The IAIFI is comprised of both physics and AI researchers at MIT, Harvard, Northeastern, and Tufts.

We are currently accepting applications from senior researchers in both academia and industry to become IAIFI Affiliates. If this interests you, see our IAIFI Affiliates Application Form.

If you are a junior researcher interested in becoming involved in IAIFI, see our Junior Researcher Interest Page.

There are various levels of involvement in IAIFI:

**Senior Investigators, Junior Investigators, IAIFI Affiliates**: Members in these categories are actively working on IAIFI-related research and must report their IAIFI-related activities to the NSF. Everyone at these levels is listed on this page.

**Friend of IAIFI**: Friends of IAIFI are Boston-area researchers interested in IAIFI’s mission, but cannot receive NSF funding and have no reporting requirements. Friends of IAIFI are welcome to participate in internal IAIFI activities. If you are interested in becoming a Friend of IAIFI, complete the interest form.

## Management

*IAIFI Director*

*QCD and jet physics, point clouds, topic modeling, optimal transport*

*MIT*

*IAIFI Deputy Director*

*dark sector physics, high-throughput real-time analysis, AI robustness*

*MIT*

## Senior Investigators

*IAIFI Institute Board (Harvard); Colloquium Organizer*

*dark matter, inflation, CMB, gravitational lensing, galaxy clustering*

*Harvard*

*IAIFI Institute Board (Northeastern); Summer School & Workshop Chair*

*string theory, particle-cosmology, topology, RL, NN-QFT correspondence*

*Northeastern*

*IAIFI Institute Board (Tufts); Summer School & Workshop Committee Member*

*neutrino physics, convolutional and generative neural networks, reinforcement learning*

*Tufts*

*IAIFI Institute Board (MIT)*

*mid-level vision, computational photography, black hole imaging*

*MIT*

*IAIFI Early Career and Equity Committee Chair*

*Time-domain astrophysics, gravitational wave astrophysics, machine learning classification*

*Harvard*

*IAIFI Community Building Chair*

*quantum field theory, collider physics*

*Harvard*

*IAIFI Research Coordinator for Physics Theory*

*Lattice QCD, flow models, unsupervised learning, interpretability*

*MIT*

*IAIFI Research Coordinator for Physics Experiment*

*Deep Learning based Hardware Acceleration, FPGAs, GPUs, Dark Matter, QCD and jet physics*

*MIT*

*IAIFI Research Coordinator for AI Foundations; Seminar Organizer*

*Sparse representations, deep learning, computational neuroscience*

*Harvard*

*IAIFI Fellowship Chair*

*gravitational waves, laser interferometry, quantum optics, precision measurements*

*MIT*

*IAIFI Education and Workforce Development Coordinator*

*quantum information science; machine learning; trapped ion quantum computation*

*MIT*

*IAIFI Computing Chair*

*strong intereactions, nuclear physics, AI for simulations*

*MIT*

*IAIFI Public Engagement Chair*

*Dark Matter, Galaxy Formation, Local Universe*

*MIT*

*IAIFI Industry Partnership Chair*

*artificial visual perception, computational sensing, computer vision*

*Harvard*

*Summer School & Workshop Committee*

*Information Theory, Generative Networks, Robust Representation Learning, Optimal Transport*

*Tufts*

*IAIFI Communications Committee Chair*

*sensorimotor control, deep learning, robotics, intuitive physics and behavior, reinforcement learning, computer vision*

*MIT*

*neutrino experiment, neutrino phenomenology, astroparticle physics*

*Harvard University*

*statistical cosmology, large-scale structure surveys*

*Harvard*

*Interstellar dust, high-energy astrophysics, cosmology*

*Harvard*

*string theory, string pheno, topology, geometry, ML*

*Northeastern*

*IAIFI Communications Committee Member*

*Dark matter theory, particle astrophysics, early-universe cosmology*

*MIT*

*IAIFI Early Career and Equity Committee Member*

*geometry, machine learning, computational physics, particle physics, materials physics*

*MIT*

*nanophotonics, AI for nanophotonics and science in general, physics inspired AI algorithms*

*MIT*

## IAIFI Fellows

*IAIFI Fellow; Summer School & Workshop Committee*

*lattice field theory, generative models, Markov Chain Monte Carlo, high performance computing*

*IAIFI*

*IAIFI Fellow, Early Career and Equity Committee and Industry Partnership Committee Member*

*cosmology and AI, ML models, statistics*

*IAIFI*

*IAIFI Fellow*

*Time-domain astrophysics, machine-learning classification, gravitational-wave astrophysics, variational inference*

*IAIFI*

*IAIFI Fellow; Summer School & Workshop Committee and Communications Committee Member*

*Theory of Deep Learning, Condensed Matter Theory*

*IAIFI*

*IAIFI Fellow*

*ML for particle physics, collider experiments, hypothesis testing, anomaly detection*

*IAIFI*

*IAIFI Fellow, Speaker Selection Committee Member*

*quantum algorithms and machine learning for condensed matter physics, high energy physics, and quantum information science*

*IAIFI*

*IAIFI Fellow, Early Career and Equity Committee and Community Building Committee Member*

*machine learning, particle physics experiments, neutrinos*

*IAIFI*

*IAIFI Fellow, IAIFI Computing Committee Member*

*particle astrophysics, cosmology, simulation-based inference, probabilistic programming*

*IAIFI*

*IAIFI Fellow*

*reinforcement learning, planning, optimal transport, robotics*

*IAIFI*

## Long-Term Visitors

## IAIFI Affiliates

*Electroweak interactions, collider physics, AI for event reconstruction, GPUs*

*Brandeis*

*Quantum information theory, in particular as it relates to high energy physics AdS/CFT; Complexity theory, both classical and quantum; Quantum Field Theory*

*Northeastern*

*ML for numerical geometry, string theory, working on a computational theory of mathematical thought*

*Harvard*

*Algebraic geometry, p-adic string theory, graph curvatures, ML for algebra*

*Brandeis*

*gravitational-wave astrophysics, muti-messenger astronomy, astroparticle physics, machine learning applications in physics*

*MIT*

*string phenomenology, dark sectors, AI transference, reinforcement learning*

*Northeastern*

*effective theory of deep learning, quantum field theory, black holes & quantum chaos, word play*

*MIT*

*Algebraic Geometry (Gromov-Witten theory, Donaldson-Thomas theory), Derived Algebraic Geometry, Mathematics of String theory, Mathematical AI*

*Center for QGM / Harvard / U. Miami*

*Geometry, large-scale optimization, numerical methods, machine learning*

*MIT*

*theoretical neuroscience, deep learning, AI*

*Harvard/Hebrew University*

*Distance geometry, matrix completion, compressive sensing, manifold learning*

*Tufts*

*Quantum gravity, string theory, geometry, particle physics, energy, ecology, computational physics*

*MIT*

*cosmological simulations, high-performance computing, galaxy/structure formation*

*MIT*

## Post-Docs and Research Scientists

*Dark-sector searches; hadron spectroscopy; high-throughput real-time analysis*

*MIT*

*nuclear physics, dense matter, gravitational wave astrophysics, HPC, AI for physics and astrophysics*

*Harvard*

*IAIFI Community Building Committee Member & Early Career and Equity Committee Member*

*string theory, algebraic topology, deep learning*

*Northeastern*

*lattice field theory, physics beyond the Standard Model, machine learning, quantum computing*

*MIT*

*lattice field theory, statistical mechanics, normalizing flows, Markov Chain Monte Carlo*

*MIT*

*Computer Architectures, Compilers, Code optimization, Machine Learning*

*MIT*

*supernovae, gravitational wave sources, transient surveys*

*Harvard*

*particle physics beyond the standard model, collider physics, quantum field theory*

*Harvard*

*Hardware acceleration, Anomaly detection, Dark matter searches*

*MIT*

*IAIFI Early Career and Equity Committee Member*

*collider physics, dark sectors, early universe cosmology*

*Harvard*

*Postdoctoral Associate*

*gravitational waves, laser interferometry, AI-based sensing and control, embedded machine learning*

*MIT*

*Data and Applied Scientist*

*dark matter, strong lensing, gaia satellite, lhc, hst, anomaly detection, uncertainty reduction*

*Microsoft*

*Phenomenology of Particle Physics, Beyond the Standard Model Physics, Jet Physics, Machine Learning*

*MIT*

*theoretical/numerical cosmology, cosmological tests of fundamental physics, LSS*

*Harvard*

## Students

*Quantum field theory, collider physics, and machine learning in high energy physics.*

*MIT*

*IAIFI Early Career and Equity Committee Member*

*Quantum field theory, theoretical particle physics, and interfaces of these with machine learning*

*MIT*

*binary evolution, neutron stars and black holes, gravitational waves, star formation history, Monte Carlo Sampling, Uncertainty Quantification*

*Harvard*

*Quantum information, quantum computation and quantum simulation with machine learning.*

*MIT*

*self-supervised learning, meta learning, contrastive learning, natural language processing*

*MIT*

*Quantum Field Theory, Particle Physics, Machine Learning*

*Harvard*

*Speaker Selection Committee Member*

*Quantum Computation, Machine Learning, Graphical Models*

*MIT*

*String theory, string field theory, and machine learning for geometry*

*MIT*

*Interested in Particle Physics, QFT, Phenomenology, Machine Learning, and Information Theory!*

*MIT*

*Time-domain astronomy, supernovae, transients, telescope surveys*

*Harvard*

*Computer Vision, Distributed COmputing, Information Theory, Deep Learning*

*MIT*

*Statistical learning; Optimization; Computer Vision; Imaging*

*Harvard*

*Symmetry equivariant neural networks, computational physics, physics inspired AI*

*MIT*

*Reinforcement learning, sequential decision making, biologically inspired computing*

*MIT*

*Electromagnetic counterpart of gravitational wave events*

*Harvard*

*Early Career and Equity Committee Member*

*Neutrino Physics & Machine Learning*

*Tufts*

*Postdoc*

*generative models, lattice field theory, physics beyond the standard model*

*Universität Bern, ITP*

*Summer School & Workshop Committee; Community Building Committee*

*jet physics, graph learning, ML interpretability and robustness.*

*MIT*

*Geometry, Systems for Machine Learning, GPUs, High Performance Computing, Domain Specific Languages, Hardware Accelaration*

*MIT*

*high energy physics, dark matter, deep learning, heterogeneous computing, accelerated architectures, high-throughput computing*

*MIT*

*IAIFI Summer School & Workshop Committee Member*

*Quantum computing in HEP. Machine-learning aided simulation*

*Harvard*

*deep learning, scalable Bayesian inference, medical imaging, computational neuroscience*

*Harvard*

*IAIFI Summer School & Workshop Committee Member*

*physics-informed machine learning, condensed matter physics, nonlinear dynamical systems, photonics*

*MIT*

*Physics for AI, nuclear physics, high energy physics, atomic molecular and optical physics*

*MIT*

*Grad Student*

*Data Analysis of Gravitational Waves with Machine Learning*

*MIT*

*Graduate Student*

*Computational & systems neuroscience, physics-inspired computing, probabilistic computing*

*MIT*

*Anomaly detection, Higgs measurements, Graph Neural Networks, Fast inference, Dark matter searches*

*MIT*

*Summer School & Workshop Committee; Speaker Selection Committee*

*Interstellar dust, Scalable Bayesian Inference, Cosmology, Astrostatistics*

*Harvard*

*IAIFI Outreach Committee Member*

*Dark matter, Galactic Dynamics, Galaxy Mergers, Dwarf Galaxies, Graph Neural Networks*

*MIT*

*High Energy Physics, Dark Matter Searches, Machine Learning, High Performance Computing*

*MIT*

*Summer School & Workshop Committee*

*NN scaling laws, machine learning, cosmology*

*Northeastern*

*Collider Data Analysis, FPGAs, Probabilistic Modeling and Inference*

*MIT*

*Collider physics, dark matter searches, Higgs physics, novel machine learning approaches*

*MIT*

*equivariant ML, wavelet/kernel methods, non-gaussianity, astrophysics*

*Harvard*

*dark matter, gravitational lensing, galaxy clustering, inflation*

*Harvard*

*Particle astrophysics and applications of machine learning in data processing and simulations.*

*MIT*

*Statistical physics, quantum information theory, theory of deep learning*

*MIT*

*Deep learning theory, structured representations, nonlinear optimization, algebraic geometry*

*Harvard*

*Experimental and computational approaches to High Energy and Particle Physics*

*MIT*

*Machine Learning, Algorithms, Probability/Statistics, Origami*

*MIT*

*Neurosymbolic Regression, Interpretable Machine Learning, Neural Simulation of Quantum Systems*

*MIT*

*Large language models, AI for physics, Automated planning, Control systems*

*MIT*

*Machine Learning, Software Engineering, Physics-inspired algorithms*

*MIT*

*Machine Learning, astrophysics, particle physics*

*Northeastern*

*Graph Neural Networks, Theoretical Particle Physics, Machine Learning for Physics*

*MIT*