" describes a new era in the digital age where the volume, velocity, and variety of data created across a wide range of fields (e.g., internet search, healthcare, finance, social media, defense, ...) is increasing at a rate well beyond our ability to analyze the data. Many technologies (e.g., spreadsheets, databases, graphs, linear algebra, ...) have been developed to address these challenges. The common theme amongst these technologies is the need to store and operate on data as whole collections instead of as individual data elements. This class describes the common mathematical foundation of these data collections (associative arrays) that apply across a wide range of applications and technologies. Associative arrays unify and simplify Big Data leading to rapid solutions to Big Data volume, velocity, and variety problems. Understanding these mathematical foundations allows the student to see past the differences that lie on the surface of Big Data applications and technologies and leverage their core mathematical similarities to solve the hardest Big Data challenges.
Sponsor(s): Mathematics
Contact: Jeremy Kepner, 2nd Floor, 300 Tech Sq, 781 981-3108, KEPNER@LL.MIT.EDU
Jan/10 | Tue | 11:00AM-01:00PM | 2nd Flr 300 Tech Sq, Bring lunch if you like |
Preface and Chapter 1 of "Mathematics of Big Data" text
Jan/17 | Tue | 11:00AM-01:00PM | 2nd Flr 300 Tech Sq, Bring lunch if you like |
Chapter 2 and Chapter 3 of "Mathematics of Big Data" text. Introduction to D4M (http://d4m.mit.edu).
Jan/24 | Tue | 11:00AM-01:00PM | 2nd Flr 300 Tech Sq, Bring lunch if you like |
Chapters 4, 5, 6, 7 of "Mathematics of Big Data" text.
Jan/31 | Tue | 11:00AM-01:00PM | 2nd Flr 300 Tech Sq, Bring lunch if you like |
Student presentations
Chapters 8, 9 of "Mathematics of Big Data"
Homer Reid
Enrollment: Unlimited: No advance sign-up
Attendance: Participants welcome at individual sessions
Do you---as an engineer---sometimes consult pure-math papers or textbooks in the hope of deriving insight into a puzzling mathematical challenge, only to be stymied by an impenetrable wall of jargon such as short exact sequences and functoriality?
Do you---as a physicist---need to know what things like cohomology and p-forms are, but can't learn from pure-math textbooks because of the dense thicket of abstract terminology and concepts lying between the title page and the interesting content?
Or do you---as an applied or numerical mathematician---simply wonder what your pure-math colleagues are doing down the corridor all day?
If so, this is the course for you!
http://homerreid.com/teaching/MoPuMMAM
Sponsor(s): Mathematics
Contact: Homer Reid, (857) 829-1667, homereid@mit.edu
Jan/23 | Mon | 02:30PM-04:00PM | E25-117 |
Jan/25 | Wed | 02:30PM-04:00PM | E25-117 |
Jan/27 | Fri | 02:30PM-04:00PM | E25-117 |
Jan/30 | Mon | 02:30PM-04:00PM | E25-117 |
Feb/01 | Wed | 02:30PM-04:00PM | E25-117 |
Feb/03 | Fri | 02:30PM-04:00PM | 32-144 |
Enrollment: Unlimited: No advance sign-up
Attendance: Participants welcome at individual sessions
Positional games is a branch of Combinatorics, studying deterministic two player zero sum games with perfect information, played usually on discrete or even finite boards. Among other, positional games include the popular games Tic-Tac-Toe and Hex as opposed to abstract games played on graphs and hypergraphs. This subject is strongly related to other branches of Combinatorics such as Ramsey Theory, Extremal Graph Theory and the Probabilistic Method. In this mini course we introduce the subject and its basic notions; learn some classical results in the field; discuss few general known tools as long as possible extensions; sketch some recent research results and talk about some interesting open problems in the field.
Sponsor(s): Mathematics
Contact: Asaf Ferber, 2-246A, ferbera@mit.edu
Jan/17 | Tue | 10:00AM-12:00PM | 4-153 |
A brief introduction to the subject. The game of HEX, Tic-Tac-Toe, Shannon's switching game, strategy stealing, Ramsey-Type games and more.
Jan/19 | Thu | 10:00AM-12:00PM | 4-153 |
Weak games, the conditional expectation method (the Erdos-Selfridge Theorem), biased games and strong games.
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