Research staff

Nicola Molinari

Nicola earned a BS and a MS in Physics from the University of Padova (where people of the caliber of Galileo once taught!) in 2013, and spent a year in the UK as part of the ERASMUS scholarship program. He then was awarded a scholarship in the EPSRC Centre for Doctoral Training on Theory and Simulation of Materials at Imperial College London, where he earned a MSc and a PhD in Physics. Nicola joined the MIR lab at its very origin as a Postdoctoral Fellow. Currently he is a research engineer at Bosch, USA and a visiting associate at MIR lab. His research interests are at the interface between computational condensed matter physics and materials science, and include ionic transport and energy storage, membrane permeation, and mechanical properties of polymers. Among others, he has received the Materials Design Research Prize, the Johnson-Matthey Prize for the Best PhD, and the Blackett Laboratory Industry Club Thesis Prize. Outside the academic walls, his interests include, but are not limited to, cooking, chess, triathlon, and hiking.

Julia Yang

Julia is from the well-defined region of central New Jersey and earned her B.S. in Materials Science and Engineering (MSE), with an additional major in Physics, from Carnegie Mellon University in 2016. She is a computational materials scientist, having studied density functional theory approximations applied to crystal structure prediction, phase stability and electrochemical performance of disordered electrodes, and the theory and application of the cluster expansion method applied to ionic systems. She earned her Ph.D. in MSE from University of California, Berkeley in 2022 while supported by the National Defense Science and Engineering Graduate Fellowship (2016-2019), and joined MIR as a HUCE Fellow to study the solvation thermodynamics and transport of charged species in non-aqueous liquids for applications in battery recycling, among others. She likes running, volleyball, wine, Berkeley Bowl, and finding new ways to lower her carbon footprint.

Jingxuan Ding

Jingxuan joined MIR in 2022 as a SEAS Fellow to study the Li ion transport and the interfacial reactions in solid state lithium battery. He is also interested in lattice dynamics and thermal transport in thermoelectric (TE) materials. He got his B.S. (2014) and M.S. (2016) in Materials Science and Engineering from Tsinghua University, China, where he did synthesis, characterization and DFT simulations of TE materials. He earned his Ph.D. in Mechanical Engineering and Materials Science from Duke University in 2022, studying atomic dynamics in TE and solid state electrolyte materials via neutron/x-ray scattering and computational modeling. Food and games are his favorite things. He wants to stay indoors, but his dog Cola (Lab & Pitbull mix) forces him to do outdoor activities like running and hiking. He is originally from Beijing, China. 

Zachary Goodwin

Zac earned his MSci in Chemistry with Molecular Physics from Imperial College London (ICL) in 2017. He continued on at ICL in the Theory and Simulation of Materials Centre for Doctoral Training, where he obtained an MSc in Physics (2018) and his PhD in Materials Science (2022). His research interests include theory and simulation of concentrated electrolytes, in the bulk and at electrified interfaces, with a particular focus on the role of ionic aggregation and solvation; strong electron interactions and broken symmetry phases in 2D moiré materials, which was the focus of his PhD and first postdoctoral position in the National Graphene Institute at the University of Manchester; and DFT calculations of charged molecules/defects interacting with graphene multilayers. Zac joined the MIR group in 2022 as a Postdoctoral Fellow to perform large scale atomistic simulations, using the methods developed within the group to obtain accurate and data efficient machine learned interatomic potentials, on various systems in the area of energy materials, such as polymer electrolytes for batteries and barocaloric materials. In his spare time, he enjoys cycling, bouldering, hiking, skiing, and making pasta.

Stefano Falletta

Stefano holds a double master’s degree in Physics of Complex Systems from Politecnico di Torino and Université Paris Sud, a master’s degree in Mathematical Engineering from Politecnico di Milano, and a diploma in Business Management and Entrepreneurship from Alta Scuola Politecnica. During his masters, he conducted research at Ecole Polytechnique and at Fermi National Accelerator Laboratory. In 2023, Stefano defended his PhD in Physics from Ecole Polytechnique Fédérale de Lausanne (EPFL) with a thesis entitled “Self-Interaction and Polarons in Density Functional Theory”. He joined MIR to combine electronic structure methods and machine learning for modelling defects and polarons. Stefano has a keen interest in video making, photography, skiing, kayaking, and swimming.

Francesco Libbi

Francesco earned his MSc in Mechanical Engineering from Politecnico di Torino in 2017. He later continued his research activity in the group "Theory and Simulation of Materials" in Lausanne, where he obtained his PhD in Materials Science in 2022. His research interests encompass a broad category of topics, including the theory and simulation of thermal transport, advanced electronic structure techniques, optical properties of qubits, and quantum computing. In 2021, he undertook a secondment at IBM Zurich aimed at developing algorithms for solving quantum chemistry problems on current superconducting quantum devices.

In 2022, Francesco joined the MIR group as a Postdoctoral Fellow, funded by the Swiss National Science Foundation Fellowship (SNSF), to develop a theory for the quantum motion of nuclei in crystals. This work aims to study ultrafast transient phenomena induced by irradiating materials with strong laser pulses in the THz range.

Norma Rivano

Norma earned her MSc in Physics from the University of Cagliari in 2018, conducting her thesis at EPFL, Lausanne, as an INSPIRE Potentials – MARVEL Master's Fellow in the "Theory and Simulation of Materials" group. Continuing at EPFL, Norma received her Ph.D. in Materials Science in 2023, specializing in "Phonons, Electron-Phonon Coupling, and Charge Transport in Low-Dimensional Materials". Her research focuses on the theory and simulation of low-dimensional materials, investigating how dimensionality affects vibrational properties, electron-phonon interactions, and transport applications. Norma aims to leverage dimensionality to engineer and design novel materials, employing a combination of analytical modeling, accurate first-principles calculations and high-throughput techniques. In 2023, she joined the MIR group as a Postdoctoral Fellow, integrating her expertise with the group's machine learning capabilities. Norma's goal is to develop a strategy that combines first-principles predictions with scalable methods for transport property predictions of large and complex heterostructures.

Albert Musaelian

Albert earned his PhD in Applied Math at Harvard in the MIR group in 2023 supported by the Department of Energy's Computational Science Graduate Fellowship (CSGF).  He is interested in method development for atomic-scale simulation and works in particular on the NequIP and Allegro atomistic machine learning approaches.

Cameron Owen

Cameron is a Postdoc in the Materials Intelligence Research (MIR) Group at Harvard University. He employs a variety of methods developed in the MIR group, primarily machine learning force fields, to study materials for use in heterogeneous catalysis. Cameron obtained his Ph.D. in Chemistry under the direction of Boris Kozinsky at Harvard in 2024, received his MPhil in Chemistry from the University of Cambridge under the direction of Stephen J. Jenkins on a Churchill Scholarship in 2020, and B.S. degrees in Chemistry and Physics from the University of Utah in 2019. He is from Boise, Idaho.

Sean Kavanagh

Seán obtained his undergraduate in Nanoscience, Physics and Chemistry of Advanced Materials at Trinity College Dublin (TCD) in his native Ireland, graduating in 2019. He then moved to London for his PhD in Computational Materials Science, in the Centre for Doctoral Training in the Advanced Characterisation of Materials (CDT-ACM) at both University College London (UCL) and Imperial College London, graduating in 2024. Seán's PhD research focused on understanding and predicting the behaviour of atomic-level defects in solid-state energy materials, along with software and method development.

Seán has joined the MIR group as a HUCE fellow, with an interest in using machine-learning methods to describe defects in solid-state energy materials. He likes being active and outdoors, socialising, taking in a view and some occasional horticulture (ideally a combining these activities). 

Matteo Carli

Matteo has a background in theoretical physics, developed during his BSc and MSc studies at the University of Trento and Imperial College London. He completed his PhD in Physics and Chemistry of Biological Systems at the International School for Advanced Studies in Trieste (SISSA), focusing primarily on the development and application of statistical and machine learning methods for unsupervised learning of high-dimensional and complex free energy surfaces.

Matteo joined MIR group in 2024. His research interests include method development for molecular and atomistic simulations, enhanced sampling techniques and the investigation of rare events utilizing statistics and artificial intelligence, unsupervised representation learning, uncertainty quantification and generative models.

Graduate students

Blake Duschatko

Blake is a graduate student in Applied Physics at Harvard University. His research interests intersect condensed matter theory, materials science, and developing efficient computational techniques for such problems. Currently, he is developing machine learning frameworks for coarse graining of molecular dynamics simulations. He is supported be a NASA Space Technology Graduate Research Opportunity (NSTGRO) award.

Anders Johansson

Anders is an Applied Physics graduate student. He is interested in the development of new and more general force fields for molecular dynamics simulations. Before joining MIR, he obtained his B.Sc. and M.Sc. from the University of Oslo, where he studied creep processes in silica asperities using molecular dynamics. In his spare time, he enjoys skeet shooting.

Kyle Bystrom

Kyle is a PhD student in Applied Physics. His primary research interest is developing more accurate and efficient electronic structure methods, particularly density functionals, using analytical theory and machine learning. He grew up in the San Francisco Bay Area and obtained his B.S. in Chemistry from UC Berkeley.

David Wang

Menghang (David) is a PhD student in Applied Physics at Harvard. He is interested in applying Machine Learning (ML) methods developed in the MIR group to study specific physics problems and exploring the potential of symmetry in ML. Before joining Harvard, he obtained his B.S. in Physics from the College of Creative Studies at UC Santa Barbara, where he worked on computational astrophysics and particle theory. During his free time, he enjoys outdoor activities and tries to become a better pilot in New England. He is from Qingdao, a beautiful seaside city in China.

Clare Yijia Xie 

Clare is a PhD student in Material Science & Mechanical Engineering. Her research interest lies at the intersection of chemistry, materials science, and computational simulation methods. Clare obtained her BSc degree in Chemistry from Imperial College London. Before joining MIR, she worked as a research engineer for a year at the Institute of High Performance Computing (IHPC), Singapore. Clare is supported by the National Science Scholarship (BS-PhD) from the Agency for Science, Technology and Research (A*STAR).

Chuin Wei Tan

Chuin Wei is a PhD student in Applied Physics. His research interests lie in improving the accuracy and speed of atomistic materials modelling techniques through machine learning. Prior to joining MIR, Chuin Wei spent a year as a senior research assistant at the Singapore University of Technology and Design after obtaining his MPhil in Materials Science and BA in Physics from the University of Cambridge.

Laura Zichi

Laura is a PhD student in Material Science and Mechanical Engineering. She is interested in understanding the reaction mechanisms that control electrolyte decomposition and interphase formation in all-solid-state batteries. Before joining MIR, she obtained her B.S. in Physics from the University of Michigan, where she studied two-dimensional atomic crystals. Additionally, she worked at Lawrence Berkeley National Laboratory, where she developed kinetic Monte Carlo simulations to study the solid-electrolyte interphase in Li-ion batteries.

Marc Descoteaux

Marc is a graduate student in Materials Science & Mechanical Engineering. He is interested in developing methods to accelerate the sampling of rare events in molecular dynamics simulations. He obtained his B.S. in Chemical Physics and M.S. in Materials Science and Engineering from Tufts University, where he used molecular dynamics and machine learning methods to predict the structures of cyclic peptides. 

Undergraduate students

Lorenzo Russotto

Lorenzo is a junior pursuing a BA in Physics. Originally from the alpine region of Aosta Valley, he is interested in employing the computational methods developed by the MIR to investigate the properties of dislocations within materials at the atomic level.

When he is not studying, you can find him exploring Massachusetts on his road bike or tinkering with anything mechanical!


Matthew Zahnzinger

Matthew has been a Faculty Coordinator with SEAS since 2017, and an administrative Team Lead since 2022. He has helped support the Kozinsky/MIR group as of 2023, in addition to the Weitz and Spaepen groups. A Malden resident originally from Brockton, he received his BA in Theatre and English from Northeastern University in 2009. Outside of Harvard, he works as a professional theatre and voice over actor. At home, Matthew is a slightly-more-than-casual chef, board game fanatic, horror aficionado, and Peter Cushing devotee.