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General Information

Full Name Adam Joseph Eisen
Date of Birth November 8th 1996
Languages English

Education

  • Sep 2020 - Present
    PhD Candidate in Brain and Cognitive Sciences
    Massachusetts Institute of Technology, Cambridge, MA, USA
    Advisors:
    Earl K. Miller and Ila R. Fiete
  • Sep 2014 - Apr 2018
    Bachelor of Applied Science in Mathematics & Engineering, Computing and Communications Option
    Queen's University, Kingston, Ontario, Canada
    Advisor:
    Abdol-Reza Mansouri
    • GPA - 4.12/4.3
    • Dean's Scholar Designation - (2015, 2016, 2017, 2018)

Papers

  • 2024
    • Eisen, A.J.*, Kozachkov, L.*, Bastos, A.M., Donoghue, J.A., Mahnke, M.K., Brincat, S.L., Chandra, S., Brown, E.N., Fiete, I.R., and Miller, E.K. “Propofol anesthesia destabilizes neural dynamics across cortex” Neuron (2024). [Link]
    • Ostrow, M., Eisen, A.J., and Fiete, I.R. "Delay Embedding Theory of Neural Sequence Models" ICML Workshop on Next Generation Sequence Models (2024). [Link]
  • 2023
    • Ostrow, M., Eisen, A.J., Kozachkov, L., and Fiete, I.R. "Beyond Geometry: Comparing the Temporal Structure of Computation in Neural Circuits with Dynamical Similarity Analysis" Neural Information Processing Systems (2023). [Link]
  • 2018
    • Das, S., Eisen, A.J., Lin, Y.H., Chan, H.S. “A lattice model of charge-pattern- dependent polyampholyte phase separation” The Journal of Physical Chemistry B (2018) [Link]

Research and Work Experience

  • Sep 2020 - Present
    Graduate Student
    MIT, Cambridge, MA
    Advisors:
    Prof. Earl K. Miller and Ila R. Fiete
    • Developed a novel approach to analyzing the stabiltiy of neural dynamics, leveraging tools from dynamical systems theory
    • Demonstrated that propofol anesthesia destabilizes neural dynamics through comprehensive large-scale data processing, analysis, and visualization
    • Constructed a novel metric for comparing the dynamics between systems, and applied it to disentangle machine learning rules
  • Sep 2018 - Aug 2020
    Research and Development
    Heliolytics, Toronto, ON, Canada
    • Developed and integrated machine learning and computer-vision algorithms for pixel-level aerial image matching, improving accuracy from about 75% to 99.9%
    • Designed and constructed a distributed network of computing and monitoring systems to implement high volume image processing and analysis pipelines
    • Constructed a framework using quantitative metrics and statistics to assess algorithm performance and improvement
  • Sep 2017 - Apr 2018
    Senior Thesis Student
    Queen's University Department of Mathematics and Engineering, Kingston, ON, Canada
    Advisor:
    Prof. Abdol-Reza Mansouri
    • Thesis: "Image restoration algorithms for musical style transfer"
    • Applied machine learning and computer vision to learn a musical style, and adapted a stochastic image model and Markov chain Monte Carlo methods to transform audio samples into the learned style
  • May 2017 - Aug 2017
    Machine Learning Researcher
    The Hospital for Sick Children Department of Genetics & Genome Biology, Toronto, ON, Canada
    Advisor:
    Prof. Lisa Strug
    • Built and tested deep learning models for predicting the likelihood of comorbidities in patients with cystic fibrosis based on genetic data
    • Analyzed and compared the predictive power of additional models including random forests and penalized regressions
  • May 2016 - Aug 2016
    Research Assistant
    University of Toronto Department of Biochemistry, Toronto, ON, Canada
    Advisors:
    Prof. Hue Sun Chan and Lewis Kay
    • Optimized and expanded a C++ model to carry out Monte Carlo simulations of interactions among charged polymers leading to polymer phase separation
    • Validated an analytic theory regarding polymer radius of gyration

Talks

  • May 24, 2023
    • The Science of Consciousness Conference, Taormina, Italy
    • Title: "Propofol anesthesia destabilizes neural dynamics across cortex"
  • January 26, 2022
    • The MetaConscious (Yang) Lab, MIT, Cambridge, MA
    • Title: "Propofol anesthesia destabilizes neural dynamics across cortex"

Writing

  • 2023
    • Eisen, A.J. “Mapping the Mountains and Valleys of the Mind” MIND OCEAN SPACE (2024). [Link]

Distinctions and Awards

  • 2020, 2021
    • Singleton Fellowship
  • 2018
    • Annie Bentley Lillie Prize in Mathematics, awarded to the graduating student in Mathematics and Engineering who has the highest average on courses in mathematics in the final year
    • Keyser Prize, awarded to the two best Mathematics and Engineering theses
  • 2017
    • Nellie and Ralph Jeffrey Award in Mathematics, awarded to the student entering the fourth year of the Mathematics and Engineering program, or of an honours program with a Mathematics major, having the highest standing in the mathematics courses of the first three years and an overall first-class average
  • 2016
    • Nellie and Ralph Jeffrey Award in Mathematics
    • Susan Near Scholarship, for standing on year's work
  • 2015
    • H. Janzen Memorial Scholarship, awarded annually to the student who attained the highest standing in the first year physics courses in Applied Science
    • R.L. Dorrance Memorial Scholarship, given by the Engineering Society for highest standing in the first year chemistry courses in Applied Science
    • Annie Bentley Lillie Prize in First Year Calculus, awarded to students with high standing in any first year calculus course
  • 2014
    • Carl Reinhardt Entrance Scholarship in Physics, for high standing in physics
    • Principal's Entrance Scholarship, for obtaining grade 12 average of 98%
    • Valedictorian of the high school graduating class, selected by peers and faculty

Conferences

  • 2024
    • Ostrow, M., Eisen, A.J., et al. "Beyond Geometry: Comparing the Temporal Structure of Neural Computation with Dynamical Similarity Analysis" (Oral Presentation)
      Computational and Systems Neuroscience, 2024, Lisbon, Portugal
  • 2023
    • Ostrow, M., Eisen, A.J., et al. "Beyond Geometry: Comparing the Temporal Structure of Computation in Neural Circuits with Dynamical Similarity Analysis"
      Neural Information Processing Systems, 2023, New Orleans, LA
    • Ostrow, M., Eisen, A.J., et al. "Beyond Geometry: Comparing the Temporal Structure of Computation in Neural Circuits with Dynamic Mode Representational Similarity Analysis" (Oral Presentation)
      Computational Cognitive Neuroscience, 2023, Oxford, United Kingdom
    • Eisen, A.J., et al. "Propofol anesthesia destabilizes neural dynamics across cortex" (Oral Presentation)
      The Science of Consciousness Conference, 2023, Taormina, Italy
    • Eisen, A.J., et al. “Propofol anesthesia destabilizes neural dynamics across cortex"
      Computational and Systems Neuroscience, 2023, Montreal, QC, Canada
  • 2022
    • Eisen, A.J., et al. "Propofol anesthesia destabilizes neural dynamics across cortex"
      Society for Neuroscience 2022, San Diego, CA
  • 2021
    • Eisen, A.J., et al. "Propofol anesthesia changes dynamic stability in cortex" (Virtual)
      Society for Neuroscience 2021, Chicago, IL

Teaching and Mentoring Experience

  • Sep 2021 - Apr 2024
    Application Assistance Mentor
    Brain and Cognitive Sciences Application Assistance Program, MIT, Cambridge, MA, USA
    • Guided more than 15 propsective applicants to Brain and Cognitive Sciences through the application process
    • Provided constructive feedback on statements of purpose, CVs, and other application materials
    • Assissted applicants in identifying programs and advisors that aligned with their research interests and career goals
  • Sep 2023 - Dec 2023
    Mentor
    Mentee:
    Nicole Wong, Undergraduate Researcher at MIT
    • Provided instruction on dynamical systems theory concepts and practice
  • Jan 2023 - Apr 2023
    Teaching Assistant
    Massachusetts Institute of Technology, Cambridge, MA, USA
    Course:
    MIT 9.40, Introduction to Neural Computation
    • Led recitations, conducted review sessions, and held office hours
    • Awarded an overall rating of 6.4/7 in student feedback surveys, the highest of all instructors for the course in 2023
  • Sep 2021 - Dec 2021
    Teaching Assistant
    Massachusetts Institute of Technology, Cambridge, MA, USA
    Course:
    MIT 9.07, Statistics for Brain and Cognitive Sciences
    • Led recitations, conducted review sessions and office hours, and filled in as primary lecturer when the instructor was unavailable
    • Awarded an overall rating of 6.5/7 in student feedback surveys, the highest of all instructors for the course in 2021
    • Student feedback said "He went above and beyond for the people in the class which I really appreciated. He was always full of energy and answered questions with a smile."
  • Sep 2016 - Apr 2018
    Tutor and Workshop Leader
    EngLinks Tutoring, Queen's University, Kingston, ON, Canada
    • Prepared materials and conducted in-depth exam workshops for courses such as Differential Equations, Real Analysis and Electricity and Magnetism
      • Led workshops of 60-100 students
  • May 2015 - Jul 2015
    Private Tutor
    Toronto, ON, Canada
    • Delivered tutoring services in math, science and jazz history to 10 high school and university-level students, with successful academic outcomes

Technical Skills

  • Languages: Python, MATLAB, R
  • Packages: PyTorch, PyTorch Lightning, scikit-learn, SciPy, LaTeX
  • Developer Tools: Git, Slurm
  • Mathematics (Selected Topics): Dynamical Systems Theory, Linear Algebra, Calculus, Probability Theory, Information Theory, Operator Theory

Additional Information

  • Musical composition and performance
    • Co-writer, musician and performer with Erez Zobary (Jul 2019 - Present)
    • Released an EP under moniker Kodachrome (Nov 2016)
    • Vocal and piano performer and teacher (Sep 2010 – Apr 2018)
  • Athletics
    • Yoga, hiking, running, cycling, resistance training
    • Completed sprint triathlon (Aug 2018)