Frequently Asked Questions
I am a strong advocate for transparency and equitable access to resources. Here are some of my most frequently asked questions. I have organized them by topic. Please expand the questions and sub-questions for detailed answers.
What PhD program were you in?
I received my PhD in Biomedical Informatics from Harvard Medical School. When I entered the program, it was called Bioinformatics and Integrative Genomics (BIG). In 2023, it became one of the two “tracks” in the Biomedical Informatics PhD program. The other track is called Artificial Intelligence in Medicine (AIM). For the most up-to-date information about the program/tracks, please visit their websites.
What courses did you take?
Fall 2019: BMIF 201 (Concepts in Genome Analysis; Required), GENETIC 201 (Principles of Genetics; Required), and BCMP 200 (Principles of Molecular Biology; Required).
Spring 2020: BIOPHYS 205 (Computational and Functional Genomics; Required), MATH 243 (Evolutionary Dynamics; Elective), and GENETIC 302QC (Teaching 101: Bringing Effective Teaching Practices to Your Classroom; Elective).
Fall 2020: MED-SCI 300QC (Conduct of Science; Required), IMMUN 307QC (Cancer Immunology; Elective), and CELLBIO 306QC (Teaching 100: The Theory and Science of Teaching; Elective).
Spring 2021: BCMP 301QC (Translational Pharmacology: The Science of Therapeutic Development; Elective) and COMPSCI 288 (AI for Social Impact; Elective).
Last updated: June 25, 2024
What were your criteria for picking a PhD advisor and lab?
Let me begin by stating that each individual has their own preferences. I encourage you to think deeply about your preferred mentoring style, career goals, etc.
Here are my top 5 criteria (ordered by importance):
- Funding. You should never be stressed about whether or not you and your projects have enough funding (or may lose funding). Student fellowships should be “nice-to-have” but not required.
- Mentorship. Advisors can truly “make” or “break” your PhD experience. Take your time to carefully select the right PhD advisor for you. Your advisor should satisfy most, if not all, of your preferences for mentorship style (as well as the lifestyle that you want to lead during your PhD). One important aspect that most people (including PhD students, postdocs, and research assistants) do not ask about is how advisors advocate for their trainees (e.g., how do they negotiate authorship, handle conflicts with collaborators, discuss thesis progress with committee members, consider their trainees for opportunities, etc).
- Research area & advisor expertise. You and your advisor should be aligned in your research interests. Ideally, your advisor should have expertise in the area(s) that you would like to grow. For example, if you want to innovate machine learning algorithms, you may benefit from an advisor with a strong background in machine learning. Or, if you want to make a significant impact in clinical medicine, you may benefit from an advisor who is a clinician and/or works closely with patients, clinical researchers, and clinicians.
- Lab culture. It is important that your advisor is not the only person whom you can talk to about your research. A PhD journey can feel isolating, even with the strongest support network. Make sure that you feel comfortable asking for advice from postdocs, graduate students, etc in the lab.
- Access to data & compute. One of the “disadvantages” of a dry lab is not being equipped to generate data in-house. Ask your advisor where they get their data from (and how do they negotiate issues with collaborators; see “Mentorship”): public databases, wet lab collaborators, clinical collaborators, industry collaborators, etc. Another important resource for dry labs is compute (e.g., GPUs). Ask your advisor about the lab’s access to compute.
Last updated: June 26, 2024
How did you pick your rotations and PhD advisor?
To select my PhD advisor, I rotated through three research groups: Prof. Michael Baym (September to December 2019), Prof. Isaac (“Zak”) Kohane (January to June 2020), and Prof. Marinka Zitnik (June to August 2020). I chose to be co-advised by Marinka and Zak. Since my PhD program did not allow formal co-advising, I was primarily advised by Marinka “on paper” and unofficially co-advised by Zak. Practically, this meant that Marinka was administratively and financially responsible for me throughout my PhD, and I was a full member of both Marinka’s and Zak’s labs.
Why did you rotate with Prof. Michael Baym?
My undergraduate research was focused on experimental and computational techniques to detect antibiotic resistance in bacterial isolates and clinical samples. I was an admirer of Michael’s research; in fact, we applied our algorithm, MGEFinder, on data from Michael’s mega-plate experiments to identify mobile genetic elements (MGEs) that may have contributed to the acquisition of antibiotic resistance.
After interviewing with Michael (during my BIG interview weekend), I knew instantly that I wanted to at least rotate with him. At the time, I was curious about bacteriophages as a potential therapeutic to treat antibiotic-resistant strains and/or slow down the antibiotic resistance crisis. He seemed to be (and indeed was!) the perfect person at Harvard Medical School to explore this idea with.
Why did you rotate with Prof. Isaac (“Zak”) Kohane?
Based on my undergraduate research experience in developing computational tools to diagnose diseases (e.g., sepsis), I was curious and motivated by the unique challenges of diagnosing rare genetic diseases. Zak’s lab focuses on innovating algorithms to address these challenges.
At the time, two graduate students, Sam Finlayson and Emily Alsentzer, were working towards building a simulation pipeline to simulate realistic patients with rare genetic diseases and a deep learning algorithm to learn knowledge-infused patient subgraph representations. I contributed to both of these projects during my rotation. After I joined the lab, Emily and I co-led the development of a deep learning algorithm for multi-faceted rare disease diagnosis.
Why did you rotate with Prof. Marinka Zitnik?
A key overarching objective of my research is to design safe, effective, and affordable therapies. I was inspired by Marinka’s postdoctoral research at Stanford, so I was ecstatic about her joining our department in December 2019.
Coincidentally, two graduate students from Zak’s lab, Sam and Emily, were planning to start a project with Marinka to develop a deep learning algorithm for learning knowledge-infused patient subgraph representations. As a result, I was able to simulate a co-advising setup between Marinka and Zak during my second rotation. I knew very quickly that this co-advising relationship was perfect for me; however, I was not sure whether to be primarily advised by Marinka or Zak (my PhD program did not allow formal co-advising). To help me make my decision, I rotated with only Marinka. During this period, I started working on a project that became a contextual AI model for single-cell protein biology.
How did you make your decisions about which lab to join?
First of all, these three professors are excellent mentors. I strongly recommend working with any and all of them.
Why did you not join the Baym lab? I thoroughly enjoyed my rotation with Michael. He (with the help of his trainees) fosters a welcoming and collaborative lab culture. Michael encourages curiosity, independence, and exploration. I did not join his lab mainly because I wanted to venture outside of my comfort zone and become an expert in a completely new field of research. If I wanted to continue studying antibiotic resistance, Michael would have been an excellent mentor.
Why did you decide to be co-advised by Marinka and Zak? I chose to be primarily advised by Marinka and unofficially co-advised by Zak. Since Marinka was a junior faculty member, she was able to be very hands-on and give concrete technical advice (e.g., debugging models). Zak, as our department chair, was more experienced with big-picture planning, both in terms of papers and career development. Also, because Marinka was new to the department and her position, there were no other lab members to seek guidance from (I was her first PhD student!). So, during the first half of my PhD, I was fortunate to be supported by the graduate students and postdocs in Zak’s lab. Due to the nature of the lab’s interdisciplinary research and Zak’s background (MD/PhD), lab meetings are regularly attended by clinicians, computer scientists, computational biologists, etc. This has been immensely beneficial to my PhD and postdoctoral training. Eventually, as Marinka’s lab grew, I helped cultivate a welcoming, supportive, and fun-loving lab culture.
Why was your second rotation much longer than the other two?
PhD students in my program typically rotate in a lab for about 14 weeks. Due to the disruptions caused by COVID-19, namely the lockdowns that interrupted research activities, I extended my rotation with Zak.
Last updated: June 26, 2024
If you have a question that is not yet answered, please do not hesitate to reach out!