_config.yml

#
# Sera - OnePage Jekyll Theme
# Configuration File
#

# Information for compile
exclude: ["Gemfile", "README.md"]

# Sass configuration
sass:
  sass_dir: _scss

# Information for deploy
baseurl: ""

# the base hostname & protocol for your site
url: "http://https://polymathic-ai.org/"

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######   Optional Features    ######
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smooth-scroll: false

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###########   Plugins    ###########
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###############   HEADER INFORMATIONS   ###############
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# This is your site title
title: Polymathic
# Website language
lang: en-US
# Header Title
header-title: Polymathic AI
# Header Tagline
header-tagline: Advancing Science through Multi‑Disciplinary AI
# SG: the site logo is set in logo.svg
# I chagned it to text.
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# IMPORTANT: you can modify contact form from this static template, but now works contact form works with a free external server
# To configure this contact form, first please send a fictive email afeter you enter below your email and verify that :)
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email: info@polymathic-ai.org

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# # Default link is a link to all Sera OnePage products
# banner-link: https://themeforest.net/collections/6069390-sera

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######  Global Social Links   ######
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youtube: "#"
facebook: "#"
twitter: "#"
vimeo: "#"

#########################
######   Widgets   ######
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# About Blog Author Widget
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  author-tagline: Blog Author
  author-info: I wonder where this goes!
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# Enter your Mailchimp User ID and Campaign ID
# @TODO: Add in a link for where to find these
mailchimp:
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####
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# Hi you now use Sera - OnePage Jekyll Theme created by Ohkimur
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# Below are each section from the website in order from top to bottom
# @TODO Edit each sections with your real information and each section from Sera will autocomplete with your information
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####

#####################################
#############   About   #############
#####################################
about-title: Our Mission
about-description: To usher in a new class of machine learning for scientific data, building models that can leverage shared concepts across disciplines. We aim to develop, train, and release such foundation models for use by researchers worldwide.

#####################################
#############  Features  ############
#####################################
features-title: Goals and Features
features-description: Through cutting-edge research and collaborative innovation, we're setting new benchmarks in the application of foundation models in science. Our goals are designed to address the pressing challenges and unlock unprecedented opportunities. Below are key features that define our mission.
#
# Features
#
features:
  # Feature
  - title: Innovative Technologies
    description: Leveraging state-of-the-art methods to push the boundaries of what foundation models can achieve in scientific research.
    icon: pe-7s-airplay

  # Feature
  - title: Interdisciplinary Research
    description: Fostering collaboration across scientific domains to address complex issues through the power of foundation models.
    icon: pe-7s-vector

  # Feature
  - title: Open-Source Solutions
    description: Creating open-source foundation models and tools that are accessible to researchers around the globe.
    icon: pe-7s-help2


#####################################
############  Portfolio  ############
#####################################
# portfolio-title: Portfolio
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# #
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#     categories: [Photography, Logo]
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#####################################
##########  Core Features  ##########
#####################################
# core-title: Core Features
# core-description: Duis at odio vitae ex gravida volutpat. Nulla finibus aliquet diam ut eleifend. Mauris consequat interdum quam. Mauris dui sapien, efficitur et cursus id, molestie fringilla turpis aliquet diam ut eleifend.

# #
# # Core Features Left
# #
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#   # Feature
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#     icon: pe-7s-coffee

#   # Feature
#   - name: Friendly
#     description: Lorem ipsum dolor sit amet, consectetuer adipiscing diam.
#     icon: pe-7s-smile

# #
# # Core Features Right
# #
# core-features-right:
#   # Feature
#   - name: Branding
#     description: Lorem ipsum dolor sit amet, consectetuer adipiscing diam.
#     icon: pe-7s-wine

#   # Feature
#   - name: Web Design
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#     icon: pe-7s-monitor

#   # Feature
#   - name: Graphic Design
#     description: Lorem ipsum dolor sit amet, consectetuer adipiscing diam.
#     icon: pe-7s-crop

#   # Feature
#   - name: Photography
#     description: Lorem ipsum dolor sit amet, consectetuer adipiscing diam.
#     icon: pe-7s-camera

#####################################
########### Testimonials ############
#####################################
# testimonials-title: Testimonials
# testimonials-description: Aenean at tincidunt sem. Interdum et malesuada fames ac ante ipsum primis in faucibus. Morbi id ornare ante. Cras odio nibh, volutpat vitae volutpat sed, suscipit et nisi.

# #
# # Testimonials
# #
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#     logo-img: codecanyon.png

#   # Client
#   -name: Irene Warner
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#     url-text: VideoHive.net
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#     logo-img: audiojungle.png

#####################################
############# Our Blog ##############
#####################################
blog-title: Recent News
# blog-description: Look at the amazingness that oozes out of us!

#####################################
############### Team ################
#####################################
team-title: The Team
# team-description: Meet our members. We are so cool!
#
# Team Members
#
team:
  # Team Member
  - full_name: Alberto Bietti
    tagline:
    avatar: albert_bietti.jpg
    website: https://alberto.bietti.me/
    bio: Alberto Bietti is a research scientist at Flatiron Institute's Center for Computational Mathematics. He received his PhD in applied mathematics from Inria and Université Grenoble Alpes in 2019, and was a Faculty Fellow at the NYU Center for Data Science from 2020 to 2022. He also spent time at Inria Paris, Microsoft Research, and Meta AI. Prior to his PhD, he obtained degrees from Mines ParisTech and Ecole Normale Supérieure, and worked as a software engineer at Quora. His research focuses on the theoretical foundations of deep learning.

  - full_name: Kyunghyun Cho
    tagline:
    avatar: kyunghyun_cho.jpg
    website: https://kyunghyuncho.me
    bio: Kyunghyun Cho is an associate professor of computer science and data science at New York University and a senior director of frontier research at the Prescient Design team within Genentech Research & Early Development (gRED). He is also a CIFAR Fellow of Learning in Machines & Brains and an Associate Member of the National Academy of Engineering of Korea. He was a research scientist at Facebook AI Research from June 2017 to May 2020 and a postdoctoral fellow at University of Montreal until Summer 2015 under the supervision of Prof. Yoshua Bengio, after receiving MSc and PhD degrees from Aalto University April 2011 and April 2014, respectively, under the supervision of Prof. Juha Karhunen, Dr. Tapani Raiko and Dr. Alexander Ilin. He received the Samsung Ho-Am Prize in Engineering in 2021. He tries his best to find a balance among machine learning, natural language processing, and life, but almost always fails to do so.

  - full_name: Miles Cranmer
    tagline:
    avatar: miles_cranmer.jpg
    website: https://astroautomata.com/
    bio: Miles Cranmer is Assistant Professor in Data Intensive Science at the University of Cambridge, joint between the Department of Applied Mathematics and Theoretical Physics and the Instititute of Astronomy. He received his PhD from Princeton University, spending time at Google DeepMind and Flatiron Institute, and before that, his BSc from McGill University. Miles is interested in automating scientific research in the physical sciences with machine learning, and works on a variety of pure and applied machine learning projects in pursuit of this goal. His ML research has concentrated on symbolic regression, graph neural networks, and physics-motivated architectures, while his applied projects have looked at multi-scale physics, planetary dynamics, and cosmology.

  - full_name: Irina Espejo
    tagline:
    avatar: irina_espejo.png
    website: https://github.com/irinaespejo
    bio: Irina Espejo joined the collaboration as a Postdoctoral Researcher at NYU CDS in May 2025. Her research interests are multimodal foundational models for science and their transferability to low-data regime. She received a PhD from NYU Center for Data Science in 2023, supervised by Kyle Cranmer. She was a Fulbright Scholar from 2018-2020. Irina previously worked at IBM Research in Zurich as a Postdoc from 2023 to 2025 and as an intern in BigHat Biosciences. Before that she obtained degrees in Physics and Mathematics from University of Oxford and Universitat Automona de Barcelona.

  - full_name: Siavash Golkar
    tagline:
    avatar: siavash_golkar.jpg
    website: http://siavashgolkar.com/
    bio: Siavash Golkar is a research scientist working in the field of machine learning and applications to scientific domains. Siavash received his PhD in 2015 in the field of High Energy Physics, working on topological states of matter. He has since worked as a postdoc at Cambridge University and New York University and as an associate research scientist at the Flatiron Institute. His recent work spans research in ML from continual and transfer learning to applying large transformer models to numerical and scientific datasets.

  - full_name: Tom Hehir
    tagline:
    avatar: tom_hehir.jpg
    website: https://tom-hehir.github.io/
    bio: Tom is a PhD student supervised by Prof Miles Cranmer at the Institute of Astronomy, University of Cambridge. He aspires to apply contemporary techniques in machine learning, data science, and statistics to assorted problems in astronomy. His current focus is on developing multimodal, transformer-based foundation models for galaxy surveys. Previously, Tom completed a master’s degree in physics at the University of Durham.
    
  - full_name: Shirley Ho
    tagline: Principal Investigator
    avatar: shirley_ho.jpg
    website: https://www.shirleyho.me/
    bio: Shirley Ho is a Group Leader of Cosmology & Machine Learning at Flatiron Institute,  Research Professor of Physics and Affiliated Faculty of Center for Data Science at New York University. She also holds other appointments at Carnegie Mellon University and Princeton University. She is also a Fellow at the International Astrostatistics Association. She was a Senior Scientist at Berkeley Lab from 2016 to 2018 and a Cooper Siegel Chair Professor at Carnegie Mellon University from 2011 to 2016. She was a Seaborg and Chamberlain fellow at Berkeley Lab and UC Berkeley from 2009-2011 under the supervision of Prof. Martin White, Prof. David Schlegel and Prof. Uros Seljak, after receiving a PhD degree from Princeton University 2008, under the supervision of Prof. David Spergel and graduated summa cum laude with a B.A. in Physics and Computer Science from UC Berkeley. She was a National Blavatnik finalist in 2023, and was awarded the Macronix Prize (2014) and Carnegie Science Award (2015). She was also recognized by the European Physical Society Giuseppe and Vanna Cocconi Prize in cosmology 2023 for work in Sloan Digital Sky Survey BOSS survey, NASA Group Achievement Prize in 2020 and 2022 for her work in Planck and Roman Space Telescope. 

  - full_name: Jake Kovalic
    tagline: 
    avatar: jake_kovalic.png
    website: https://www.linkedin.com/in/jake-kovalic-080508146/
    bio: Jake is a PhD student in Applied Physics at Yale, supervised by Smita Krishnaswamy. His research interests include multimodal foundation models and representation learning with applications to biological datasets. Previously, Jake worked at Johns Hopkins Applied Physics Lab, and completed his undergraduate studies in Computer Science and Physics and the University of Michigan.

  - full_name: Geraud Krawezik
    tagline:
    avatar: geraud_krawezik.jpg
    website: https://www.simonsfoundation.org/people/geraud-krawezik/
    bio: Géraud Krawezik joined the foundation in 2021 as a software engineer in the Scientific Computing Core in the Flatiron Institute. He was previously part of the technical team at Lucata, where he was working on graph, artificial intelligence, database, and linear algebra algorithms. Géraud has held several research and development positions, ranging from engineering for parallel scientific software, quantitative programming in finance, to CTO in a consumer electronics startup. Géraud has a PhD in High Performance Computing from Paris Sud University, and has conducted post-doctoral research at UIUC.

  - full_name: Francois Lanusse
    tagline:
    avatar: francois_lanusse.jpg
    website: https://flanusse.net/
    bio: Francois Lanusse is an interdisciplinary researcher at the intersection of Deep Learning, Statistical Modeling, and Observational Cosmology. Dr. Lanusse holds a permanent position at the CNRS, and is currently an Associate Research Scientist at the Simons Foundation. He received his PhD in Astrophysics at CEA Paris-Saclay and was subsequently a postdoctoral researcher at Carnegie Mellon University and UC Berkeley.

  #- full_name: Tanya Marwah
  #  tagline:
  #  avatar: tanya_marwah.png
  #  website: https://tm157.github.io/
  #  bio: Tanya Marwah is a Research Fellow at the Simons Foundation working with Polymathic AI. She is broadly interested in theoretical and empirical foundations of Machine Learning and its applications to scientific domains. Her current interests are around generative modeling of scientific phenomena, inverse problems and building scientific agents. Her ultimate goal is to develop ML algorithms and methods that help us accelerate the scientific process and enable scientific discovery. She recently graduated with a PhD from the Machine Learning Department at Carnegie Mellon University and holds a Masters in Robotics from the Robotics Institute at CMU and was a Siebel Scholar.

  - full_name: Michael McCabe
    tagline:
    avatar: michael_mccabe.jpg
    website: https://mikemccabe210.github.io/
    bio: Michael McCabe joined the institute as a research analyst in 2023. He is a final year PhD Student at the University of Colorado, Boulder advised by Prof. Jed Brown and has broad research interests in machine learning and optimization, especially for physical systems. Michael’s current research goals are integrating ideas from numerical methods into large-scale deep learning architectures to build tools that are better suited to learning physical dynamics  more reliably or efficiently. Throughout his PhD, he has worked with Lawrence Berkeley and Argonne National Laboratories. Outside of work, Michael enjoys climbing, running, and reading.

  #- full_name: Lucas Meyer
  #  tagline:
  #  avatar: lucas_meyer.jpg
  #  website: https://ltmeyer.github.io/
  #  bio: Lucas Meyer is a researcher and software engineer working on accelerating science using artificial intelligence and high-performance computing. He holds a PhD in computer science and applied mathematics from Université Grenoble Alpes, completed in partnership with INRIA and EDF, under the supervision of Bruno Raffin. His doctoral research centered on training deep learning models for large-scale numerical simulations. Before pursuing his PhD, Lucas worked in the space industry, including at the European Space Agency, developing software and deep learning methods for remote sensing. He holds an M.Sc. in computer science from Université de Montréal, where he worked on optimization software for robotic swarms with Giovanni Beltrame. He also graduated in software engineering and applied mathematics from École Nationale des Ponts et Chaussées.
    
  - full_name: Rudy Morel
    tagline:
    avatar: rudy_morel.jpg
    website: https://www.di.ens.fr/rudy.morel/
    bio: Rudy Morel is a Research Fellow at the Center for Computational Mathematics (CCM) at the Flatiron Institute. He earned his PhD in Applied Mathematics from the École Normale Supérieure (ENS) in Paris, specializing in applied stochastic processes. Rudy's current research focuses on developing and understanding foundational models for science, with a particular emphasis on multi-scale modeling, generalization properties, and efficient fine-tuning.

  - full_name: Payel Mukhopadhyay
    tagline:
    avatar: payel_mukhopadhyay.jpg
    website: https://www.linkedin.com/in/payel-mukhopadhyay-5529b026b/
    bio: Payel Mukhopadhyay is an Assistant Research Professor at the University of Cambridge working at the intersection of AI, physics, and scientific computing. She received her PhD in astrophysics from Stanford University in 2022, where her research covered supernovae, galactic outflows, cosmic rays, and dark matter. Her current work focuses on developing machine learning methods for scientific discovery, with particular interests in foundation models, scientific machine learning, and complex physical systems. Outside of research, she enjoys cooking, reading, and taking long walks with her dog.

  #- full_name: Ruben Ohana
  #  tagline:
  #  avatar: ruben_ohana.jpg
  #  website: https://rubenohana.github.io/
  #  bio: Ruben Ohana joined the Center for Computational Mathematics of the Flatiron Institute as a Research Fellow in 2022. His research interests are machine learning for scientific problems, optimization of large models, and bridging gaps between theoretical fields. He obtained his PhD from Ecole Normale Supérieure in 2022, supervised by Florent Krzakala, Alessandro Rudi and Laurent Daudet. In parallel, he was a research scientist at LightOn, and interned at the Criteo AI Lab.  

  - full_name: Mariel Pettee
    tagline:
    avatar: mariel_pettee.jpg
    website: https://marielpettee.com/
    bio: Dr. Mariel Pettee (Physics PhD, Yale University) is an interdisciplinary scientist and performing artist based in Brooklyn. She is a Chamberlain Postdoctoral Research Fellow at Lawrence Berkeley National Laboratory and a visiting researcher at the Flatiron Institute Center for Computational Astrophysics. Her scientific research encompasses the development of Machine Learning (ML) models for high-energy particle physics and cosmology that have broad applicability across other areas of science and art. Since 2017, she has been one of the pioneers of AI-generated dance, leading multiple independent teams of researchers to develop custom ML models to generate choreography based on 3D motion capture data of her own movements. Prior to her PhD, she earned her Bachelors in Physics & Mathematics from Harvard University and her Masters in Physics at the University of Cambridge as a Harvard-Cambridge Scholar. 

  - full_name: Helen Qu
    tagline: 
    avatar: helen_qu.png
    website: https://www.simonsfoundation.org/people/helen-qu/
    bio: Helen Qu is a research fellow at the Center for Computational Astrophysics (CCA) at the Flatiron Institute. She is broadly interested in reinforcement learning, collective intelligence, multimodal models, and AI for science. She holds a PhD in Physics and a BSE in Computer Science from the University of Pennsylvania, specializing in machine learning methods for type Ia supernova cosmology.

  #- full_name: Bruno Regaldo
  #  tagline:
  #  avatar: bruno_regaldo_saint_blancard.jpg
  #  website: https://bregaldo.github.io/
  #  bio: Bruno Régaldo-Saint Blancard is a Research Fellow at the Center for Computational Mathematics, Flatiron Institute. He obtained a PhD in Astrophysics from the École Normale Supérieure (ENS), Paris. Prior to that, he graduated from the École Polytechnique, and obtained a M.S. in Astrophysics from the Observatoire de Paris. Bruno’s research focuses on the development of statistical methods for astrophysics/cosmology and beyond, using signal processing and machine learning. He is interested in various problems including generative modeling, inference, denoising, and source separation.

  - full_name: Jeff Shen
    tagline:
    avatar: jeff_shen.png
    website: http://jshen.net/
    bio: Jeff is a PhD student at Princeton University supervised by Shirley Ho. He is broadly interested in deep generative models and how to adapt these models to be better suited for use in the physical sciences. Within Polymathic, his current focus is on developing multimodal foundation models for astrophysics surveys. Previously, Jeff completed his undergraduate degree in astrophysics and statistics at the University of Toronto.


  - full_name: Hadi Sotoudeh
    tagline:
    avatar: hadi_sotoudeh.png
    website: https://inferstellar.ai
    bio: Hadi is a PhD student at the University of Cambridge, co-supervised by Miles Cranmer and Neil Lawrence. His research focuses on developing foundation models that learn physically meaningful representations of astronomical and physical systems. Within Polymathic AI, he works on connecting simulations and observations through shared latent representations, with applications to galaxy evolution, large sky surveys, and cosmology. More broadly, he is interested in how expressive AI models can support reliable scientific inference while remaining grounded in physical and methodological principles. Before Cambridge, he worked on machine learning for astrophysics at Mila with Laurence Perreault-Levasseur. Outside research, he enjoys hiking, scuba diving, and watching birds behave like tiny dinosaurs.


  # - full_name: Tiberiu Tesileanu
  #   avatar: tiberiu_tesileanu.jpg
  #   website: https://www.ttesileanu.com
  #   bio: "Tiberiu Tesileanu is currently a Research Software Engineer at Meta, working with the CTRL team. Before that he was an Associate Research Scientist with the Center for Computational Neuroscience at the Flatiron Institute. His background is in high energy physics, having worked on the AdS/CFT duality in string theory for his PhD. He then worked for several years in systems biology and computational neuroscience, before shifting focus towards machine learning and software engineering."

#####################################
########## Collaborators ############
#####################################
collaborators-title: Collaborators & Friends
# collaborators-description: 
#
# Collaborators
#
collaborators:
  # List of collaborators
  - full_name: Michael Eickenberg
    avatar: michael_eickenberg.jpg
    mini-avatar: michael_eickenberg.png
    website: https://www.simonsfoundation.org/people/michael-eickenberg/
    bio: Michael Eickenberg joined the Flatiron Institute’s Center for Computational Mathematics in February 2020. Eickenberg’s work consists in using machine learning methods towards forward and reverse modeling of fMRI brain activity following sensory stimulation. Recently, Eickenberg was a postdoctoral researcher at the Helen Wills Neuroscience Institute at UC Berkeley. He has a Bachelor’s degree in Physics and Mathematics from the University of Luxembourg, a Master’s degree in Mathematics, Computer Vision, and Applied Mathematics from École Normale Supérieure de Cachan, and a Ph.D. in Machine Learning and Modeling Applied to Neuroimaging from Paris-Sud University (Paris XI).
  
  - full_name: Rio Fear
    avatar: 
    mini-avatar: rio_fear.png
    website: https://astroautomata.com/#team
    bio: 
  
  - full_name: David Fouhey
    avatar: 
    mini-avatar: david_fouhey.png
    website: https://cs.nyu.edu/~fouhey/
    bio: 
  
  - full_name: Jiequn Han
    avatar: 
    mini-avatar: jiequn_han.png
    website: https://users.flatironinstitute.org/~jhan/ 
    bio: 

  - full_name: Keiya Hirashima
    avatar: 
    mini-avatar: keiya_hirashima.png
    website: https://kyafuk.github.io/utokyo-hirashima/index.html
    bio: "Keiya Hirashima is a fourth-year PhD student in Astronomy at the University of Tokyo, Japan, and spending time at Flatiron Institute. He is striving to synergize Machine Learning, HPC, and galactic evolution insights. With a foundation in computer science, he is currently exploring CNN-based and transformer-based models for: (1) surrogate models to replace computationally intensive multi-scale simulations, and (2) the morphological classification of galaxies. He earned his B.E. in Informatics and Mathematical Science from Kyoto University. Beyond research, he enjoys pole vault and bouldering."
  
  - full_name: Ghazal Khalighinejad
    avatar: 
    mini-avatar: ghazal_khalighinejad.png
    website: https://ghazalkhalighinejad.github.io/
    bio: 
  
  - full_name: Oliver Liu
    avatar: 
    mini-avatar: oliver_liu.png
    website: https://ollieliu.com/
    bio:

  - full_name: Nick Lourie
    avatar: nick_lourie.jpg
    mini-avatar: nick_lourie.png
    website: https://www.semanticscholar.org/author/Nicholas-Lourie/35219984
    bio: Nicholas Lourie is a PhD student at NYU investigating empirical models of deep learning. His research seeks better statistical frameworks for designing, developing, and evaluating neural networks. At NYU, he is advised by He He and Kyunghyun Cho, while in the past he worked at the Allen Institute for AI on machine ethics, common sense, prompt-based learning, and the evaluation of natural language processing models.
  
  - full_name: Stefan Nixon
    avatar:
    mini-avatar: stefan_nixon.png
    website: https://uk.linkedin.com/in/stefan-nixon-a3856b1a5
    bio:
  
  - full_name: Liam Parker
    tagline:
    mini-avatar: liam_parker.png
    website: https://www.linkedin.com/in/liam-parker-96ba14160/
    bio:  Liam is a Ph.D. student in physics at U.C. Berkeley, supported by the NSF Graduate Research Fellowship, and a visiting researcher at the Flatiron Institute. He has been a member of the Polymathic team since 2023. Presently, his research focuses primarily on developing large, multimodal foundation model for the physical sciences. Prior to Berkeley, he received his B.S. in physics from Princeton University and completed a predoctoral fellowship in the Center for Computational Astrophysics at Flatiron. Outside of work, Liam enjoys mountaineering, olympic-style weightlifting, and guitar.
  
  - full_name: Francesco Pio Ramunno
    avatar: 
    mini-avatar: francesco_pio_ramunno.png
    website: https://github.com/fpramunno
    bio:
  
  - full_name: Francois Rozet
    avatar: 
    mini-avatar: francois_rozet.png
    website: https://francois-rozet.github.io/
    bio:
  
  - full_name: Sebastian Wagner-Carena
    avatar: 
    mini-avatar: sebastian_wagner-carena.png
    website: https://www.simonsfoundation.org/people/sebastian-wagner-carena/
    bio:
  
  - full_name: Rachel C. Zhang
    avatar: 
    mini-avatar: rachel_zhang.png
    website: https://astroautomata.com/#team
    bio:


#####################################
########## Institutions #############
#####################################
institution-title: Participating Institutions

institution:
    # Institution Member
  - name: Schmidt<br>Sciences
    avatar: SchmidtSciences.png
    url: https://www.schmidtsciences.org/
  
  # Institution Member
  - name: Simons<br>Foundation
    avatar: simons-logo.svg
    url: https://www.simonsfoundation.org/

  # Institution Member
  - name: New York<br>University
    avatar: nyu.png
    url: https://www.nyu.edu/

  # Institution Member
  - name: University of Cambridge
    avatar: cambridge.png
    url: https://www.cam.ac.uk

  # Institution Member
  #- name: Schmidt Futures
  #  avatar: schmidt.png
  #  url: https://www.schmidtfutures.com/

  # Institution Member
  #- name: Princeton University
  #  avatar: princeton.svg
  #  url: https://www.princeton.edu/

  # Institution Members
  - name: Berkeley Lab
    avatar: berkeley.png
    url: https://www.lbl.gov/


#####################################
############### SAG ################
#####################################
sag-title: Scientific Advisory Group
# sag-description: Meet our SAG. They are cool too!
#
# Team Members
#
sag:
  - name: Colm-Cille<br>Caulfield
    affil: University of Cambridge
    url: http://www.damtp.cam.ac.uk/person/cpc12

  - name: Leslie<br>Greengard
    affil: Flatiron Institute<br>New York University<br>
    url: https://www.simonsfoundation.org/people/Leslie-Greengard # Leslie likes this one. Don't change.

  - name: David<br>Ha
    affil: Sakana AI
    url: https://blog.otoro.net/

  - name: Yann<br>LeCun
    affil: Meta AI<br>New York University
    url: http://yann.lecun.com/

  - name: Stephane<br>Mallat
    affil: École&nbsp;Normale&nbsp;Supérieure<br>Collège de France<br>Flatiron Institute
    url: https://www.di.ens.fr/~mallat/mallat.html

  - name: David<br>Spergel
    affil: <br>Simons Foundation <br> &nbsp;
    url: https://www.simonsfoundation.org/people/David-Spergel/

  - name: Olga<br>Troyanskaya
    affil: Flatiron Institute<br>Princeton University
    url: https://www.cs.princeton.edu/people/profile/ogt

  - name: Laure<br>Zanna
    affil: New York University
    url: https://zanna-researchteam.github.io/

#####################################
#############  Careers  ############
#####################################
career-title: Careers
career-description: Current job openings

roles:
  - title: Research Software Engineers
    description: In-person - Manhattan, NYC / Rolling Deadline
    link: https://apply.interfolio.com/160510

  - title: Research Software Engineers
    description: In-person - Manhattan, NYC / Rolling Deadline
    link: https://apply.interfolio.com/156427
  
  - title: Research Scientists
    description: In-person - Manhattan, NYC / Rolling Deadline
    link: https://apply.interfolio.com/164213
  
  - title: Internship (Fall 2025 - Spring 2026)
    description: In-person - Manhattan, NYC / Rolling Deadline
    link: https://docs.google.com/forms/d/e/1FAIpQLSfpf7DHjjT8EB3pGKLja04YQa5yhnmW1_TcyAPL03uR4ePgqg/viewform

#  - title: Postdoctoral Researchers to build large scientific model with solar physics data
#    description: In-person - Manhattan, NYC / Mar 15, 2025
#    link: https://apply.interfolio.com/161867
  

#####################################
########## Pricing Tables ###########
#####################################
# pricing-title: Pricing Tables
# pricing-description: Nulla a tellus at turpis gravida congue non interdum et malesuada fames ac ante ipsum primis in faucibus. Morbi id ornare ante. Cras odio nibh, volutpat vitae volutpat sed, suscipit et nisi. Nulla a tellus at turpis gravida congue non sed nisl. Pellentesque scelerisque eu neque et tincidunt.

# #
# # Plan Personal
# #
# plan-personal-price: $99
# plan-personal-offer-1-title: 01 PSD Pack
# plan-personal-offer-1-info: Mauris gravida fringilla est. Proin sodales sed erat et cursus. Mauris quis posuere enim.
# plan-personal-offer-2-title: 100 Support Tickets
# plan-personal-offer-2-info: Mauris gravida fringilla est. Proin sodales sed erat et cursus. Mauris quis posuere enim.
# plan-personal-url: "#"

# #
# # Plan Business
# #
# plan-business-price: $499
# plan-business-offer-1-title: 05 PSD Pack
# plan-business-offer-1-info: Mauris gravida fringilla est. Proin sodales sed erat et cursus. Mauris quis posuere enim.
# plan-business-offer-2-title: 1000 Support Tickets
# plan-business-offer-2-info: Mauris gravida fringilla est. Proin sodales sed erat et cursus. Mauris quis posuere enim.
# plan-business-url: "#"

# #
# # Plan Ultimate
# #
# plan-ultimate-price: $999
# plan-ultimate-offer-1-title: 10 PSD Pack
# plan-ultimate-offer-1-info: Mauris gravida fringilla est. Proin sodales sed erat et cursus. Mauris quis posuere enim.
# plan-ultimate-offer-2-title: Support Unlimited
# plan-ultimate-offer-2-info: Mauris gravida fringilla est. Proin sodales sed erat et cursus. Mauris quis posuere enim.
# plan-ultimate-url: "#"

#####################################
############   Contact   ############
#####################################
contact-title: Contact Us
contact-description: Need more information? Get in touch.

#####################################
#############   Footer   ############
#####################################
footer-description: © 2023 Polymathic AI. All rights reserved.
# SG: removed the following from footer section
# footer-copyright-text: Ohkimur
# footer-copyright-url: https://github.com/ohkimur
# footer-copyright-year: 2021


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    template: 'collaborator-member'
    name: 'full_name'
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# Show future posts:
timezone: America/New_York
future: true