BEGIN:VCALENDAR
VERSION:2.0
PRODID:ILLC Website
X-WR-TIMEZONE:Europe/Amsterdam
BEGIN:VTIMEZONE
TZID:Europe/Amsterdam
X-LIC-LOCATION:Europe/Amsterdam
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:19700329T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=-1SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:19701025T030000
RRULE:FREQ=YEARLY;BYMONTH=10;BYDAY=-1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
UID:/NewsandEvents/Archives/2022/newsitem/13298/21
 ---27-May-2022-2022-Program-for-Women-and-Mathemat
 ics-The-Mathematics-of-Machine-Learning-
DTSTAMP:20220113T150450
SUMMARY:2022 Program for Women and Mathematics "Th
 e Mathematics of Machine Learning"
DTSTART;VALUE=DATE:20220521
DTEND;VALUE=DATE:20220527
LOCATION:New Jersey, U.S.A.
DESCRIPTION:Co-sponsored by the National Science F
 oundation, Lisa Simonyi, the Institute for Advance
 d Study (IAS), and Princeton University Department
  of Mathematics, Women and Mathematics (WAM) is an
  annual program that aims to recruit and retain mo
 re women in mathematics. WAM aims to counter the i
 nitial imbalance in the numbers of men and women e
 ntering mathematics training as well as the higher
  attrition rate of female mathematicians compared 
 to their male counterparts at every critical trans
 ition stage in mathematical careers. WAM encourage
 s female mathematicians to form collaborative rese
 arch relationships and to become active in a verti
 cal mentoring network spanning a continuum from un
 dergraduates to emerita professors, which provides
  support and reduces the sense of isolation experi
 enced by many women in mathematics. While there ar
 e a number of women's programs targeted solely at 
 undergraduates, or graduate students, or postdocs,
  very few programs provide the depth and breadth t
 hat come from simultaneously including features ta
 ilored for undergraduate students, graduate studen
 ts, and researchers from a broad spectrum of US in
 stitutions, all in one united community of scholar
 s, as WAM does.  Terng Lecture Series: Cynthia Rud
 in (Duke University), Introduction to Interpretabl
 e Machine Learning.  Uhlenbeck Lecture Series: Mar
 ia Florina Balcan (Carnegie Mellon University), Fo
 undations for Learning in the Age of Big Data
X-ALT-DESC;FMTTYPE=text/html:\n  <p>Co-sponsored b
 y the National Science Foundation, Lisa Simonyi, t
 he Institute for Advanced Study (IAS), and Princet
 on University Department of Mathematics, Women and
  Mathematics (WAM) is an annual program that aims 
 to recruit and retain more women in mathematics. W
 AM aims to counter the initial imbalance in the nu
 mbers of men and women entering mathematics traini
 ng as well as the higher attrition rate of female 
 mathematicians compared to their male counterparts
  at every critical transition stage in mathematica
 l careers. WAM encourages female mathematicians to
  form collaborative research relationships and to 
 become active in a vertical mentoring network span
 ning a continuum from undergraduates to emerita pr
 ofessors, which provides support and reduces the s
 ense of isolation experienced by many women in mat
 hematics. While there are a number of women's prog
 rams targeted solely at undergraduates, or graduat
 e students, or postdocs, very few programs provide
  the depth and breadth that come from simultaneous
 ly including features tailored for undergraduate s
 tudents, graduate students, and researchers from a
  broad spectrum of US institutions, all in one uni
 ted community of scholars, as WAM does.</p>\n\n  <
 p>Terng Lecture Series: Cynthia Rudin (Duke Univer
 sity), Introduction to Interpretable Machine Learn
 ing.<br>\n  Uhlenbeck Lecture Series: Maria Florin
 a Balcan (Carnegie Mellon University), Foundations
  for Learning in the Age of Big Data</p>\n
URL:https://www.ias.edu/math/wam/program-years/202
 2-program-women-and-mathematics
END:VEVENT
END:VCALENDAR