About the Lab

We are a computational chemistry group at Cornell University. Our focus is computational analytical chemistry: designing and understanding how algorithms give quantitative predictions in chemistry. Currently, our research centers on three areas:

Recovering Protein Heterogeneity from Cryo-EM. Proteins are fundamental to the molecular machinery of life. Many proteins are highly conformationally heterogeneous, switching between structures to achieve their goals. We attempt to build algorithms that can recover these changes in structure from cryogenic electron microscopy experiments.
Heterogeneity in In-Situ EM Recently, in-situ electron microscope techniques have enabled materials to be imaged while they are undergoing meaningful chemical reaction. Moreover, combining in-situ experiments with advanced electron microscopy techniques such as 4D-STEM or EELS provide rich data about how material composition changes over time. However, the resulting data is often very noisy. We develop new algorithms for analyzing in-situ EM experiments that can function with noisy data, giving reliable insights in the face of statistical uncertainty.
Manipulating Protein Language Models Protein language models apply the same technology that powers natural language models such as ChatGPT, Claude, and DeepSeek to the sequence of amino acids that make up a protein. We are exploring the capabilities of these models for zero-shot and few-shot prediction of protein properties. In addition, we are attempting to close the loop between protein language model and experimental peptide design, allowing for rapid and efficient iterations on peptide drug candidates.

Lab Values

We are curious. Science is about learning, not knowing. We are always looking for new ways of thinking, and are comfortable showing that we don't understand everything.
We are open. Science is a team sport. To help out teammates, we take pains to share our science freely amongst the scientific community and with the world.
We are caring. Doing good science requires delving deep into the unknown: an experience both exciting, and terrifying. On our journey, we celebrate each other's achievements and support each other through setbacks.
We are inclusive. We actively strive to make science a place where everyone thrives, no matter their background and identity. We resist oppression of any kind, including but not limited to sexism, classism, racism, homophobia, transphobia, ableism and xenophobia. Everyone is welcome and celebrated here.

People

Erik Henning Thiede

Erik is a Professor of Chemistry at Cornell University. He received his PhD from the University of Chicago working with Profs. Aaron Dinner and Jonathan Weare. He then did a postdoc at the Flatiron Institute CCM, working with Prof. Risi Kondor, Dr. Pilar Cossio, and Dr. Sonya Hanson.

Personal Webpage.

Jake Moomaw

Jake is a moonshot enthusiast who has worn many hats: algorithms researcher, amateur chemist, software engineer, roboticist, vulnerability researcher and electronics hobbyist. He is currently in the lab as a joint undergraduate researcher and part-time software developer.

Joshua Rhodes

Joshua is a graduate student in the Cornell Chemistry Department. His work focuses on developing new probabilistic machine learning algorithms for cryo-EM data.

Diego Sanchez Espinoza

Diego is a graduate student in the Cornell Center for Applied Math, jointly advised by Prof. Yunan Yang. His work focuses on applying Wasserstein flows to the analysis of cryo-EM data.

Kawamura

Kawamura is a graduate student in the Cornell Biophysics program. She works on expanding the limits of cryo-EM to work on protein disordered regions.

Wenzhe Chen

Wenzhe Chen is a graduate student joint with Hening Lin at the University of Chicago. He works on finetuning and repurposing structure prediction tools to better match experimental data.

Kwanghwi Je

Kwanghwi Je is a postdoctoral researcher. He earned his doctorate from the University of Michigan. His expertise lies in using molecular simulation techniques to investigate biomolecular dynamics and phase behavior of colloidal nanoparticles. Beyond the lab, he enjoys running and exploring new places.

Yafet Nagesh

Yafet is a sophomore at Cornell University. He is working on developing algorithms to analyze cryo-EM images of nanoparticles.

Emily Almgren

Emily is a graduate student in Cornell's Center for Applied Math. She is working jointly with Prof. Anil Damle on developing faster algorithms for analyzing large EM datasets.

Joshua Almonte

Joshua is a graduate student in Cornell's Chemical Engineering program. Working together with Profs. Chris Alabi and Alexander Terenin, he is exploring more efficient algorithms for designing peptides.

Triet Minh Vu

Triet is a graduate student in the Cornell Chemistry Department working jointly with our group and Yao Yang's group. Triet is developing new representation learning algorithms for analyzing operando EM movies.

Zora Zhang

Zora is a graduate student in the Cornell Chemistry Department working jointly with our group and Yao Yang's group. Her research combines operando electron microscopy with computational analysis and machine learning.

Andrew Ahn

Guanzhong (Alain) Wang

Alain is a sophomore at Cornell. He is investigating how different probabilistic metrics affect the ensemble of structures we recover from cryo-EM experiments.

Alumni

Jeffrey Xiang Working at Amazon.

Hailey Foster Undergraduate Researcher in the Craine Lab.

The Thiede Lab

@ Cornell