Natasha Seelam

Natasha Seelam

PhD Candidate

Massachusetts Institute of Technology (MIT)

Biography

This page is under construction (2020.07.08)

I’m finishing my PhD in Chemical Engineering at MIT in CSAIL. My research focuses on analytical and computational approaches to understand how proteins facilitate virtually impossible reactions at ambient conditions. During my doctorate, I studied how several enzymes catalyze reactions through an atomistic perspective using molecular dynamics coupled with quantum chemistry (QM/MM). From these simulations, we’ve created predictive models capable of identifying both the structural features most indicative of successful reactions, and the electronic underpinnings of such methods.

In addition to my doctoral work, I work on several side projects in the space of vision, language, and game design. Please feel free to drop a note if you’d like to chat!

Interests

  • Computational Enzymology
  • Structural Biology
  • Machine learning
  • Computational Linguistics
  • Interpretability

Education

  • PhD in Chemical Engineering, 2020 (Expected)

    Massachusetts Institute of Technology

  • BS in Chemical and Biomolecular Engineering, 2013

    Johns Hopkins University

Research

Capturing the free-energy of protein-facilitated reactivity

Using umbrella-sampling methods to sample rare configurations, we uncover reaction landscapes of how proteins facilitate chemistry to uncover novel insight into mechanisms.

Dynamics in enzyme catalysis

Every atom in a protein is subject to forces that allow them to move. Leveraging path-sampling algorithms, we explore how proteins employ dynamics in order to cross reaction barriers, and how this gives rise to reactivity.

Electronic underpinnings of protein catalysis

Structural features of a protein can be highly predictive of successful reactions. In the following work, we explore how geometry of the active-site relates to quantitated electronic mechanism in an enzyme.

Projects

Winning strategies for 2048

There seem to be certain heuristic strategies people suggest for winning the game 2048. I wanted to explore why these policies work with reinforcement learning

Mentorship

Division of Student Life (Burton Conner B1)

Graduate Resident Assistant (GRA)

2016-2020

I lived with some of the brightest, best students at MIT and had the privilege of being their GRA. The duties of a GRA encompass interpersonal conflict to academic stress. I take deep pride in being part of this community.

Resources for Easing Stress and Friction (REFS-X)

Co-founder, REF

2015-

I co-founded a group in my department to handle academic stressors. Every REF takes a 40 hour professionally certified conflict-management and mediation training. The group website is here.

10.40 Graduate Thermodynamics, MIT ChemE

Teaching Assistant

2017

I had the pleasure of teaching ChemE’s graduate thermo (focused on stat mech) to over 50 first year grad students. As written qualifiers have been since removed, the first year graduate coursework is critical. I created exams and lesson plans including several simulation based variants (computational Ising Models). My work was awarded the Institute Graduate Teaching Award for the School of Engineering in 2017.

UROP and Graduate Research Mentor

Mentor

2015-2019

I have trained 5 undergrads and 3 graduate students at my home institution in various enzymology and quantum chemistry related projects. Such projects included transition-state identification for KARI, and machine-learning feature selection for enzymatic drivers of reactivity.

Contact