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HSRPAIN

Vision (borrowed from Kempner)

HSRPAIN seeks to build a community of scholars who work across boundaries and fields and are poised to solve some of the most compelling mysteries of our time. Coming together to learn, collaborate, and discover – HSRPAIN members are scientists who seek to fundamentally and radically advance our understanding of Natural and Artificial Intelligence.

Mission

The mission of HSRPAIN is to understand the basis of intelligence in natural and artificial systems. The program will strive collectively to reveal the fundamental mechanisms of intelligence, endow artificial intelligence (AI) with features of natural intelligence, and apply these new AI technologies for the benefit of humanity.

HSRPAIN will recruit and train future generations of researchers to study intelligence from biological, cognitive, engineering, and computational perspectives.  It will elevate Harvard University’s standing in AI to the top ranks while expanding the national capacity to nurture new talent and develop expertise in a critical area of science and technology. Thus, the program will:

  1. Advance a fundamental and unified understanding of the nature of intelligence that has evolved in organisms and can be engineered in silico
  2. Train the next generation of researchers to work collaboratively across disciplines and to become versed in relevant areas of computational theory, AI and machine learning (ML), neuroscience, and cognitive science
  3. Translate theoretical advances to the development of next generation AI systems with qualitatively better capabilities for deeper reasoning and more efficient use of data
  4. Use knowledge gained from the study of AI systems to explain how the brain processes information, computes, learns and guides action
  5. Contextualize research via application challenges from complex domains of importance to humanity

Values

HSRPAIN members are expected to model and support the following:

  • Rigor in thought and research
  • Constructive collaboration and community building
  • Diversity
  • Inclusivity, respect, and honesty in communication and action
  • Curiosity to discover, connect, and understand
  • A commitment to make the world a better place

Interest form https://forms.gle/9ZpaRZDVjiVarYEj9

Background

Dartmouth Summer Research Program on AI effectively created the field of AI: https://home.dartmouth.edu/about/artificial-intelligence-ai-coined-dartmouth

Last year, I tried to put together a Harvard Workshop on AI Safety (https://docs.google.com/document/d/1e7nfXMIyDWllundoQRKW9O_rL8EF3mZMVt9nwTVu1tU/edit#heading=h.ayy045golo75). This year, I'm envisioning a Harvard Summer Research Program on AI Neuroscience, instead.

I'm assembling a team of all-star student researchers from around the world for this fellowship (all TBC):

C House Residents (2)

  1. Isaak Freeman from MIT, who's working on Worm Brain Simulations at Boyden's lab
  2. Vik Gupta, Media Lab, Fluid Interfaces and Trinity Dysis, Harvard, CBI @ Harvard
  3. Dünya Baradari, MIT Media Lab
  4. Alexey Guzey, MIT, Physics universal resurrection

The Residency (2)

  1. Lauren Pearson, UofT, Glioblastoma research
  2. Theo Wang, Cambridge, Neurosymbolic programming
  3. Anshul Kashyap, Berkeley, Light-based neuron stimulation

Harvard (2)

  1. Aneesh Muppidi, Harvard, CNUGS
  2. Noah Evers, Harvard, Neuro major
  3. Ege Cakar, Harvard Kempner, KRANIUM

Previous collaborators (2)

  1. Shayan Chowdhury, Columbia, AI in Medicine at HMS
  2. Viraj Chhajed, UCLA, Biological neurons playing Pong
  • Italicized means in the house currently. Bold means organizers. ? means haven’t confirmed yet.

Proposed Mentors:

  1. Prof Gabriel Kreiman - Alzheimer’s Brain Cloning
  2. Prof Kanaka Rajan - Fly Brain Simulation
  3. Prof Tomer Ullman - Intuitive Psychology
  4. Researchers at the Columbia Zuckerman Institute
    1. Prof Richard Zemel - Director of NSF AI Institute for ARtificial and Natural Intelligence (ARNI)
    2. Prof Smaranda Muresan - LLMs
    3. Prof Luis Gravano - CS and information retrieval (RAG)
    4. Prof Peter Balsam - Chair of Neuroscience and Behavior
  5. Find ppl doing research on how hormones affect the brain
  6. Harvard Innovation Labs

Interest form https://forms.gle/9ZpaRZDVjiVarYEj9

Details

  • Location: 352 Harvard St, Cambridge, MA 02138
  • If you can’t pay rent, I can cover it + a stipend in exchange for 2% of a future company
  • I can provide compute

There are a number of potential topics for research in AI neuroscience. Some examples include:

  • Prosthetics: returning motor function. An example of this would be LimbX
  • In vitro experiments: culturing neurons and training them.
  • Computational simulations: new methods for understanding and modeling the brain
  • Oncology: applying AI techniques to study neurological disorders and disease (e.g. glioblastoma) -
  • Implants and sensors: developing AI systems that can interact with the brain
  • Philosophy: exploring the ethical implications of AI neuroscience research.

There are a number of challenges in conducting research in AI neuroscience. Some of these challenges include:

  • The complexity of the brain. The brain is a complex organ with a vast number of neurons and connections. This makes it difficult to study and understand how the brain works.
  • The ethical implications of AI neuroscience research. AI neuroscience research raises a number of ethical issues, such as the potential for bias and discrimination, the potential for creating harmful or dangerous AI systems, and the need to protect privacy.
  • The need for interdisciplinary collaboration. AI neuroscience research requires a high level of interdisciplinary collaboration between researchers from different fields, such as computer science, neuroscience, and ethics.
  • The need for large datasets. AI neuroscience research often requires large datasets of brain imaging data and other data. These datasets can be difficult and expensive to obtain.
  • The need for specialized equipment. AI neuroscience research often requires specialized equipment, such as brain imaging scanners and electrophysiological recording devices. This equipment can be expensive and require specialized training to use

Proposed Program:

June - August (10-12 weeks)

  1. Weekly
    1. Stand-ups
    2. Lunches/Dinners
    3. Lectures/seminars
  2. Monthly
    1. Conference
    2. Travel
    3. Research reports
  3. Inspiration: BMM Camp 8/4-25
    1. https://www.mbl.edu/education/advanced-research-training-courses/course-offerings/brains-minds-and-machines
    2. See https://twitter.com/gkreiman/status/1762499262750113800/quotes
  4. By summer end
    1. Published research (own site/journal)
    2. Sparks Breakthrough
    3. Friends

Interest form https://forms.gle/9ZpaRZDVjiVarYEj9

Alt description

The program would also include a series of lectures and workshops led by world-renowned AI and neuroscience researchers. Students would also have the opportunity to work on their own research projects under the supervision of a faculty mentor.

This curriculum would provide students with a comprehensive overview of AI neuroscience and the tools and techniques used in this field. It would also give students the opportunity to conduct their own research and to develop their own research skills.

HSRPAIN brings together a diverse group of top student researchers from around the world to work on cutting-edge AI neuroscience research. We foster an environment where students can collaborate and learn from each other, and provide students with the opportunity to work with world-renowned AI and neuroscience researchers.