In an effort to reduce inequities in the PhD application process, a group of PhD students have created the Pre-Submission Application Review (PAR) Program to help applicants to the PhD program.
When Chris Kedzie and Katy Gero heard about Stanford University’s Student-Applicant Support Program they immediately thought, “this is something that we can do at Columbia.” Within hours they put together a rough plan on how to help applicants of the PhD program – by lending their expertise with reviewing a personal statement.
“Many times people who end up in PhD programs get there because of an invisible network of support, normally from other people who have attended a PhD program,” said Chris Kedzie, a seventh-year PhD student. When he was applying to graduate programs many of his friends who were in PhD programs helped and gave him invaluable feedback on his application, specifically his personal statement. “But for those who do not have access to that kind of network, it can put them at an unfair disadvantage.”
This review program attempts to fill the gap and help provide access to PhD students who can look over an applicant’s statement of purpose. “It is certainly not even close to addressing all of the systemic problems that some people face when applying to grad school,” said Katy Gero, a fourth-year PhD student. She, too, had friends in PhD programs who helped her with her application and she saw what a big difference getting feedback and guidance made. “We hope this is a small step in the right direction and it is something that we as grad students can implement ourselves.”
The initiative did not pop up out of the blue. Kedzie and Gero have been meeting with other students, faculty, and department staff since the #ShutDownSTEM strike for Black lives on June 10th. Over the summer, the group brainstormed ways that they can make the CS department more equitable. One of the points discussed was making the PhD program more accessible and so it was easy to get the group’s support for the PAR Program.
The initiative was put together quickly because of the support of fellow students, like Khalil Dozier and Tim Randolph, along with Associate Director for Academic Administration and Student Services Cindy Meekins, Professor Augustin Chaintreau, and CS Department Chair and Professor Rocco Servedio. The program was presented to the Dean’s office and officially launched in mid-October.
“The Computer Science Department is very happy to support our PhD students in this effort that they have led to improve the equity of our PhD program,” said Rocco Servedio, a professor and chair of the department. The department launched the CS@CU MS Bridge Program in computer science last year and is working on other programs with students and faculty. “We hope that this and other similar-in-spirit programs will bear fruit in broadening access to our department to a wide group of learners.”
Interested applicants have to apply to the PAR program and submit their personal statement and CV by November 7th at 11:59 pm EST. Because the program is student-run and dependent on volunteers, there is no guarantee that every applicant can be accommodated. For those who are accepted, they will be notified, then paired with a PhD student in the same research area who will review their materials and provide feedback to them by November 21st – well ahead of the December 15th deadline to apply to the PhD program.
“We have been really impressed by the support we have seen,” said Kedzie. “We hope that this is a step towards a lot of bigger changes to the department and the school, to make it a more equitable place for everyone.”
Payal Chandak (CC ’21) developed a machine learning model, AwareDX, that helps detect adverse drug effects specific to women patients. AwareDX mitigates sex biases in a drug safety dataset maintained by the FDA.
Below, Chandak talks about how her internship under the guidance of Nicholas Tatonetti, associate professor of biomedical informatics and a member of the Data Science Institute, inspired her to develop a machine learning tool to improve healthcare for women.
Payal Chandak
How did the project come about? I initiated this project during my internship at the Tatonetti Lab (T-lab) the summer after my first year. T-lab uses data science to study the side effects of drugs. I did some background research and learned that women face a two-fold greater risk of adverse events compared to men. While knowledge of sex differences in drug response is critical to drug prescription, there currently isn’t a comprehensive understanding of these differences. Dr. Tatonetti and I felt that we could use machine learning to tackle this problem and that’s how the project was born.
How many hours did you work on the project? How long did it last? The project lasted about two years. We refined our machine learning (ML) model, AwareDX, over many iterations to make it less susceptible to biases in the data. I probably spent a ridiculous number of hours developing it but the journey has been well worth it.
Were you prepared to work on it or did you learn as the project progressed? As a first-year student, I definitely didn’t know much when I started. Learning on the go became the norm. I understood some things by taking relevant CS classes and through reading Medium blogs and GitHub repositories –– this ability to learn independently might be one of the most valuable skills I have gained. I am very fortunate that Dr. Tatonetti guided me through this process and invested his time in developing my knowledge.
What were the things you already knew and what were the things you had to learn while working on the project? While I was familiar with biology and mathematics, computer science was totally new! In fact, T-Lab launched my journey to exploring computer science. This project exposed me to the great potential of artificial intelligence (AI) for revolutionizing healthcare, which in turn inspired me to explore the discipline academically. I went back and forth between taking classes relevant to my research and applying what I learned in class to my research. As I took increasingly technical classes like ML and probabilistic modelling, I was able to advance my abilities.
Looking back, what were the skills that you wished you had before the project? Having some experience with implementing real-world machine learning projects on giant datasets with millions of observations would have been very valuable.
Was this your first project to collaborate on? How was it? This was my first project and I worked under the guidance of Dr. Tatonetti. I thought it was a wonderful experience – not only has it been extremely rewarding to see my work come to fruition, but the journey itself has been so valuable. And Dr. Tatonetti has been the best mentor that I could have asked for!
Did working on this project make you change your research interests? I actually started off as pre-med. I was fascinated by the idea that “intelligent machines” could be used to improve medicine, and so I joined T-Lab. Over time, I’ve realized that recent advances in machine learning could redefine how doctors interact with their patients. These technologies have an incredible potential to assist with diagnosis, identify medical errors, and even recommend treatments. My perspective on how I could contribute to healthcare shifted completely, and I decided that bioinformatics has more potential to change the practice of medicine than a single doctor will ever have. This is why I’m now hoping to pursue a PhD in Biomedical Informatics.
Do you think your skills were enhanced by working on the project? Both my knowledge of ML and statistics and my ability to implement my ideas have grown immensely as a result of working on this project. Also, I failed about seven times over two years. We were designing the algorithm and it was an iterative process – the initial versions of the algorithm had many flaws and we started from scratch multiple times. The entire process required a lot of patience and persistence since it took over 2 years! So, I guess it has taught me immense patience and persistence.
Why did you decide to intern at the T-Lab? I was curious to learn more about the intersection of artificial intelligence and healthcare. I’m endlessly fascinated by the idea of improving the standards of healthcare by using machine learning models to assist doctors.
Would you recommend volunteering or seeking projects out to other students? Absolutely. I think everyone should explore research. We have incredible labs here at Columbia with the world’s best minds leading them. Research opens the doors to work closely with them. It creates an environment for students to learn about a niche discipline and to apply the knowledge they gain in class.
Professor Kathy McKeown talks with DeepLearning.AI’s Andrew Ng about how she started in artificial intelligence (AI), her research projects, how her understanding of AI has changed through the decades, and AI career advice for learners of NLP.
Fellows from the department were among the participants of the prestigious conference where laureates of mathematics and computer science meet the next generation of young researchers.
This year’s event, although virtual, still presented itself as an opportunity to learn new things and network for the fellows – alum Oded Stein (PhD ’20) and PhD students Ireti Akinola and Ana-Andreea Stoica. Below they share what they enjoyed most and how they look forward to attending the event in person after the pandemic.
I was excited to learn that Donald Knuth and Yoshua Bengio were among the Turing laureates that will be participating at this year’s conference. It was interesting to hear them talk about their careers. While they shared some thoughts on their specific paths, they were quick to point out that the world is a lot different now compared to when they started. What was evident with their talks was that they tried to work on problems that they found interesting.
In other sessions, speakers highly recommended multi-disciplinary collaborations to help advance impactful modern research. I also learned a bit more about health care and disease management, which is the main theme of the event. This was quite timely as the pandemic has made this time a defining moment in healthcare.
Science communication came up a lot throughout the course of the forum. As young researchers, speakers recommended writing as much as you can – writing ideas down, both in prose and equations, helps with clarity.
The Heidelberg forum was a good mix of learning from very accomplished academics and meeting other students. With all the difficulties that an online event presents, I appreciated that the organizers took many questions and feedback from participants, and the talks felt more like a lively discussion.
I liked hearing from prominent researchers like Karen Uhlenbeck and Don Knuth not only about their work, but also about their research process, interests, and a bit about their life story of how they got engaged with their field. Other than that, the forum presented several interesting discussions about current topics, such as using big data in healthcare, or the potential dangers of artificial intelligence, which connected some of the more theoretical foundations to application domains and ethical considerations.
The forum had a lively online platform that simulated real-life interaction and facilitated a poster session where people could mingle and learn from each other — which I think is really needed for any online event!
I learned about the forum from my advisor, Augustin Chaintreau, and was excited to see in the program many amazing researchers on fields related to mine. While I enjoyed the forum this year, I’m sure the in-person experience will be very different. I’m looking forward to participating (hopefully!) in person next year.
I really enjoyed attending the virtual forum. It was quite an experience to hear talks by some of the most esteemed people in mathematics and computer science. I was very inspired by hearing their stories and it was great that they answered many audience questions during the sessions.
There was also a virtual meeting room for a poster session, which provided social interactions between the attendees which I appreciated since we were all meeting virtually.
One specific thing I learned from the lab tours is that doing astronomy is very labor-intensive! The researchers hike far away to get to the telescopes, live in cramped living conditions to operate the machinery, and there is also the constant danger from forest fires.
I think it was a good experience, but it would have been even better if it was in-person. I’m looking forward to attending the event when the public health situation makes an in-person meeting possible.
On October 28, students, faculty, alumni, families, and friends—from across Columbia and around the world—come together to give back to Columbia Engineering on Giving Day. Together, we invest in the future of our department, our school, and our shared commitment to intellectual excellence and bringing this excellence to the service of humanity. This year on Giving Day you can give back directly to the Computer Science department!
P.S. For our students – be a part of the action by following our progress and amplifying the message via social media!
For the COVID-19 Hub, CRAC was asked to join a team along with CUIT and senior leadership across every campus to create a user-populated resource for COVID-related projects. The idea is that students and researchers alike can browse or search COVID-related projects and make connections with colleagues whose work and interest mirror their own.
Below, Mackenzie talks about volunteering and how it was working on the Project 8 COVID-19 Hub.
Matt Mackenzie
Why did you decide to volunteer? Being someone who is not fluent in anything biology, I didn’t think there was any way I could contribute to the fight against COVID. When I heard about a more IT-centric project, I thought I could be useful, and do my small part to help.
Were you actively looking for a project to work on or was your interest because the project was COVID-related? I was interested because of the COVID-related nature of the project. I had never worked on a research project before, and always wanted to, but being in the middle of the semester I was not actively looking for any more work!
How was it working on the project? What did you do? The project went from April to June. On average, I worked maybe 4 hours a week. But some days were very light, and some required many hours of work. The largest portion of my work was writing Python code to clean incoming data, which is something I was very comfortable with.
What were the things you already knew and what were the things you had to learn while working on the project? Python was our main tool for automation, and I have been using that for years. We were all responsible for knowing the structure of the data since sometimes we needed to populate missing fields or manually clean data, so learning the structure was also necessary. At one point we categorized some of the project data we were working with, and that required learning more about the projects themselves.
We used Qualtrics to collect survey data, knowing a little more about that would have been nice.
Was this your first project to collaborate on? How was it? This was my first project. I thought it was very interesting to see how rapidly things were accomplished, and how a vast network of individuals from all different backgrounds could work together so seamlessly.
While I was only a part of Project 8, the entire CRAC organization shared a Slack workspace, and watching the high level of intellectualism and professionalism in the conversations all across the organization was really inspiring to continue with research and education.
Do you think your skills were enhanced or improved by working on the project? Yes. While my Python skills maybe got a little bit of practice, I think my soft skills benefitted the most, as we had to work together and communicate electronically with each other.
I don’t see myself pursuing biology, but working on this project definitely has made me want to get involved with more research opportunities.
Would you recommend volunteering or seeking projects out to other students? Absolutely! The COVID-19 pandemic is obviously still on-going and will remain a problem for the foreseeable future. If you have the skills or passion to help in any way, I encourage everyone to do so. Not only is it a great learning experience, but you get to have a truly positive impact on society.
Dean Boyce's statement on amicus brief filed by President Bollinger
President Bollinger announced that Columbia University along with many other academic institutions (sixteen, including all Ivy League universities) filed an amicus brief in the U.S. District Court for the Eastern District of New York challenging the Executive Order regarding immigrants from seven designated countries and refugees. Among other things, the brief asserts that “safety and security concerns can be addressed in a manner that is consistent with the values America has always stood for, including the free flow of ideas and people across borders and the welcoming of immigrants to our universities.”
This recent action provides a moment for us to collectively reflect on our community within Columbia Engineering and the importance of our commitment to maintaining an open and welcoming community for all students, faculty, researchers and administrative staff. As a School of Engineering and Applied Science, we are fortunate to attract students and faculty from diverse backgrounds, from across the country, and from around the world. It is a great benefit to be able to gather engineers and scientists of so many different perspectives and talents – all with a commitment to learning, a focus on pushing the frontiers of knowledge and discovery, and with a passion for translating our work to impact humanity.
I am proud of our community, and wish to take this opportunity to reinforce our collective commitment to maintaining an open and collegial environment. We are fortunate to have the privilege to learn from one another, and to study, work, and live together in such a dynamic and vibrant place as Columbia.
Sincerely,
Mary C. Boyce
Dean of Engineering
Morris A. and Alma Schapiro Professor
I was excited to learn that 
The Heidelberg forum was a good mix of learning from very accomplished academics and meeting other students. With all the difficulties that an online event presents, I appreciated that the organizers took many questions and feedback from participants, and the talks felt more like a lively discussion.
I really enjoyed attending the virtual forum. It was quite an experience to hear talks by some of the most esteemed people in mathematics and computer science. I was very inspired by hearing their stories and it was great that they answered many audience questions during the sessions.
On October 28, students, faculty, alumni, families, and friends—from across Columbia and around the world—come together to give back to Columbia Engineering on 
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