Upcoming Events & Seminars
Fall 2025 Schedule
Welcome! Explore this fall’s exciting presentations featuring Duke students, postdocs, and guest speakers from outside Duke.
If you have any questions, please contact Amy Chung (hong.chung@duke.edu) or Meg Taylor (meg.taylor@duke.edu).
| Date | Presenter 1 | Presenter 2 / Host |
| September 12, 2025 | Coban Brooks (Romero lab): Synthetic evolution of enzyme specificity with a self-driving lab | Brian Lerner (Tim Dunn Lab): Using Deep Learning to Improve Prognosis of Traumatic Brain Injury |
| September 19, 2025 | Anita Silver (Big Ideas lab): Identifying gut microbial links to cardiorespiratory fitness in humans | Minji Jang, PhD (Tim Dunn Lab): Quantitative Approaches to Neural and Behavioral Mechanisms in Animal Models: Neurophysiological Change in Autism Spectrum Disorder |
| September 26, 2025 | Pablo Cordero Alvarado (Segura & Collier Lab): Engaging the systemic and local immune system for the treatment of chronic tissue healing via anti-cytokine immunotherapies | Sophia Colmenares (Reker Lab): Investigating Metabolic Cytochrome Drug Inhibition with Pairwise Machine Learning |
| October 3, 2025 | Gabe Rocklin, PhD (Northwestern University) | Faculty Host: Phil Romero, PhD |
| October 10, 2025 | Rebeca Stipel, PhD (Reker Lab): Precisely Silencing Genes with Machine Learning-Guided Development of siRNA Nanoparticles | Hayoung Jeong (Big Ideas lab): Characterizing Patterns of Missingnesss in Wearable Data |
| October 17, 2025 | Owen Fenton, PhD (UNC) | Faculty Host: Daniel Reker, PhD |
| October 24, 2025 | Kaichun Yang (Tony Huang lab): Precision acoustofluidics for life science | Yasha Saxena (Segura Lab): Title TBD |
| October 31, 2025 | Hrshita Gowda (Reker Lab): Machine learning guided prediction of drug effects on the microbiome | Nathaniel Blalock (Romero lab): Machine learning-guided olivetolic acid cyclase engineering enables tailored cannabinoid biosynthesis in yeast |
| November 7, 2025 | David Karig, PhD (Clemson University) | Faculty Host: Lingchong You, PhD |
| November 14, 2025 | Brian Shoichet, PhD (UCSF) | Faculty Host: Daniel Reker, PhD |
| November 21, 2025 | Arthur Prindle, PhD (Northwestern University) | Faculty Host: Lingchong You, PhD |
Student- & Postdoc-Focused Works-In-Progress Meetings on AI/Automation in Biodesign
Spring 2025 Schedule
Welcome! Are you a grad student/postdoc looking to share your work to the Center for Quantitative BioDesign community? We would love to hear about your work in progress! Please plan on giving a ~20-minute talk + 10 minutes for Q&A, and we’ll provide pizza and drinks
Preferences to presentation dates will be given on a first come-first serve basis! If you have any questions, please contact Lauren Hong (lauren.hong@duke.edu) or Max Golovsky (maximillian.golovsky@duke.edu).
| Date | Presenters |
| Jan 17, 2025 | Presenter 1: Erin Ostrem, PhD – (Venturelli Lab): Dietary Fiber and Host-Derived Glycans Shape Butyrate Production through Modulation of Interspecies Interactions
Presenter 2: Zachary A. Holmes – (You Lab): A foundation model for microbial growth dynamics |
| Jan 24, 2025 | Presenter 1: Benjamin Perry – (Romero Lab): Towards New-to-Nature Enzyme Design: a Learned Joint Representation of Reaction-Sequence Space
Presenter 2: Katie Duncker – (You Lab): Engineering microbial consortia as distributed environmental sentinels |
| Jan 31, 2025 | Presenter 1: Utsuki Yano – (Lynch Lab): Title TBD
Presenter 2: Fred Peng – (Chatterjee Lab): EvoFlow: Generating and Representing Proteins with Language Model Learned from Evolution |
| Feb 7, 2025 | Presenter 1: Shrey Goel – (Chatterjee Lab): MeMDLM: De Novo Membrane Protein Design with Masked Discrete Diffusion Protein Language Models
Presenter 2: Zachary Quinn – (Chatterjee Lab): PepMLM: Target Sequence-Conditioned Generation of Therapeutic Peptide Binders via Masked Language Modeling |
| Feb 28, 2025 | Presenter 1: Yan Xiang, PhD – Reker Lab: Drug-Excipient Nanoparticle Design Using Yoked Deep Learning Molecular Simulation
Presenter 2: Amy Chung – Reker Lab: Profiling microbiome metabolites via machine learning
|
| Mar 28, 2025 | Presenter 1: Xiaoli Chen, PhD – You Lab: Engineering dual-barcoded populations for quantification of microbiome dynamics
Presenter 2: Ryan Boileau – Chory Lab: Massively multiplexed and parallel structure-function assays using automation |
April 11, 2025-
Presenter 1: Dongheon Lee, PhD – You Lab: Control of Intracellular Biochemical Reactions through Biomolecular Phase Separation
Presenter 2: Vita Zhang – Gladfelter Lab: Designing Synonymous RNAs with Temperature-Sensitive Physical Properties
April 25, 2025-
Presenter 1: Pak Lun Kevin Cheung – Venturelli Lab: System Identification for Microbial Communities Dynamical Systems
Presenter 2: Coban Brooks – Romero Lab: Automating the process of scientific discovery for protein engineering
Spring 2025 CQB Seminar Schedule
Time: 3:00 – 4:00 pm
Day of the Week: Friday (s)
Place: Wilkinson Auditorium 021
| Date | Course | Speaker | Institution | Faculty Host | Presentation Title |
|---|---|---|---|---|---|
| Feb 14, 2025 | CQB
seminar |
Maria Brbic, Ph.D. | EPFL Institute of Bioengineering | John Hickey, PhD | Generative AI for Unlocking the Complexity of Cells |
| Feb 21, 2025 | CQB seminar | Shriya Srinivasan, Ph.D. | Harvard University | Daniel Reker, PhD | Unlocking the Gut’s Brain with Ingestible Bioelectronics |
| Mar 7, 2025 | CQB seminar | Rodrigo Reyes, Ph.D. | McGill University | Lingchong You, Phd | Single-Molecule Tracking of DNA-Binding Proteins: Insights into Cellular Function and Genome Maintenance |
| Mar 21, 2025 | CQB seminar | Ron Dror, Ph.D | Stanford University | Daniel Reker, PhD | Discovering Safe, Effective Drugs via Machine Learning and Simulation of 3D Structure |
| Apr 4, 2025 | CQB
seminar (postponed) |
Declan P O’Regan, Ph.D. | Laboratory of Medical Sciences (MRC) | Postponed to Fall 2025 or Spring 2026 | Postponed to Fall 2025 or Spring 2026 |
| Apr 18, 2025 | CQB seminar | Li Bowen, Ph.D. | University of Toronto | Daniel Reker, PhD | AI-Driven Design of Lipid Nanoparticles for mRNA Delivery |
