TEAM

Associate Vice President for Research

Cardiss Collins Professor of Mechanical Engineering

Professor of Civil and Environmental Engineering (by courtesy)
Professor of Materials Science and Engineering (by courtesy)
Professor of Industrial Engineering and Management Sciences (by courtesy)

Director, Northwestern Initiative for Manufacturing Science and Innovation (NIMSI)

Research Interests: Innovative manufacturing processes and systems, particularly in the areas of deformation-based processes and laser processes

Postdoctoral Scholars

Xiaoxiao (Catherine) Ding

xding@northwestern.edu

Research Interests:
1. Multiscale Mechanics
2. Mechanical Metamaterials
3. Integrated Design and Manufacturing

Deepak Sharma

deepak.sharma@northwestern.edu

Research Interests:
1. Computational Mechanics
2. Damage Mechanics
3. Fatigue Life Modeling
4. Machine Learning

PhD Students

Vasudev Aravind

vasudevaravind2022
@u.northwestern.edu

Research Interests:
1. Directed Energy Deposition – Additive Manufacturing
2. Functionally Graded Materials

Fred Carter

Fredcarter2024
@u.northwestern.edu

Research Interests:
1. Additive Manufacturing
(a) Laser Powder Bed Fusion (PBF)
(b) Laser Directed Energy Deposition (DED)
2. CFD simulation for Additive Manufacturing Processes
3. Machine Learning for Additive Manufacturing

Jin Choi

jinchoi2024@u.northwestern.edu

Research Interests:
1. Additive manufacturing

Fanglei Hu

fangleihu2021@u.northwestern.edu

Putong Kang

putongkang
@u.northwestern.edu

Research Interests:
1. Laser-Induced Plasma Micromachining
2. Additive Manufacturing

Garrett Mathesen

garrettmathesen2023
@u.northwestern.edu

Nhung Nguyen

nhungnguyen2022
@u.northwestern.edu

Interests:
1. Additive Manufacturing, Microstructure Evolution

Conor Porter

conorporter2024
@u.northwestern.edu

Research Interests:
1. Laser Powder Bed Fusion
2. Directed Energy Deposition

Dani Quispe

daniel.quispe@northwestern.edu

Research Interests:
1. Generative design to discover advanced manufacturing processes.
2. Machine learning-based simulations for predicting material response after a manufacturing process