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.
Meet Stuart Castaneda! He is a PINC Mentor and graduate student at San Francisco State University. His current research delves into the HIV-1 subtype B’s different mutation classes and their fitness costs. Stuart utilizes coding to analyze this data! To read more about Stuart, his research and career outlook, as well as what he does as a PINC mentor, please check out his interview below.
How did you get into coding?
I was curious on how coding could be applied to various biological questions. More specifically I wanted to know how scientist design systems and models to analyze biological data. I learned about the PINC program through a colleague and thought the program would be a perfect fit to solving my questions about coding. I believe my first programming language I was introduced to was Python. After the first class I established a great foundation with the basics and was able to transfer the experience to learn new computer program languages.
How did learning coding skills impact your career/career goals?
After learning how to code, I knew that I would always want a component of coding during my research career. My current research requires coding to analyze and estimate fitness costs of different mutation classes in HIV-1 subtype B. Coding makes this process of analyzing large datasets fast, and reproducible. A great skill I learned during PINC is to annotate my code. This allows others to understand what my code does step by step.
What do you do as a PINC mentor?
As a PINC mentor I try to get to know my mentees and help them with any problems they find during the course. These problems can range from homework to understanding concepts covered in class. So far, I’ve only helped in the first class that all PINC scholars take, CSC 306. In this class scholars are introduced to Python, a computer language that I was first introduced to, and learn the basics of coding. I believe having a mentor in this first class is a great necessity, since this is their first step into the coding world.
What do you like about being a mentor?
My favorite part about being a mentor is helping my mentees understand computer science concepts. It allows me to think of analogies and visual aids that could explain these concepts that they are having trouble with.
For example, my favorite concept to explain to students is how for loops work. Imagine you’re driving on the road and you are directed into a racetrack. This racetrack will be our “for” loop. As you drive around the racetrack you notice a sign on the jumbotron saying “If you want to exit do 100 laps”. This is your conditional statement that must be met in order to exit the racetrack. The screen keeps track of the number of laps you’ve done and always compares it to 100. As you do your 100th lap the screen says “Exit” and one of the gates lead you back on to the road.
Do you have any advice for students wanting to join the PINC program?
Don’t be intimidated by learning a new computer language. Learning to code can be daunting at first, but if you have the time and determination, anyone can learn.
What do you think are the benefits of being a part of the PINC program, both as a mentor and a mentee?
There are several benefits that I received as a mentee in the PINC program. As a mentee I was guided by my mentor on how to approach concepts and problems. Our program coordinators hosted networking events, and professional panels. My favorite experience as a mentee was working as a team with my fellow colleagues. Just like programming professionals, we were tasked to work on a year-long project and had actual deadlines to finish our product. As a mentor I have the opportunity to pass down what I learned to my mentees. This experience as a mentor has given me translational skills to teach future colleagues.
What are your next steps?
My next step is to finish my research project, and graduate with my master’s in science from SFSU. My current project deals with analyzing sequence data of HIV-1 subtype B. I plan to prove that CpG creating mutations are costly to HIV-1 subtype B. This class of mutation has been shown in previous studies to be costly in one region of HIV. My project hypothesizes that these mutations are costly throughout the genome. I plan to begin my PhD in Bioinformatics, at the University of Michigan later this year!
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.
Promoting Inclusivity in Computing (PINC) via Computing Application Minor
Ilmi Yoon, Pleuni Pennings, Anagha Kulkarni, Kaz Okada, Carmen Domingo
Abstract— We aimed to build a new educational pathway that would provide basic training in computer science for women and students from underrepresented (UR) groups who otherwise may not take computer science classes in college. Specifically, this on-going project focused on creating a 2-year Computer Science (CS) program consisting of exciting new courses aimed at biology majors. Biology traditionally attracts large numbers of women, a significant number of students from UR groups, and has compelling needs for CS technology. The interdisciplinary program is training the next generation of innovators in the biological sciences who will be prepared to cross disciplinary boundaries. The program consists of the following: (1) computer science courses with content related to biology, (2) cohorts of students that progress through the program together, and (3) a small group peer mentoring environment, and (4) facilitated interdisciplinary research projects. Graduates from this program, referred to as “PINC” – Promoting INclusivity in Computing – will receive a “Minor in Computing Applications” in addition to their primary science degree in Biology. The program is now in its second year and thus far 60 students have participated. Among them, 73% are women and 51% are underrepresented minorities (URM). The majority of students in the PINC program stated that they would not have taken CS courses without the structured support of the PINC program. Here we present the data collected during this two year period as well as details about the Computing Application minor and programmatic components that are having a positive impact on student outcomes.
Promoting Diversity in Computing
Anagha Kulkarni, Ilmi Yoon, Pleuni Pennings, Kaz Okada, Carmen Domingo
Abstract: In this paper we present a pilot program at San Francisco State University, Promoting INclusivity in Computing (PINC), that is designed to achieve two goals simultaneously: (i) improving diversity in computing, and (ii) increasing computing literacy in data-intensive fields. To achieve these goals, the PINC program enrolls undergraduate students from non Computer Science (non-CS) fields, such as, Biology, that have become increasingly data-driven, and that traditionally attract diverse student population. PINC incorporates several well-established pedagogical practices, such as, cohort-based program structure, near-peer mentoring, and project- driven learning, to attract, retain, and successfully graduate a highly diverse and interdisciplinary student body. On successful completion of the program, students are awarded a minor in Computing Applications. Since its inception 18 months ago, 60 students have participated in this program. Of these 73% are women, and 51% are underrepresented minorities (URM). 74% of the participating students had nominal or no exposure to computer programming before PINC. Findings from student surveys show that majority of the PINC students now feel less intimidated about computer programming, and vividly see its utility and necessity. For several students, participation in the PINC program has already opened up career pathways (industry and academic summer internships) that were not available to them before.
The PINC program is a collaboration between the Biology and the CS department. One of our goals is to make CS more accessible for non-CS majors, and one way to track our success is to see if the number of Biology students who are taking CS classes is increasing. We just got the data for Fall 2017 and we see that the fraction of Biology majors (undergraduates) who are taking a CS class has increased for the 3rd time in a row. The PINC program launched in Fall 2016. Thanks to Institutional Research for providing the data!