Chris Davies: “Today, we are here to recognize and celebrate these students who began, endured, and successfully completed the PINC, GOLD, or gSTAR certificate programs. I want to begin by saying congratulations and well done. Bringing together the fields of computing and data science with biology and chemistry is a pathway towards the future, that is now. The growth of technology to analyze large data sets, create applications, and the ability to code has never been more important in a generation than it is now. To the dreamers and organizers of these programs, I am happy to say your dream has come true amongst these students today.
Matt Suntay is one of the students in the PINC program and also a research student in my lab in the E. coli / drug resistance / machine learning team. A few days ago he gave a speech at our PINC/GOLD/gSTAR graduation event. I thought it was a great speech and Matt was kind enough to let me share it here both as a video and the text for those of you who prefer reading.
“To those of you who may know me, you all know I’m pretty adventurous. For those of you who may not know me, first off, my name is Matthew Suntay, and I have jumped off planes, cliffs, and bridges – and each time was just as exhilarating as the last. But, let me tell you about my most favorite jump: the leap of faith I took for the PINC program.
My biggest advice when pursuing an internship, career, degree, etc. is to be your authentic self, know you are good enough, and do what is best for your growth.
How did you decide to get a degree in biology? What interested you in making this choice?
My interest in science stems from wantingto understand how thehuman body works in order to have a better knowledge whenunderstandingmedical conditions mylovedones suffer from. WhenI was a child, my father had a stroke — my family’s frustrations from not fully understanding how my father was affected by this incident and the doctors not having all of the answers is what initially piqued my interest in studying science,I wanted to be able to understand and answer those questions.
Why are you interested in a career in Biotech? What inspires you…
Adrian Choppa, Kaila Marie Gemenes, Natassja Punak and Imani Warren worked on a project to create a virtual reality game for the Tourniquet Master Training (TMT) by Stanford Technology Enabled Clinical Improvement Center. They worked with Dr Anagha Kulkarni and Dr Ilmi Yoon and mentors Jose Castanon, Ben Tingle.
Hailey Garma, Austin Sanchez and Caroline Solis worked on a flow cytometry project with Dr Anagha Kulkarni, Dr Nicole Adelstein and Dr Shadi Toghi Eshghi (Genentech) and mentors: Erick Velez, Sally Mostafa.
Yesterday, she came to SFSU to give a talk in our seminar series and to meet with student from the PINC program. The PINC students had many questions about PhD programs, computer languages, how to deal with failure and how it is to be a woman of color in the academic world.
In the fall of 2019, the SFSU PINC program is welcoming a new cohort of PINC minor students.
The first class of the minor (CSC 306) is an intro to programming in Python and will be taught by Dr Pleuni Pennings on MW 3:30 – 4:45 in Thornton 329. CSC 306 is a gentle introduction to the world of programming and students need absolutely no prior knowledge. The class is open to students from Biology / Biochem/ Chemistry. Students can simply sign up for the class, we no longer ask students to apply to become a PINC student. Pre-Biology students very welcome!
If you want to do the entire minor, it consists of 5 classes usually taken over 4 semesters. Master students can sign up for the classes, but cannot get the minor.
If you have any questions, please email pennings @ sfsu . edu.
The promotion video above was made by Niquo Ceberio with the help of Jhony Zavaleta who both took CSC 306 in the fall of 2018. The two students who are interviewed in the video are Emily Samperio (who is now taking CSC 698) and Maria Flores (who is now in CSC 220).
We try to keep track of where PINC students go and recently, many PINC students have been successful in getting into PhD programs or interesting jobs.
Last year, Cecelia Brown did an internship at IBM Research and started a PhD program at Stanford. Ezequiel Lopez started a job doing data analysis for the SF BUILD program on our campus. But graduation from PINC doesn’t necessarily happen at the same time as graduation from SFSU, so many of the PINC 2018 students are now graduating and going different places.
Dr Carla Pugh is a surgeon, researcher and educator. In her lab, she builds anatomical models with sensors that interface with computers to help medical professionals learn how to use touch better, in other words, to train their haptic skills. Touch is key for many medical examinations (e.g., finding a lump in a breast) but it is hard to train people to do such examinations correctly. To learn more about her work have a look at this Ted Talk: https://www.tedmed.com/talks/show?id=292997
On March 4th, 2019, Students from the PINC program at SFSU and the Howard West Program at Google were invited to visit her lab and learn about her work.
A special treat for the PINC students was that we got to talk to Cecilia Brown, a PINC alum who is now a PhD student at Stanford.
The PINC program started in 2016 as a collaboration between the CS and Biology Departments at SFSU. Now, two years later, we are extremely happy to announce that were awarded 1.3 million dollars from the NSF to continue our efforts in the next 5 years!
The money will be used to run separate PINC sections for CS classes, to hire PINC mentors, to run the PINC summer program and to do research on how we can best support women and students from underrepresented groups in their CS journey.
Abstract of the NSF proposal
This project aims to address two pressing needs in STEM education: 1) increasing the number of students graduating with expertise in data and computer science; and 2) improving diversity in STEM fields. The project team at San Francisco State University (SFSU) will achieve these goals by developing and implementing a Computing Application minor. This minor will use evidence-based approaches to attract, retain, and support students, with attention to students from groups that are underrepresented in computer/data science, including female students. By tailoring activities to students’ majors, the project expects to increase student engagement and help students experience how data and computer science are applied in their majors and future professions. Students in the minor will have opportunities to work with local industry and governmental agencies. In addition, this project will link to the NSF INCLUDES project at SFSU. As a result, the Computing Application minors will be able to work with high school students as computer science mentors and role models. These experiences can support development of critical skills, including leadership. The project aims to provide a sustainable and scalable model for introducing data and computer science to science majors that can be adopted by other institutions, and that can broaden participation in those fields.
The Computing Application minor will be a four-semester, five-course sequence designed for STEM students who have no prior computer/data science knowledge and who are taking a full course load in their major. The project will provide participating students with learning experiences related to their majors, train computer science faculty in evidence-based science teaching methods, and invite students to share their knowledge with the K-12 community. To reduce stereotype threat and imposter syndrome, the project will employ a cohort-based structure that uses peer, faculty, and industry mentors to create a nurturing and supportive community of learners. The project will identify pedagogies that promote students’ interest in computer/data science and their motivation to use it in their majors. These research results can inform other efforts to broaden the diversity of people who have computational expertise, and who decide to pursue graduate degrees and careers in computer/data science.
Eight teams of mostly undergrad students from Biology, Biochemistry, Economics and other disciplines spent 9 weeks during the summer of 2018 learning “Big Data” skills. Each team was led by a senior undergrad or graduate student, with support from a professor. The program was run by Drs Rori Rohlfs (biology), Nicole Adelstein (chemistry), Sepideh Modrek (economics) and Pleuni Pennings (biology).
During the 9 weeks of the program, students worked in small groups for 10 hours a week on campus. In the first weeks of the program, each team worked through an online class, and then they applied their new skills to a research project. For example, one team learned data science skills in R and then analyzed data on the experience of students in our local REU program. Another team learned machine learning skills and then worked on a project to determine the subtype of an HIV sequence using machine learning algorithms.
Many of the students in the program were recruited to the different labs on campus to continue doing computational research. Several students joined the PINC program to take their first CS class.
The “splicing team” did computational research on alternative splicing during the 2018 summer program.