Summer 2026 Admitted Student Events

Welcome to the Columbia Statistics community! We encourage all incoming Fall 2026 MA in Statistics students to join our summer event series. These sessions are designed to help you prepare for the upcoming semester, explore research and professional opportunities, and connect with our thriving community. 

Event Registration Instructions – Please Login to Canvas using instructions below

Click here to log in to CourseWorks and register for the Summer events.

• If you have a Columbia UNI, select “UNI Login” and sign in using your UNI and password. Please refer to the GSAS New Student Checklist page to activate your UNI and Columbia Email.
• If you do not have a Columbia UNI, select “Guest Login” and sign in using the email address associated with your GSAS Admissions application.

Event Schedule

Mentored Research Panel: Student Insights & Experiences

• Date & Time: Thursday, June 11, 2026 | 8:00 PM – 9:00 PM EST
• Moderator: Professor Tian Zheng
• About: Curious about how to take your academic journey to the next level? Join us for an inspiring conversation with recent MA in Statistics graduates who have been exactly where you are. They’ll dive into their firsthand experiences with cutting-edge mentored research in AI and data science, share insider tips on uncovering the best on-campus opportunities, and offer invaluable advice to help you pave your own path to success.

Professional & Career Development Webinar

• Date & Time: Tuesday, June 16, 2026 | 9:30 AM – 10:30 AM EST
• About: Students will gain a foundational understanding of the career development process and learn how to navigate the job search with confidence. The session covers resume optimization, networking strategies, finding job and internship opportunities, recruiting timelines, and application best practices.

  Participants will also learn about employer expectations, professional branding, and the career resources available through Columbia University. Whether you’re exploring career options or preparing for an active search, this session offers practical guidance and actionable next steps to help you move forward.

• Key Topics: Effective networking, understanding recruiting timelines, navigating employer expectations, and accessing exclusive Columbia career resources.
• Student Career Survey This survey helps us understand your career goals and professional interests after graduation. By sharing your target industries, aspirations, and job search plans, you enable us to offer more relevant resources, tailored career support, and meaningful networking opportunities throughout your time in the program.

MA Mentored Research: Faculty Spotlights

• Date and Time: Thursday, June 18, 2026 | 9:30AM-11:00AM
• Speakers: Marco Avella, Ph.D.; Sharon Di, Ph.D.; Khanh N. Dinh, Ph.D.; Tian Zheng, Ph.D. Liam Paninsk, Ph.D. 
• About: Are you interested in pursuing research as part of your MA in Statistics experience? Join us for an exclusive webinar where you can hear directly from faculty members whose research spans a wide range of cutting-edge fields — from robust statistics and machine learning to urban transportation, cancer genomics, and AI-driven data science.

Columbia Student Life & Campus Services Webinar

• Date & Time: Friday, June 26, 2026 | 9:30 AM – 10:30 AM EST
• About: Your graduate experience is about so much more than just midterms and coding! Meet Columbia’s Graduate Student Life Team for a vibrant introduction to your new home away from home. From exploring bustling student clubs and navigating housing to unlocking essential campus services and mastering life in New York City, this session ensures you arrive ready to thrive both inside and outside the classroom.

Summer R/Python Coding Bootcamp

• Date & Time: Tuesday, July 7 – Friday, July 31, 2026 | 8:00am-10:00am EST
• Instructors: Alex Pijyan (R) & Ben Goodrich (Python) – Lecturers in Discipline, Department of Statistics
• About: Hit the ground running this fall! This intensive, four-week bootcamp is your ultimate toolkit for a data-driven curriculum, equipping you with total fluency in R and Python—the ultimate power duo of modern statistics, data science, and quantitative research. Through interactive lectures and hands-on coding challenges, you’ll evolve from foundational principles to advanced data manipulation and stunning visualization, giving you the ultimate confidence boost before day one of classes.
• Structure: The bootcamp is organized into two consecutive instructional modules: the first two weeks focus on R, followed by two weeks focused on Python. Review Full Course Overview and Syllabus here.

Preview Lecture: The Delta Method

• Date & Time: Tuesday, July 7, 2026 | 9:30 AM – 11:00 AM EST
• Featured Speaker: Gabriel J. Young-Lecturer in Discipline, Department of Statistics, MA Program Director
• About: Consider this your strategic roadmap for the upcoming year! Join us for an essential deep dive into the program’s academic architecture. This lecture will walk you through upcoming course offerings and structural highlights, ensuring you have a crystal-clear vision of your academic journey ahead.

Math Refresher Course 

• Date & Time: Wednesday, July 8 – Friday, July 17, 2026 | 9:00pm-11:00pm EST
• Instructor: Prof. Dobrin Marchev – Lecturer in Discipline, Department of Statistics
• Structure: Six courses taught 3 classes per week across two weeks.
• About: Dust off those math muscles and gear up for Fall 2026! This optional, high-impact refresher is designed to sharpen your mathematical edge and ensure a seamless transition into graduate-level coursework. We will breathe new life into essential topics like calculus, linear algebra, and optimization, directly tying them to their real-world applications in probability and statistics.

Webinar on Course Registration & Program Essentials 

• Date & Time: Tuesday, July 28, 2026 | 9:30 AM – 10:30 AM EST
• About: The final countdown is on! This crucial, final session is designed to cross the t’s and dot the i’s before your classes officially begin. We will walk you step-by-step through the course registration portal and review key program requirements, ensuring you cross the starting line feeling completely prepared, organized, and stress-free.

Congratulations to our MA Statistics student, Shuxin Tang, and her team members at NYU School of Global Public Health for being selected as finalists in the upcoming Eastern North American Region (ENAR) DataFest competition! They will be presenting their work on March 24, 2025, in New Orleans. The statistics community couldn’t be more proud of Shuxin’s accomplishments.

Leonard Mushunje, Shunri (David) Zheng, Tengyu Song, and Qinyuan Dong received a departmental Travel Award to attend the JSM Conference in Toronto this summer. Read about their conference experience!

Leonard:

“My experience at the 2023 JSM conference was undoubtedly life changing and rewarding.

The program was packed with captivating, diverse and rich sessions ranging from theoretical to applied Statistics topics. More than hundred sessions were delivered every day and I was fortunate to attend interesting sessions on high dimensional statistics, the future of data science and algebraic statistics. These sessions have definitely enriched me with more advanced knowledge in algebraic statistics, high dimensional statistics, and ultimately my approach to conquering the data science arena. A big thank you goes to the Statistics department for honoring me with a Travel award to attend the JSM 2023. I also had time to listen to talks from bright minds from top notch schools and organizations such as Harvard, MIT,

Stanford, Columbia, Oxford, University of Cambridge, Google, DeepMind, Fidelity Investments among others. I also had a chance to present my poster, “Generative adversarial networks for high dimensional financial time series data” and I received useful feedback and comments from the audience. My hope is to give a special or invited talk in the future JSM conferences. Last but not least, one of the most memorable benefits from the conference was networking. With over 6000 participants from both academia and industry, I managed to create lifelong networks and had time to share my past, current and future plans with others, molding me into a more determined scholar. We had a JSM app which enabled us to access the contact information for all speakers and attendees which made our future networking easier.”

David:

“Attending the Joint Statistical Meetings (JSM) was an exhilarating experience for me. It was my first dive into the world of academic conferences, and every moment was filled with learning and connection. I was especially captivated by the talks and courses centered around reinforcement learning, a topic I’m deeply passionate about. Beyond the academic insights, JSM provided a wonderful platform to bond with like-minded individuals. I found joy in making new friends and discussing shared interests with students and professionals alike. The event was a wealth of knowledge, and I am grateful for every session I attended. A special thanks goes to our department for their support, making this enriching experience possible for me.”

Tengyu:

“I had the amazing opportunity to attend this year’s Joint Statistical Meeting (JSM) in Toronto, my first-ever JSM experience. Let me sum up my time there.
JSM is a fantastic place to learn about new statistical topics. Every day, there are lots of interesting presentation sessions, though sometimes I had to choose because they overlapped. They also offer professional development courses for an extra fee. Just before JSM began, Mr. Peterson emailed me to volunteer as a course monitor. This let me take a professional development course for free. So, I ended up taking two courses without any charge. These courses were really good, especially the one about fundamental reinforcement learning. The instructors covered the basics and also talked about their own research and where current theories might have gaps. 

JSM is also great for making connections. There are loads of people at the event, like professors, exhibitors, and PhD students from around the world. I met many people during the first-timer orientation, poster sessions, receptions, and even the dance party. I quickly made friends with a lot of them. 

JSM isn’t just about learning and networking – it’s fun too. At the EXPO, you can chat with exhibitors and get some cool stuff. The dance party is a chance to relax with colleagues and friends over a beer. I even joined the scavenger hunt, scanning QR codes at different places to win prizes. I didn’t quite make it to the top five, but the organizers still gave me a free JSM T-shirt. 

And of course, I can’t forget the COPSS Award. This year, Professor Tibshirani from Berkeley won it. Also, Professor Gelman got the Monroe G. Sirken Award and gave an interesting talk about his latest research on handling weight in sampling inference. 

All in all, my first JSM experience was a mix of learning, networking, and fun. It broadened my statistical knowledge and helped me connect with others in the field. I am deeply grateful to our statistics department for granting me this remarkable opportunity.”

Qinyuan:

“My first-time academic conference experience has been more than fantastic. Though I only

stayed for three days, the impressive academic atmosphere and abundant presentations are

something that I will never forget. To meet my previously learned knowledge and future research

interests, I joined several presentations regarding Bayesian statistics and machine learning,

which I might not be able to thoroughly understand but really got me exposed to the newest and

most advanced theories and methods. During the conference, I enjoyed wandering in the JSM

Expo and taking part in the scavenger hunt, exploring those companies and organizations that

successfully bring statistics into application. Also, I went to our department’s reception and

luckily had the chance to talk to Chair Zheng and fellow students, which really gave me the

feeling of being in this great family of statistics.”

Congratulations, Master’s Degree Graduates!! 

For Leadership & Mentorship.