Joshua Shay Kricheli v2 / beta

Computer Science PhD · Syracuse University

Models that learn & logic that verifies.

I’m a NeuroSymbolic AI researcher at the Leibniz Lab, working on systems that combine statistical learning with rigorous logic — and that can detect, explain, and recover from their own errors. Advised by Prof. Paulo Shakarian.

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Joshua Shay Kricheli
Syracuse, New York, USA 2018 - Present
8+
Years experience
0
Peer-reviewed publications
0
Talks & essays
0
Awards & fellowships

00 — About

Engineer, computer scientist, working at the intersection of logic and learning.

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I work on NeuroSymbolic AI — systems that fuse statistical learning with rigorous logic so they can detect, explain, and recover from their own errors, without leaning on ground-truth labels. That thread runs from large-scale LLM pretraining and scaling laws to robotics and modern control, and it grew out of shipping real systems in industry before I returned to research.

I’m a 3rd-year Computer Science Ph.D. student and a Research Associate at the Leibniz NeuroSymbolic Lab at Syracuse University (SU), New York, USA, under Prof. Paulo Shakarian. I recently served as a Visiting Researcher with the Learning Sciences group at the Institute for Creative Technologies (ICT), University of Southern California (USC).

Until 2023 I was an AI/ML Researcher at Ben-Gurion University of the Negev (BGU), Israel, where I co-founded Prof. Gera Weiss and Prof. Shai Arogeti’s Intelligent Robotics Lab (IRL). I hold an M.Sc. in Computer Science and a B.Sc. in Mechanical Engineering, both from BGU — the mechanical-engineering start is where my interest in control and autonomous systems began.

News

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Research focus

Where my work lives.

Three threads run through everything I build — together they shape the questions I ask and the systems I help bring into the world.

  1. 01

    NeuroSymbolic AI

    Infusing statistical neural models with rigorous logic so that learned systems can reason, justify, and recover from their own errors — the core of my PhD work.

  2. 02

    Machine Learning

    From hierarchical multi-label classification to LLM scaling laws and agentic frameworks for education — applied ML on real problems with real constraints.

  3. 03

    Robotics & Control

    Differential games and modern control theory for autonomous systems handling competing objectives — bridging the mechanical engineering that started my path with the AI that continues it.

01 — Education

Three degrees, one trajectory.

From mechanical engineering to computer science to a PhD in NeuroSymbolic AI — each step a deliberate move toward the questions I find most worth answering.

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02 — Experience

A research-and-engineering path across labs and continents.

Roles at Syracuse, ICT@USC, ASU, BGU, Dell, and Intel — always at the boundary of research and shipped systems.

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03 — Publications

Peer-reviewed work.

Papers across NeuroSymbolic AI, hierarchical multi-label classification, vision-language sensor fusion, and differential games for control.

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04 — Teaching & Talks

Sharing the work.

Courses I’ve taught, talks I’ve given, and essays I’ve written — the public-facing side of the research.

Teaching

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Talks & Essays

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05 — Recognition

Selected fellowships, scholarships, and awards.

Funding and recognition that has supported my path from Israel to the United States, across mechanical engineering, AI, and security-focused research.

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06 — News

What’s happening lately.

A live feed from my research life — new papers, talks, affiliations, and milestones.

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