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DTSTART;TZID=America/New_York:20230419T080000
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DTSTAMP:20230315T185926Z
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UID:9777-1681891200-1681923600@ma.stat.columbia.edu
SUMMARY:DATA SCIENCE DAY
DESCRIPTION:Data Science Day provides a forum for innovators in academia\, industry\, and government to connect. The in-person conference will host keynote presentations from leading voices in data-driven innovation\, lightning talks from Columbia University researchers\, and interactive poster and technology demonstrations. \nKeynote Speaker:  Manuala Veloso. JPMorgan Chase & Co.  \n\nWednesday\, April 19\, 2023\nMore details HERE. \nREGISTER
URL:https://ma.stat.columbia.edu/event/data-science-day-april-19/
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230418T113000
DTEND;TZID=America/New_York:20230418T123000
DTSTAMP:20230405T193233Z
CREATED:20230405T192538Z
LAST-MODIFIED:20230405T193233Z
UID:9993-1681817400-1681821000@ma.stat.columbia.edu
SUMMARY:ALUMNI PANEL on the HEALTH/PHARMA/BIOTECH INDUSTRIES
DESCRIPTION:Have you thought about a career path in the healthcare related industry? \n\nAre you wondering if you need a biology or life science background to enter the field?\nWhat are the most needed technical/soft skills in this industry that provides more job security?  \n\nCome join this virtual panel to learn from three of our great alumni who had years of experience in the field.  \nCheck the MA Weekly Newsletter for the Zoom Link and RSVP. 
URL:https://ma.stat.columbia.edu/event/alumni-panel-on-the-healthcare-industry/
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DTSTART;VALUE=DATE:20230417
DTEND;VALUE=DATE:20230419
DTSTAMP:20230405T191342Z
CREATED:20230405T185545Z
LAST-MODIFIED:20230405T191342Z
UID:9981-1681689600-1681862399@ma.stat.columbia.edu
SUMMARY:FALL 2023 - ADVANCE REGISTRATION
DESCRIPTION:REGISTRATION FOR FALL CLASSES will be available during appointment times from Monday – Friday. \nAs a reminder\, all MA students are required to register every semester. An official leave of absence is the only exception to this Continuous Registration policy. \nAdvance registration for Fall 2023 is open Monday\, April 17 through Friday\, April 21 and then will reopen from Monday\, June 12 through Friday\, June 16\, and Tuesday\, June 20 through Friday\, June 23. For registration dates in August\, please visit the Registrar’s Office website. Please refer to Student Services Online (SSOL) for specific registration appointment times. All students are required to register themselves through SSOL. \nPlease note the following: \n\nYou must register for a Residence Unit or other enrollment category along with your courses. IF YOU HAVE COMPLETED TWO RU’s in the MA Program\, YOU MUST REGISTER FOR ER.  The enrollment category affects your tuition rate\, access to Columbia buildings and facilities\, health insurance\, and more. Additional information about enrollment categories may be found here.\nIn addition\, students holding a visa must register either for a full Residence Unit or for Extended Residence to maintain their visa status. If you have additional questions regarding your visa status\, you may contact ISSO. \nStudents who signed up for the Columbia Student Medical Insurance must register for a Residence Unit or other enrollment category for the fall term by August 14 in order for your health insurance to continue. If you do not register by August 14\, your health insurance will lapse.\n\nPlease write with any other questions at gsas-studentaffairs@columbia.edu.   \nHOW TO REGISTER FOR CLASSES\nIt is the student’s responsibility to stay on track with graduation requirements\, and to make sure the Faculty Adviser approves course selections prior to registering for each semester.  Schedules should be reviewed again if changes are made. \nThe GSAS Academic Calendar indicates the general dates that students can register.  The system will allow students to register only during specific registration appointment times on Student Services Online (SSOL) (accessed with UNI and password).  “REG APPTS” reveals the designated times. \nThe Columbia Course Directory and Vergil offer key information about each class including the course size\, prerequisites\, and if there are any restrictions. For example\, if a course is not open to students in GSAS\, it would not be open to an MA Statistics student. For further details about registration procedures\, students may refer to the GSAS Registration page. \nBefore registering\, the onus is on the student to reach out to their assigned Faculty Adviser to have the individual course list approved (in person or via email). \nHERE is a video that describes how to use SSOL for registration.  HERE is a video about using Vergil for planning your courses and schedule. \nRESIDENCE UNITS\nBelow are Residence Unit Categories for each of the MA Programs. For more information about Residence Units\, see also Tuition & Fees  and the GSAS Website.  Registration in the Graduate School of Arts and Sciences is a two-part process that consists of registering for both individual classes and also for a full or fractional Residence Unit.  A Residence Unit (RU) is a registration category that determines the amount of tuition. \nStudents in F-1 status must complete the program in three semesters maximum (full-time).  The number of classes each semester may vary as long as all requirements are completed within three semesters (maximum).  It is possible to graduate after two semesters\, but this is not recommended as the courses are challenging and all students must maintain a 3.0 GPA.  Always check with ISSO about international and visa-related issues.  \nFull-Time Student (Registration for one full RU or ER is considered full-time.) \n\nFirst Semester – RU\nSecond Semester – RU\nStudents may opt to take summer courses / Statistical Fieldwork\nThird Semester – ER\n\nPart-Time Student \nPart-time allows for QR (Quarter Residence Unit) or HR (Half Residence Unit).  ALL MA Program students are required to complete two RUs to graduate.  \nAll Students \nAfter completing a total of two RUs\, all students who wish to continue their studies in the MA Program for a subsequent semester must register for ER.  One can register for ER for more than one semester (e.g.\, Summer Term and Fall Term).  ALL MA Program students are required to complete two RUs to graduate.  \n\n\n\nStatistics  Categories\n \n\n\nFull Residence Unit (RU)*\n\n20 credits max (RESI) \n\n\n\nExtended Residence (ER)*\n\n20 credits max (EXRS) – Taken after completion of two Residence Units \n\n\n\nSummer ER*\n20 credits max (EXRS) – Taken during the summer semester\n\n\nHalf Residence Unit (HR)*\nThree courses max\n\n\nQuarter Residence Unit (QR)*\n\nTwo courses max \n\n\n\n\n*To find the call number for the kind of residence unit you want\, look in the Columbia Course Directory under Richard Slusarczyk – (Assc. Dean-Academic Affairs\, GSAS) who will be listed as the “instructor” for GSAS residence units.  Choose the correct unit and semester.  \nREGISTRATION GUIDELINES\nFor registration guidelines please review: \n\nRegistration Outline\nCourse Checklist Form\n\nHow many courses? \n\nThe number of classes taken must be approved by the Faculty Adviser.\nTo remain in Good Academic Standing (GPA at 3.0 and above)\, it is recommended to take no more than four classes per semester\, especially in the first semester.\nStudents on F-1 visa must register for a full RU in their first two semesters.  Most students need a third semester to complete all requirements \, but anyone who completes all their program requirements (courses and 2 RUs) may graduate.  After completing 2 RUs in GSAS\, one must register for ER to continue for a subsequent semester. \nA full RU or ER allows any number of points up to and including twenty points.\nPart-time students may register for a QR or HR\, as long as the program is completed within four years and a total of two RUs have been fulfilled.\nMost full-time students should plan for three full semesters. Completing the MA Program in two semesters requires faculty adviser approval. \n\nWhich classes to take? \n\nHere are details about the Statistics MA Program requirements.\nHere are approved electives.\nHere is information about Cross Registration.\nHere are electives grouped according to interest area\, such as finance\, data science\, public health\, insurance\, or the Ph.D. track.\nHere is a list of courses that will not count for the MA Degree in Statistics.\n\nWhat if a class is “restricted?” \n\nThis means that it is closed to MA Statistics Students.\n\nLook up the course in the Columbia Directory and review the section “Open To.”\nSome courses open to additional students on a later date.  This is often found in the “Notes” section of the course.\n\n\nHere is information about cross registration into other schools.\n\nWhat if a class is full? \n\nSSOL is the primary source for all registration including the waitlists.\nThe student should register as soon as possible to get on the electronic waitlist.\nWaiting is the next step.  Eventually\, the student’s request to join the class will either be accepted or denied.\nStudents should not email the instructor to bypass others on the waitlist.\nThere is no need to reach out to a Faculty Adviser except in a case where a class is required for graduation in the last semester of the program.\nThis is a helpful Guide for waitlists.  \nQuestions may be sent to waitlists@columbia.edu.\nIt is important to have a back-up plan\, such as an alternative course or a different section that is still open.\nIt is not permissible to remain on the waitlist if you are accepted into another section of the same course.\nIf accepted into a desired section\, please drop all other sections to open those waitlists to others.\n\nResidence Unit (RU) Status \n\nAlways review RU status.\nQuestions about tuition may be sent to gsas-finaid@columbia.edu.\nIf the total number of points goes over twenty\, there will be extra charges.\nIf a student needs to change to a lower RU\, this must be done manually by the student.  It does not happen automatically when one registers for fewer credits.\nStatistics students in the MA Program may not register for greater than fifteen points at one time.  Special permission must be obtained to register for more than fifteen.\n\nCourses must have a letter grade to count for graduation. \n\nAny course with P/F or R Grade does not count toward graduation.\nThe three CORE courses and the CAPSTONE COURSE MAY NOT be taken Pass/Fail. \n\nHow to add or drop a class after registration: \n\nThe first two weeks of the semester is called the “Change of Program Period” because students may add and drop classes in SSOL without penalty.\nYour schedule should be set at the end of the “Change of Program Period.”\n\n\nRefer to the Academic Calendar for add/drop and other deadlines.\n\nNo classes may be dropped after the LAST DAY TO DROP.  There are no exceptions.\nNo classes may be changed to R or Pass/Fail after the DEADLINE to change to PASS/FAIL or R.\n\n\nThe deadlines for half- semester courses are different\, to remain in proportion to the deadlines for full-semester courses:\n\nHalf-semester courses must be dropped within the first two weeks.\nThe deadline for Pass/Fail or for R credit is the first day of the fifth week. (Remember that core classes may not be taken for Pass/Fail or R credit.  Nor may they be taken over to receive a higher grade.)\n\n\n\n\nHERE is information about the post-Change of Program Period.\nStudents who stop attending a course without officially dropping will be assigned a grade unless they communicate with the instructor and make proper arrangements.  Students in academic challenges should reach out to their instructor and TA first\, then to the faculty adviser\, and the MA Team. \n\nThe Registration Adjustment Form (RAF) \nThe Registration Adjustment Form may NOT be used to enter a class that is noted as RESTRICTED in your SSOL schedule. The Registration Adjustment Form (RAF) may be used only under these special circumstances: \n\nDuring cross registration when the other school has no special procedure. The form should be brought to GSAS Main Office located at 107 Low Library with the signature and UNI of one’s Faculty Adviser\, the instructor\, and possibly an appropriate administrator of the other school.  An email print-out approval attached to the RAF will count for a signature.\nWhen needing to sign-up for greater than the allowed fifteen credits for MA Statistics Students. \nTo drop the last or only class. A special request must be made to the Office of Student Affairs at 107 Low Library. An application for a Leave of Absence or Withdrawal is required based upon the particular situation.\n\nUnder all circumstances\, the RAF gets handed in to 107 Low Library (GSAS) or emailed to gsas-studentaffairs@columbia.edu.  \nIMPORTANT LINKS FOR REGISTRATION\n\nUniversity Registrar– University Registrars Office\nRegistration–GSAS instructions for registration\nDirectory of Classes or Vergil – either can be used to find out more information about a class including cap and if there are any restrictions.\nGSAS Academic Calendar\nRegistration Adjustment Form– This is for special cases to add/drop that are not accessible via SSOL.\nRequest for Transcripts\nStudent Financial Services: Billing and Payments\nFAQs-Registration\n\nCROSS REGISTRATION\nThe Statistics Department does not have any influence on allowing you into a cross registered class. Cross Registration is always at the discretion of the specific School/Department/Instructor.  \nAdmittance into any course is not guaranteed.  All courses are subject to availability.  \nMost schools/departments do not allow students to cross-register until the first week of classes.  \nSchools and departments all have their own cross registration processes. Please review the links and information below. For schools/departments not listed\, review each individual website and\, if needed\, reach out to their student affairs office to inquire about their cross registration options and processes.  \n\nComputer Science\nIndustrial Engineering and Operations Research \nColumbia Business School\n\nMost courses have a prerequisite of Capital Markets “FINC B8306/ MATH G4076” or “waiver exam”.\nEmail crossreg@gsb.columbia.edu.  \n\n\nData Science Institute\n\nNon-Data Science students will be able to join a waitlist via SSOL.  \nSpace permitting\, Non-DS students will be moved from the waitlist to the class roster during the first week of classes. \nStudents are encouraged to attend the first day of class to get the syllabus and to get a pulse for the course.\nEmail:  DataScience-Registration@columbia.edu.\nFall courses open via waitlist are:\n\nCSOR W4246 – Algorithms for Data Science\nCOMS W4995 – Topics in Computer Science: Elements of Data Science\nCOMS W4995 – Topics in Computer Science: Applied Deep Learning\nCOMS W4995 – Topics in Computer Science: Applied Machine Learning\n\n\n\n\nMath Finance  \n\nAll Math Finance courses have managed waitlists.  This means that everyone who registers is automatically added to a waitlist which is managed by the instructor. \nThe first priority goes to Math Finance students.  After those students are given places\, then spaces will be available for Statistics Students.  \nSome Math Finance courses will not be available for cross registration until the first week of classes.\n\n\nBiostatistics\n\nThe approved electives in this department are 8100 level courses which all have P6103/4 as their prerequisite. \nBiostat 6000 level courses are not approved for graduate credit in the MA Program in Statistics.  \n\n\n\nMA students may register for courses at Teachers College\, as long as they get permission from TC and their adviser. \nTRANSFER CREDIT\nCourses taken in Statistics at Columbia University prior to entering the M.A. program may count toward the M.A. degree if approved by the Program Director and upon final review by the Graduate School. According to the policy of the Statistics Department\, no more than 4 classes (and a maximum of 1 RU)\, taken at Columbia prior to admission in the M.A. program may be applied towards the M.A. degree.  No Columbia course may be applied to more than one degree. \nWhen transfer credit is granted\, concomitant Residence Units may also be credited toward fulfilling the two RU requirement for the M.A. Degree.  Here is more information about transfer credit. \nA student may receive Transfer Credit by following this procedure: \n\nThere is a Transfer Credit form on the GSAS Website.  The top of this form must be filled out with student signature on the appropriate line.\nThe courses should be listed in the blank area provided.\n“Previous Institution” should be Columbia University\, i.e.\, where the courses were taken.\nThe form may be given or emailed to Jill Forger who will pass it to the Faculty Director for approval.\nThe Faculty Director will determine the number of points and RUs to be credited.\nOnce the form has been approved and signed by the Director\, it can be submitted to GSAS in 107 Low.\n\nCOURSES TAKEN FOR R GRADE OR PASS/FAIL\nAfter the deadline to drop a class\, all classes will remain on the transcript and receive a grade.  \nCOURSES TAKEN FOR R OR PASS/FAIL DO NOT COUNT TOWARD THE MA STATISTICS DEGREE.    \n\nThe decision to choose Pass/Fail or R is PERMANENT after the deadline.  \nCourses taken for Pass/Fail or R do not count toward the 30 credits required for graduation.  \nA PASS will not affect the GPA\, but a FAIL grade will be the same as an F in any course.  \n\nNot all classes are Pass/Fail eligible: \n\nCore Courses & Capstone Courses are NOT Pass/Fail eligible.  \nElective Courses:  The instructor will determine if the course is Pass/Fail eligible. Check for Pass/Fail eligibility in SSOL.  If not\, ask the instructor.  \n\nFor R Credit\, a student must make an arrangement with the instructor before the deadline.   \nGSAS DEADLINES for dropping classes and choosing Pass/Fail or R are strictly enforced.  \n\nHERE are further details on the GSAS grading system.  \n\nFrom the GSAS Website:   \nR credit and Pass/Fail (P/F) are two different marks. Unlike R credit\, the mark of P/F assesses the quality of a student’s performance. Additionally\, students taking a course Pass/Fail are evaluated on all the gradable assignments for the course.  \nStudents who elect to take a course for R credit are not required to take the final examination; however\, they must meet all other course requirements\, unless the instructor states otherwise in writing.
URL:https://ma.stat.columbia.edu/event/fall-2023-advance-registration/
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230414T180000
DTEND;TZID=America/New_York:20230414T200000
DTSTAMP:20230214T215210Z
CREATED:20230214T215013Z
LAST-MODIFIED:20230214T215210Z
UID:9656-1681495200-1681502400@ma.stat.columbia.edu
SUMMARY:MA Statistics Alumni Social Event
DESCRIPTION:Join our Alumni of the Year 2022 Awards Ceremony followed by networking and socializing.  \nOpen to alumni of the MA Statistics program. An RSVP is required. If you have any questions about this event please email Violet Yin. \nWe look forward to getting everyone back together and seeing you at the event.
URL:https://ma.stat.columbia.edu/event/ma-statistics-alumni-social-event/
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230412T133000
DTEND;TZID=America/New_York:20230412T143000
DTSTAMP:20230405T195025Z
CREATED:20230327T203519Z
LAST-MODIFIED:20230405T195025Z
UID:9966-1681306200-1681309800@ma.stat.columbia.edu
SUMMARY:Lunch with Dr. Gabriel Young – Informal Faculty Talks with MA Students
DESCRIPTION:Please read the MA Statistics Newsletter for details and RSVP.  \nFor more information about Dr. Gabriel Young\, see the Department of Statistics Directory. 
URL:https://ma.stat.columbia.edu/event/lunch-with-dr-gabriel-young/
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230407T080000
DTEND;TZID=America/New_York:20230408T170000
DTSTAMP:20230405T203002Z
CREATED:20230313T182302Z
LAST-MODIFIED:20230405T203002Z
UID:9792-1680854400-1680973200@ma.stat.columbia.edu
SUMMARY:The Statistical Machine Learning Symposium
DESCRIPTION:The Statistical Machine Learning Symposium\, organized by the Department of Statistics  with support from the Data Science Institute (DSI) \, is a two-day workshop that will be held April 7-8\, 2023 at Columbia University\, School of Social Work\, 1255 Amsterdam Ave\, Room 311-312. It will consist of lectures from invited speakers in academia and industry\, as well as lightning talks and poster presentations from junior researchers (graduate students and postdocs from the New York area institutions). \nSee here for the schedule. \nWe invite abstract submissions  by March 21\, 2023. Decisions will be made around March 25\, 2023. \nOrganizing committee: \nDaniel Hsu \, Samory Kpotufe \, Arian Maleki \, Cindy Rush \, Eren Kizildag \, Belinda Tzen . \nList of Invited Speakers: \nMisha Belkin (UCSD)\nJoan Bruna Estrach (NYU)\nMatt Hoffman (Google)\nStefanie Jegelka (MIT)\nAdam Klivans (UT Austin)\nZongming Ma (UPenn)\nMarina Meila (UW)\nVahab Mirrokni (Google)\nNati Srebro (TTIC)\nPragya Sur (Harvard)\nMengdi Wang (Princeton)\nDana Yang (Cornell)
URL:https://ma.stat.columbia.edu/event/the-statistical-machine-learning-symposium/
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230406T133000
DTEND;TZID=America/New_York:20230406T143000
DTSTAMP:20230405T194353Z
CREATED:20230327T203150Z
LAST-MODIFIED:20230405T194353Z
UID:9962-1680787800-1680791400@ma.stat.columbia.edu
SUMMARY:Lunch with Professor Philip Protter – Informal Faculty Talks with MA Students
DESCRIPTION:Topic:  “Modeling the Random Times Things Happen and How to Predict Them” \nHERE‘s more information about Philip Protter.  \nPlease read the MA Statistics Newsletter for details and RSVP. 
URL:https://ma.stat.columbia.edu/event/lunch-with-professor-philip-protter/
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230330T113000
DTEND;TZID=America/New_York:20230330T123000
DTSTAMP:20230313T165726Z
CREATED:20230313T165559Z
LAST-MODIFIED:20230313T165726Z
UID:9769-1680175800-1680179400@ma.stat.columbia.edu
SUMMARY:Professional Workshop:  Networking & Mentorship
DESCRIPTION:About the Workshop: Are you hesitant in reaching out to professional contacts on LinkedIn? Or you can not figure out how to start the process? Don’t worry\, come join this hands on workshop that Violet will tell you how to correctly connect with different contacts\, how to set up the right strategy that can enhance your reach. You will also learn how to maximize the benefit of a mentorship relationship that is already set up either through the Stats alumni mentorship program or built by yourself.
URL:https://ma.stat.columbia.edu/event/professional-workshop-networking-mentorship/
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230328T110000
DTEND;TZID=America/New_York:20230328T123000
DTSTAMP:20230320T162825Z
CREATED:20230320T162648Z
LAST-MODIFIED:20230320T162825Z
UID:9811-1680001200-1680006600@ma.stat.columbia.edu
SUMMARY:CPT Workshop with Q&A
DESCRIPTION:If you are a F-1 international student and are interested in working off campus during Summer 2023\, come join this session to learn about the F-1 Curricular Practical Training. In this session\, Violet will walk you through the general CPT application procedure as well as the Stat GR5399: Statistical Fieldwork course requirements.  \nThis workshop is to help students better understand the CPT requirements and application process.  Check the MA Statistics Newsletter for the RSVP Link. 
URL:https://ma.stat.columbia.edu/event/cpt-workshop-with-qa/
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END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20230324
DTEND;VALUE=DATE:20230327
DTSTAMP:20230313T175202Z
CREATED:20230313T174955Z
LAST-MODIFIED:20230313T175202Z
UID:9782-1679616000-1679875199@ma.stat.columbia.edu
SUMMARY:The Philosophy of Deep Learning Conference
DESCRIPTION:REGISTER  HERE \n\n\n\nThe conference will explore current issues in AI research from a philosophical perspective\, with particular attention to recent work on deep artificial neural networks. The goal is to bring together philosophers and scientists who are thinking about these systems in order to gain a better understanding of their capacities\, their limitations\, and their relationship to human cognition. The conference will focus especially on topics in the philosophy of cognitive science (rather than on topics in AI ethics and safety). It will explore questions such as: \n•What cognitive capacities\, if any\, do current deep learning systems possess? \n•What cognitive capacities might future deep learning systems possess? \n•What kind of representations can we ascribe to artificial neural networks? \n•Could a large language model genuinely understand language? \n•What do deep learning systems tell us about human cognition and vice versa? \n•How can we develop a theoretical understanding of deep learning systems? \n•How do deep learning systems bear on philosophical debates such as rationalism vs empiricism and classical vs. nonclassical views of cognition? \n•What are the key obstacles on the path from current deep learning systems to human-level cognition?\n  \nEvent Speakers \n•Cameron Buckner\, Associate Professor of Philosophy\, University of Houston \n•Rosa Cao\, Assistant Professor of Philosophy\, Stanford University \n•Ishita Dasgupta\, Research Scientist\, DeepMind \n•Nikolaus Kriegeskorte\, Professor of Psychology and Neuroscience\, Columbia University \n•Brenden Lake\, Assistant Professor of Psychology and Data Science\, New York University \n•Grace Lindsay\, Assistant Professor of Psychology and Data Science\, New York University \n•Tal Linzen\, Assistant Professor of Linguistics and Data Science\, New York University \n•Raphaël Millière\, Presidential Scholar in Society and Neuroscience\, Columbia University \n•Nicholas Shea\, Professor of Philosophy\, Institute of Philosophy\, University of London \n  \nA pre-conference debate on March 24 will address whether large language models need sensory grounding for meaning and understanding. Speakers include: \n•Jacob Browning\, Postdoctoral Associate\, New York University \n•David Chalmers\, University Professor of Philosophy and Neural Science\, New York University \n•Yann LeCun\, Silver Professor of Data Science\, Computer Science\, Neural Science\, and Electrical Engineering\, New York University \n•Ellie Pavlick\, Assistant Professor of Computer Science\, Brown University\n  \nEvent Information \nFree and open to the public. Registration is required via Eventbrite. All in-person attendees must follow New York University’s COVID-19 policies. NYU requires that you be able to show proof of COVID-19 vaccination\, including one booster\, if asked. You must register at least 24 hours in advance so that your name/email address can be sponsored in the NYU system. You will need to show proof of government ID to a security guard. \nThis event is co-organized by Presidential Scholars in Society and Neuroscience at Columbia University as part of the Seminars in Society and Neuroscience series and by the Center for Mind\, Brain\, and Consciousness at New York University. \nThe Center for Mind\, Brain\, and Consciousness at New York University provides reasonable accommodations to people with disabilities. Requests for accommodations should be submitted to philosophy@nyu.edu at least two weeks before the event. \n\n\n\n\n \n\n 
URL:https://ma.stat.columbia.edu/event/the-philosophy-of-deep-learning-conference/
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230323T113000
DTEND;TZID=America/New_York:20230323T123000
DTSTAMP:20230313T171654Z
CREATED:20230313T171249Z
LAST-MODIFIED:20230313T171654Z
UID:9772-1679571000-1679574600@ma.stat.columbia.edu
SUMMARY:Data Science Industry Practitioner Talk with Eric Feder of Lyft\, Inc.
DESCRIPTION:Lyft\, Inc. Data Scientist\, Eric Feder\, will give an overview of the different kinds of work that data scientists do through the lens of projects that he has worked on throughout his career. Speaking on a range of experiences\, from causal inference to forecasting to natural language processing\, Eric will discuss both the technical and non-technical tasks that data scientists need to do to create valuable contributions to an organization. \nPlease see the MA Newsletter for details & RSVP. 
URL:https://ma.stat.columbia.edu/event/data-science-industry-practitioner-talk-with-lyft-inc-s-eric-feder/
ATTACH;FMTTYPE=image/png:https://ma.stat.columbia.edu/wp-content/uploads/2023/03/2023-03.23.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230323T080000
DTEND;TZID=America/New_York:20230323T170000
DTSTAMP:20230323T165020Z
CREATED:20230118T195233Z
LAST-MODIFIED:20230323T165020Z
UID:9475-1679558400-1679590800@ma.stat.columbia.edu
SUMMARY:LAST DAY to choose PASS/FAIL or R CREDIT
DESCRIPTION:Decisions to take a particular course Pass/Fail or for R credit are not reversible after this date (GSAS Rule).  \n\nCourses taken for PASS/FAIL or R Credit DO NOT COUNT TOWARD GRADUATION. \nA class must have a LETTER GRADE to count toward graduation. \nA course taken for Pass/Fail cannot be taken a second time to receive a better grade.*\n\nCOURSES TAKEN FOR R GRADE OR PASS/FAIL\nDuring the semester there are important dates to remember including the LAST DAY to DROP COURSES and the LAST DAY for R Grade & PASS/FAIL.  These deadlines are strictly followed.** \nPASS/FAIL — Not all courses are eligible for P/F.  \n\nCheck on SSOL to see if the course is eligible for P/F and select.\nIf not available on SSOL\, check with your instructor.\nIf instructor approves P/F\, but it’s NOT eligible on SSOL\, have the instructor sign a RAF .  Send the form to gsas-studentaffairs@columbia.edu. \nClick HEREfor further details on the “Pass/Fail” grade.\n\nR CREDIT \n\nR grades must be approved by the course instructor.  You must make an arrangement with the instructor.\nClick HERE for further details on the “R” grade. \n\nCourses taken for R or Pass/Fail do not count towards the MA Statistics degree.  \n\nCore classes may not be taken for R or P/F.\n\nFrom the GSAS Website:   \nR credit and Pass/Fail (P/F) are two different marks. Unlike R credit\, the mark of P/F assesses the quality of a student’s performance. Additionally\, students taking a course Pass/Fail are evaluated on all the gradable assignments for the course.  \nStudents who elect to take a course for R credit are not required to take the final examination; however\, they must meet all other course requirements\, unless the instructor states otherwise in writing. \nOnce the Drop Date is past\, all the classes on your schedule will remain on your transcript.   \n*Students are not allowed to re-register for a course to improve letter grade.  (The only exception would be for a Grade of F which must be approved by the instructor\, the Faculty Director of the MA Program\, and the Graduate School of Arts & Sciences.  While the second grade will be used to determine graduation\, the original “F” will remain on the transcript and will affect the cumulative GPA that is visible on the transcript.)  \n\nReview REQUIREMENTS of the MA Degree.\nReview GOOD ACADEMIC STANDING.\n\n**Deadlines for half-semester courses are different from full-semester courses.  Half-semester courses must be dropped within the first two weeks.  The deadline to change the grade of a half-semester course to Pass/Fail is the first day of the fifth week of the course.  Core courses may NOT be taken for Pass/Fail or R Credit.
URL:https://ma.stat.columbia.edu/event/last-day-to-choose-pass-fail-or-r-credit/
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230322T180000
DTEND;TZID=America/New_York:20230322T190000
DTSTAMP:20230321T134223Z
CREATED:20230321T132855Z
LAST-MODIFIED:20230321T134223Z
UID:9828-1679508000-1679511600@ma.stat.columbia.edu
SUMMARY:COLUMBIA STATISTICS CLUB:  TECH ALUMNI PANEL
DESCRIPTION:Students interested in a career in tech or data science will benefit from hearing from our alumni in these fields.  Join the Columbia Statistics Club on Zoom.  \nFind out more on Eventbrite. 
URL:https://ma.stat.columbia.edu/event/statistics-industry-alumni-panel/
ATTACH;FMTTYPE=image/png:https://ma.stat.columbia.edu/wp-content/uploads/2023/03/2023-22-CSC-AlumniPanel-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20230319
DTEND;VALUE=DATE:20230320
DTSTAMP:20230313T180924Z
CREATED:20230313T180331Z
LAST-MODIFIED:20230313T180924Z
UID:9787-1679184000-1679270399@ma.stat.columbia.edu
SUMMARY:Apply to become an MA Student Mentor for the STAR PROGRAM
DESCRIPTION:Looking for a meaningful summer job on campus? This could be the opportunity for you!  \nFor this summer’s STAR Program\, the department is seeking 5-6 qualified and motivated MA students to serve as mentors for our undergraduate participants. We invite anyone interested to review and submit the application form by March 19\, Sunday\, 11:59PM ET.  Find the link in the MA Statistics Newsletter to apply.  \nWhat is the STAR Program? \nA six-week training program that takes place in person and on campus\, during the Summer Session A term (May 22-June 30) for undergraduate students interested in statistics\, data science\, computer science\, and other related fields. Program offers include a subsidized graduate-level class\, seminars and workshops\, and networking events. Most STAR participants are from historically underrepresented backgrounds.  \nWorkload and compensation: \n\n10 hours per week between May 22nd to June 30\, 2023 \n$21.5 per hour
URL:https://ma.stat.columbia.edu/event/apply-to-become-an-ma-student-mentor-for-the-star-program/
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END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20230313
DTEND;VALUE=DATE:20230318
DTSTAMP:20230118T205410Z
CREATED:20230118T204901Z
LAST-MODIFIED:20230118T205410Z
UID:9498-1678665600-1679097599@ma.stat.columbia.edu
SUMMARY:SPRING BREAK
DESCRIPTION:No classes.   Monday – Friday.
URL:https://ma.stat.columbia.edu/event/spring-break/
ATTACH;FMTTYPE=image/png:https://ma.stat.columbia.edu/wp-content/uploads/2023/01/springBREAK.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230310T150000
DTEND;TZID=America/New_York:20230310T160000
DTSTAMP:20220831T195856Z
CREATED:20220831T195508Z
LAST-MODIFIED:20220831T195856Z
UID:9011-1678460400-1678464000@ma.stat.columbia.edu
SUMMARY:VIRTUAL INFORMATION SESSION: M.A. in Statistics
DESCRIPTION:Join THIS Virtual Information Session.   Learn about our MA Program in Statistics at Columbia University and find out if it’s the right choice for you.  \n\n3pm – 4pm  /\nMar. 10\, 2023  \n\nFIND information on applying to GSAS and CREATE your application.  Introduction to GSAS Admissions. 
URL:https://ma.stat.columbia.edu/event/virtual-information-session-m-a-in-statistics-5/
ATTACH;FMTTYPE=image/png:https://ma.stat.columbia.edu/wp-content/uploads/2022/08/2022-23-MA-Info-Session-Image-cropped-e1661966661727.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230308T140000
DTEND;TZID=America/New_York:20230308T170000
DTSTAMP:20230313T163756Z
CREATED:20230228T230336Z
LAST-MODIFIED:20230313T163756Z
UID:9713-1678284000-1678294800@ma.stat.columbia.edu
SUMMARY:Mid-Term Study Break with Help Room
DESCRIPTION:The Help Room will be OPEN!  
URL:https://ma.stat.columbia.edu/event/mid-term-study-break-with-help-room-2/
ATTACH;FMTTYPE=image/png:https://ma.stat.columbia.edu/wp-content/uploads/2023/02/Midterm-study-BREAK-.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230307T140000
DTEND;TZID=America/New_York:20230307T170000
DTSTAMP:20230313T163158Z
CREATED:20230228T225759Z
LAST-MODIFIED:20230313T163158Z
UID:9710-1678197600-1678208400@ma.stat.columbia.edu
SUMMARY:Mid-Term Study Break with Help Room
DESCRIPTION:The Help Room in 617 will be OPEN!   \n 
URL:https://ma.stat.columbia.edu/event/mid-term-study-break-with-help-room/
ATTACH;FMTTYPE=image/png:https://ma.stat.columbia.edu/wp-content/uploads/2023/02/Midterm-study-BREAK-.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230303T130000
DTEND;TZID=America/New_York:20230303T140000
DTSTAMP:20230224T210132Z
CREATED:20230224T205918Z
LAST-MODIFIED:20230224T210132Z
UID:9706-1677848400-1677852000@ma.stat.columbia.edu
SUMMARY:CPT Workshop + Q&A
DESCRIPTION:CPT Workshop + Q&A\nThis workshop is to help students better understand the CPT requirements and application process. \nIf you are a F-1 international student and are interested in working off campus during Summer 2022\, come join this session to learn about the F-1 Curricular Practical Training. In this session\, Violet will walk you through the general CPT application procedure as well as the Stat GR5399: Statistical Fieldwork course requirements.
URL:https://ma.stat.columbia.edu/event/cpt-workshop-qa/
ATTACH;FMTTYPE=image/png:https://ma.stat.columbia.edu/wp-content/uploads/2023/02/CPT-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230302T123000
DTEND;TZID=America/New_York:20230302T133000
DTSTAMP:20230214T212044Z
CREATED:20230214T211731Z
LAST-MODIFIED:20230214T212044Z
UID:9648-1677760200-1677763800@ma.stat.columbia.edu
SUMMARY:Data for Good Seminar
DESCRIPTION:With Ian Foster\, Argonne National Laboratory and the University of Chicago.  \nHosted by DSI Computing Systems for the Data-Driven Science Center.  \nSee the MA Statistics Newsletter for more information. 
URL:https://ma.stat.columbia.edu/event/data-for-good-seminar/
ATTACH;FMTTYPE=image/png:https://ma.stat.columbia.edu/wp-content/uploads/2023/02/Data4Good.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230302T113000
DTEND;TZID=America/New_York:20230302T123000
DTSTAMP:20230224T204931Z
CREATED:20230224T204549Z
LAST-MODIFIED:20230224T204931Z
UID:9702-1677756600-1677760200@ma.stat.columbia.edu
SUMMARY:Data Science Practitioners’ Talk with Ali and Kai from Neuberger Berman
DESCRIPTION:Continuing our Data Science Industry Practitioners’ Talk Series\, we are excited to host Ali and Kai from Neuberger Berman! \nAbout Neuberger Berman: \nNeuberger Berman is a global asset management firm with over $400 billion in assets under management\, serving individuals\, families\, endowments\, foundations\, and institutions. Founded in 1939\, the firm employs a research-driven approach to investing\, focused on creating long-term value and managing risk. Neuberger Berman offers a wide range of investment strategies across equities\, fixed income\, private equity\, and hedge funds\, and is also known for its expertise in alternative investments and ESG (environmental\, social\, and governance) investing. \nSpeakers’ short Bio: \nKai Cui is a Managing Director and Head of Data Science at Neuberger Berman. Kai leads Neuberger’s team of data scientists and data analysts and collaborates with business units across asset classes to integrate data science and data insights in investment research and strategies. Prior to joining Neuberger Berman in 2018. Kai was a Vice President at Point72 Asset Management where he focused on big data and advanced data analytics in long/short equity research. Kai began his career at Validus\, a reinsurance and insurance-linked securities manager. He received a BS in Biology and Mathematics from Tsinghua University and a PhD in Statistics from Duke University. \nAli Gulamhuseinwala is a vice president and senior data science engineer at Neuberger Berman. Ali leads a team of data science engineers and works closely with the Data Science team to help with data sourcing\, onboarding\, processing and productionizing processes. Prior to working with the Data Science\, Ali was part of technology team developing applications in C# .NET and SQL. He received his MS in Computer Science from Syracuse University. \nTalk Overview: \nAs part of this talk we will go over how Data Science fits into the traditional asset management space and the insights it provides in investment research. We will also walk through the data engineering pipelines and describe how data from various sources is transformed and unified using various open source tools and technologies like AWS\, Databricks Spark and Snowflake. \nAttendance Policy: \nPlease note that space is limited\, if you register for a ticket\, we expect you to attend in-person. If you no longer able to attend\, please cancel your ticket at least 24 hours prior to the event\, this will give opportunity to the students on the waitlist. \nStudents who registered but did not attend MA Stats events for more then twice will result in not receiving career opportunities announcements in the future. \n  \nRSVP is required.  Please check the MA Statistics Newsletter for details. 
URL:https://ma.stat.columbia.edu/event/data-science-practitioners-talk-with-ali-and-kai-from-neuberger-berman/
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230301T170000
DTEND;TZID=America/New_York:20230301T190000
DTSTAMP:20230614T141406Z
CREATED:20230614T141406Z
LAST-MODIFIED:20230614T141406Z
UID:10217-1677690000-1677697200@ma.stat.columbia.edu
SUMMARY:PART-TIME STUDENTS' SOCIAL
DESCRIPTION:An informal dinner gathering was thoughtfully organized for Part-time MA Statistics Students\, scheduled conveniently after work hours.  This event provided an opportunity for the group to come together\, fostering connections and engaging in vibrant discussions about their shared interests.  The relaxed setting of the dinner allowed for meaningful interactions and the building of a supportive network among the participants.   
URL:https://ma.stat.columbia.edu/event/part-time-students-social/
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230227T100000
DTEND;TZID=America/New_York:20230227T113000
DTSTAMP:20230220T205600Z
CREATED:20230209T222907Z
LAST-MODIFIED:20230220T205600Z
UID:9632-1677492000-1677497400@ma.stat.columbia.edu
SUMMARY:SQL Workshop with Professor Charles Lang
DESCRIPTION:About Professor Lang: \nProf. Charles Lang is the Executive Director of the Digital Futures Institute at Teachers College\, Columbia University. Charles does research into education technology and has taught data science for the last eight years. \nEvent Details: To work within the data science industry it is necessary to be able to understand and work with the existing database architecture of an organization. The two hour SQL introductory workshop will cover essential aspects of working with databases to extract and analyze data.    The workshop will cover how to: \n\nSet up a common database architecture an SQL database in Amazon Web Services\nConnect to that database\, reading and writing data\nUse Basic SQL coding to query the database and using an RStudio SQL script\, querying an SQL database using dplyr
URL:https://ma.stat.columbia.edu/event/sql-workshop-with-professor-charles-lang/
ATTACH;FMTTYPE=image/png:https://ma.stat.columbia.edu/wp-content/uploads/2023/02/SQL-final.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230224T130000
DTEND;TZID=America/New_York:20230224T143000
DTSTAMP:20230214T211423Z
CREATED:20230214T211207Z
LAST-MODIFIED:20230214T211423Z
UID:9645-1677243600-1677249000@ma.stat.columbia.edu
SUMMARY:Data for DE&I - Improving Health Equity with Data
DESCRIPTION:An in-person iCubed Seminar event with KPMG.  \nSee the MA Statistics Newsletter for details. 
URL:https://ma.stat.columbia.edu/event/data-for-dei-improving-health-equity-with-data/
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230224T130000
DTEND;TZID=America/New_York:20230224T143000
DTSTAMP:20230214T212421Z
CREATED:20230209T222431Z
LAST-MODIFIED:20230214T212421Z
UID:9629-1677243600-1677249000@ma.stat.columbia.edu
SUMMARY:Emotional Intelligence Seminar with Steve Safier\, Ph.D.
DESCRIPTION:Emotional Intelligence (EI) is the ability to be aware of our own and others’ emotions and to manage those positively. Based on years of research and practical application\, EI has been found to be critical for interpersonal success at work and at home\, and is a topic for study and development around the world. Mastering EI can help; you in school\, job interviews\, on the job and throughout your life. \nOn Friday\, February 24 at 1 PM EST\, Dr. Steve Safier\,Director of the Masters in Human Capital Management Program at the Columbia University School of Professional Studies\, will conduct a seminar on EI. Dr. Safier has also held multiple senior executive positions in industry and served as a senior partner in a global managing consulting firm. https://sps.columbia.edu/faculty/steve-safier-phd \nSee the MA Newsletter for the RSVP. 
URL:https://ma.stat.columbia.edu/event/emotional-intelligence-seminar-with-steve-safier-ph-d/
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230222T210000
DTEND;TZID=America/New_York:20230222T233000
DTSTAMP:20230217T221526Z
CREATED:20230214T210306Z
LAST-MODIFIED:20230217T221526Z
UID:9642-1677099600-1677108600@ma.stat.columbia.edu
SUMMARY:Graduate Career Fair with Chinese Companies
DESCRIPTION:2023 Spring Graduate Student Finance and Quant Career Fair with Chinese Companies in partnership with Columbia Global Centers | Beijing\n\nWhen: Feb 22nd 2023 9:00PM – 12:00AM (EST) \nDuring the event\, students will have an exclusive opportunity for real-time engagement with recruitment professionals from multinational and reputable China-based companies.  \nFor GSAS students: \nResume submission deadline: February 16\, 12:00 pm ET \nPDF format: Resumes must be exactly 2-pages: 1-page resume in Chinese\, followed by a 1-page resume in English \nResume submission Instruction can be found here  \nEvent Participation Link will be shared with the registered students on Tuesday\, February 21st. \nCheck the MA Statistics Newsletter for registration link. 
URL:https://ma.stat.columbia.edu/event/graduate-career-fair-with-chinese-companies/
ATTACH;FMTTYPE=image/png:https://ma.stat.columbia.edu/wp-content/uploads/2023/02/Beijing.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230221T080000
DTEND;TZID=America/New_York:20230221T170000
DTSTAMP:20230220T203220Z
CREATED:20230118T200053Z
LAST-MODIFIED:20230220T203220Z
UID:9479-1676966400-1676998800@ma.stat.columbia.edu
SUMMARY:LAST DAY to DROP a CLASS
DESCRIPTION:TODAY IS THE LAST DAY TO DROP A CLASS.  \nGSAS does not allow a student to drop a class after TODAY.*   \nClasses dropped up to and including TODAY will not appear in your transcript.  \nDropping a Course is a Two-Step Process.   \nWhen you request to drop a course\, you will receive an email when your request has been approved.  Then you must log in to SSOL to complete the drop.   \nHERE is information about the Add/Drop Tool.  ALWAYS check that the course has been dropped from your schedule.   \nNot all Classes are Pass/Fail or R-Credit Available.   \nPlease speak with the Professor before the Drop Date if you are considering pass/fail or R credit to make sure that is an option.  \nImportant:   \n\n\n\nClasses dropped before the deadline will not appear in your transcript.  \nIf you do not drop the class from your schedule\, you will receive a grade for the course.**\nA course must have a grade in order to count for graduation.  \nPass/Fail or R credit do not count for graduation\n\n\n\nQuestions about Registration:   \n\n\n\nVisit the Student Service Center in Kent Hall \nTelephone:  212-854-4400\nEmail:  ssc@columbia.edu.  \n\n\n\n*Exception:  If the class is successfully cross-registered into another SCHOOL (For example\, the Engineering School (SEAS) or the Business School\, etc.) follow the deadlines for THAT School. \n**Not attending classes or sending a notification to the instructor does not constitute dropping a course. Students who stop attending a course without formally dropping it by the deadline should be assigned a letter grade based on the same criteria as students who complete the course. \n***Deadlines for half-semester courses are different from full-semester courses.  Half-semester courses must be dropped within the first two weeks.***
URL:https://ma.stat.columbia.edu/event/last-day-to-drop-a-class-2/
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230216T100000
DTEND;TZID=America/New_York:20230216T160000
DTSTAMP:20230214T214033Z
CREATED:20230214T204723Z
LAST-MODIFIED:20230214T214033Z
UID:9637-1676541600-1676563200@ma.stat.columbia.edu
SUMMARY:Columbia University Graduate Career Expo
DESCRIPTION:Free for all participating Schools of Columbia University.  \nHave you already registered for the Columbia Graduate Virtual Career Expo on February 16\, 10:00 am – 4:00 pm?  \nCareer fairs and expos are unique opportunities to network with a large number of recruiters from a wide range of organizations who are excited to identify and meet with prospective applicants. Having real-time interactions with recruiters is invaluable in your job-hunting process. Join next week’s Expo to network with employers\, explore roles and industries of interest\, and further propel your career exploration!But\, how can you best prepare to participate in a virtual career fair? Freelance career coach and writer\, Kaila Kea-Lewis\, compiled a few suggestions in her article “Your Guide to Virtual Career Fairs—So You Can Impress From Afar” and MintLife provides several hints in their “10 Ways to Master a Virtual Career Fair.”Don’t miss out on this rich opportunity! Register for the Expo at: careereco.com/events/CU \nP.S. GSAS Compass will host a virtual preparation session on February 14 at 12:00 pm. Join us to pick up best practices and to learn more about ways to prepare for success during the Expo. Register for the session via Zoom. \nRegister for the Career Expo HERE
URL:https://ma.stat.columbia.edu/event/columbia-university-graduate-career-expo/
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20230214T113000
DTEND;TZID=America/New_York:20230214T123000
DTSTAMP:20230211T142039Z
CREATED:20230207T192940Z
LAST-MODIFIED:20230211T142039Z
UID:9623-1676374200-1676377800@ma.stat.columbia.edu
SUMMARY:Lunch with Dr. Xin Feng
DESCRIPTION:Dr. Xin Feng is an alumnus of our Ph.D. program. He has had a very successful career in quantitative finance.  \nDr. Feng is eager to share his insights on upcoming opportunities in the field with our students.  He will discuss how utilizing the resources and courses offered by our Statistics Department and MA Program can help prepare them for success. For more information\, please refer to the latest edition of the MA Newsletter. \nFrom Dr. Xin Feng:  \n\nAfter getting my PhD\, I worked briefly in the educational testing industry for 9 months\, then started my career in quant trading. Working at hedge funds and a prop desk in a bank\, I primarily worked on statistical arbitrage strategy in global equity and managed futures strategies. Luckily I experienced the whole flow from building alpha\, to constructing portfolio and doing execution. \n \nAfter working in New York for 10 years\, I set up WizardQuant in China in 2013. Starting with just a few people\, we have grown into a multi-billion quant hedge fund with a team of over 150 people in 5 different offices in New York\, Shanghai (headquarters)\, Beijing\, Shenzhen\, Chengdu. We work with data every day\, try to understand the patterns in the data\, forecast the movement of financial instruments and see the result almost instantaneously\, which is quite exciting. 
URL:https://ma.stat.columbia.edu/event/lunch-with-dr-xin-feng/
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DTSTART;TZID=America/New_York:20230210T150000
DTEND;TZID=America/New_York:20230210T160000
DTSTAMP:20220831T200023Z
CREATED:20220831T195137Z
LAST-MODIFIED:20220831T200023Z
UID:9007-1676041200-1676044800@ma.stat.columbia.edu
SUMMARY:VIRTUAL INFORMATION SESSION: M.A. in Statistics
DESCRIPTION:Join THIS or one of our upcoming Virtual Information Sessions.   Learn about our MA Program in Statistics at Columbia University and find out if it’s the right choice for you.  \n\n3pm – 4pm  /\nFeb. 10\, Mar. 10\, 2023  \n\nFIND information on applying to GSAS and CREATE your application. Introduction to GSAS Admissions. 
URL:https://ma.stat.columbia.edu/event/virtual-information-session-m-a-in-statistics-4/
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