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Anika Gupta

SB, Massachusetts Institute of Technology, Computer Science and Biology

Algebra, Biology, Calculus, Chemistry, College Consulting, Computer Science, Statistics

Anika graduated from MIT in 2018, where she studied Computer Science and Biology and developed not only her passion for data-driven biomedical innovation, but also her passion for teaching and a deep appreciation for the pedagogical power of interdisciplinary study. The first rule of mastering material, according to Anika, is to enjoy it. As such, a cornerstone of her tutoring philosophy is to engage students by approaching subjects through the perspectives of their passions. Beyond tapping into students’ motivations for learning, a pedagogy built upon interconnectedness teaches students to synthesize knowledge in ways that can often unlock novel frameworks of thinking and problem-solving. A tutor for over seven years, Anika has brought this approach to students of all ages and at all levels of mastery, from leading workshops for young girls interested in STEM to, more recently, TAing machine learning courses for medical and masters students and serving as a Resident Tutor for Harvard College students. To Anika, the most satisfying student outcomes of all are those in which intellectual engagement fosters newfound confidence—in which students transform from hesitant learners at the back of the class to leaders of their peers—whether in middle school, high school, college, or graduate school.

Now a PhD candidate in Bioinformatics at Harvard University, Anika is herself a student at the intersection of many fields, studying the genomics of cellular identity through statistics, computation, and truly massive datasets. Using the natural variation that exists in gene transcription, she hopes to identify cause-and-effect relationships between genes that can guide the development of more precise medicines. A one-shy student herself who was afraid to ask questions in class, she now centers her academic career on bold questions: What genetic malfunctions underpin disease? What genetic interventions can address them?