Moshe Mash, Ph.D.

AI Research Scientist | LLMs · NLP · Multi-Agent Systems

AI Research Scientist with a Ph.D. and Carnegie Mellon Robotics Institute postdoctoral fellowship, specializing in large language models, NLP, and multi-agent systems. Over a decade of experience translating research into production — built predictive systems at Amdocs saving millions annually, deployed clinical ML models at Diagnostic Robotics, and led NLP/LLM research at DICTA. Founder of MashInnovateAI. Published in JACM, AIJ, Science Translational Medicine, and CHI. Best Paper Award, ACM EC 2016. Research funded by J.P. Morgan.

moshikmash@gmail.com
+1-412-626-1676
Pittsburgh, PA · Open to remote & relocation
Moshe Mash, Ph.D.

Research & Skills

Applied AI AI Research Natural Language Processing LLM Fine-tuning RAG End-to-End Delivery (PoC → Production) Python PyTorch HuggingFace Transformers Production ML Reinforcement Learning Agentic AI Multi-Agent Systems Game Theory MDP Social Choice & Fair Division SQL Distributed Training Healthcare & Clinical ML Human-Centric AI Data Science Workflows

Professional Experience

Principal AI Researcher & Founder

MashInnovateAI 2024–Present
  • Independent AI R&D consultancy delivering end-to-end custom AI systems — NLP, LLM fine-tuning, RAG, agentic and multi-agent LLM systems, and applied ML — from proof of concept to production deployment
  • Clients include startups, established companies integrating AI into their products and workflows, and universities and academic research groups
  • Primary client: DICTA – The Israel Center for Text Analysis, continuing and expanding the NLP and LLM research agenda as an independent researcher

AI Researcher

DICTA – The Israel Center for Text Analysis 2022–Present
  • Lead research at the intersection of computational linguistics and Jewish studies, focusing on rabbinical and modern Hebrew
  • Developed NLP pipelines for authorship attribution, achieving high accuracy on long-debated questions of authorship in classical Jewish texts
  • Designed AI-driven systems for automatic citation generation and cross-referencing of classical sources
  • Built and deployed LLM-based tools actively used by scholars for live analysis of Hebrew texts
  • Tech: Python, PyTorch, HuggingFace Transformers, RAG, and classical NLP

Postdoctoral Researcher

Carnegie Mellon University, Robotics Institute 2019–2022
  • Hosted by Prof. Reid Simmons and Dr. Stephanie Rosenthal
  • Conducted research on the behavior and cognitive processes of ML practitioners as they develop AI models
  • Designed frameworks to capture, model, and analyze workflows, with emphasis on decision-making and iteration cycles
  • Developed predictive methods to identify critical moments of difficulty (“stuckness”) in ML development
  • Research funded by J.P. Morgan, which renewed the award for a second consecutive year
  • Mentored students in AI and human-computer interaction research

AI Researcher

Diagnostic Robotics 2019
  • Developed machine learning models for the healthcare domain, with applications in risk prediction
  • Collaborated with clinicians and researchers to refine AI-driven predictive healthcare decision-support systems

AI Researcher

Amdocs 2018–2019
  • Led the development of an innovative system predicting at-risk maintenance contract renewals, saving the company millions of dollars
  • Designed, built, and deployed the system from scratch, including problem definition, algorithm design, evaluation, and deployment pipeline

Research Assistant

Weizmann Institute of Science 2011–2012
  • Developed image-processing algorithms for 3D biomedical images

Research & Development for Technology Companies

As the founder of MashInnovateAI, I lead a company dedicated to unlocking the power of data and AI for technology companies. We provide expert analysis, custom AI tools, and ongoing support to help businesses transform complex information into actionable insights and drive real results.

Deep Data Analysis

Unlock insights with our deep data analysis, turning complex information into clear, actionable strategies.

Custom AI Tools

Tailored AI solutions built for your needs, enhancing efficiency and driving growth effortlessly.

Ongoing Support

Dedicated assistance to ensure your success, keeping your AI tools running smoothly and effectively.

Ph.D.
AI & Computer Science
Deep research expertise you can trust
10+
Years of AI Experience
Research to production, across industries
End-to-End
PoC → Production
From idea to deployed, maintained system

Education

Ph.D.

Software and Information Systems Engineering

Ben-Gurion University of the Negev

2014–2018

Dissertation: Reaching Fair Agreements in Group Settings
Advisor: Prof. Ya'akov (Kobi) Gal

M.Sc.

Computer Science (AI specialization)

Bar-Ilan University

2011–2013

Thesis: Joint Exploration with Self-Interested Agents
Advisor: Prof. David Sarne

B.Sc.

Software Engineering

Shenkar College of Engineering and Design

2007–2011

Awards & Recognition

Best Paper Award

ACM Conference on Economics and Computation (2016)

Excellence in Teaching Award

Ben-Gurion University (2016, 2017)

Ph.D. Scholarship for Academic Excellence

Ben-Gurion University (2014)

Selected Publications

Gendered Words and Patent Grant Rates: A Textual Analysis

Gerhardt D., Marcowitz-Bitton M., Schuster W.M., Elmalech A., Suissa O., Mash M.

Northwestern Journal of Technology and Intellectual Property, 23 Nw. J. Tech. & Intell. Prop. 509 (2026)

The T cell receptor landscape of childhood brain tumors

Raphael I, Xiong Z, Sneiderman CT, Raphael RA, Mash M., et al.

Science Translational Medicine, 17(790):eadp0675. 2025

Human-Computer Coalition Formation in Weighted Voting Games

Mash, M., Fairstein, R., Zick, Y., Bachrach, Y., & Gal, K.

ACM Transactions on Intelligent Systems and Technology (TIST). 2020

Which Is the Fairest (Rent Division) of Them All?

Gal, K., Mash, M., Procaccia, A., & Zick, Y.

Journal of the ACM (JACM). 2017

Joint Search with Self-Interested Agents and the Failure of Cooperation Enhancers

Rochlin, I., Sarne, D., & Mash, M.

Artificial Intelligence Journal (AIJ). 2014

Predicting Data Scientist Stuckness During the Development of Machine Learning Classifiers

Mash, M., Oryol, S., Rosenthal, S., & Simmons, R.

VL/HCC. 2022

DSWorkFlow: A Framework for Capturing Data Scientists' Workflows

Mash, M., Rosenthal, S., & Simmons, R.

CHI. 2021

How to Form Winning Coalitions in Mixed Human-Computer Settings

Mash, M., Zick, Y., Bachrach, Y., & Gal, K.

IJCAI. 2017

Which Is the Fairest (Rent Division) of Them All? Best Paper Award

Gal, K., Mash, M., Procaccia, A., & Zick, Y.

EC. 2016

Peer-Designed Agents for Reliably Evaluating the Distribution of Outcomes in Environments Involving People

Mash, M., Lin, R., & Sarne, D.

AAMAS. 2014

Join Me with the Weakest Partner, Please

Mash, M., Rochlin, I., & Sarne, D.

WI-IAT. 2012

Teaching & Professional Service

University Teaching

Taught and lectured at Ben-Gurion University, Tel-Aviv Yafo Academic College, Bar-Ilan University, and Shenkar College. Courses include Databases, Machine Learning, Game Theory, Intelligent Systems, and Software Design. Recipient of the Excellence in Teaching Award (2016, 2017).

Advising & Mentoring

Served as Final Projects Coordinator and Adviser for undergraduate students at Ben-Gurion University (2015–2018). Departmental Seminar Coordinator for four consecutive years. Mentored students in AI and HCI research at CMU.

Peer Review & Service

Reviewer for top AI venues: AAAI, IJCAI, AAMAS, KDD, CHI, EC, ECAI, and Group Decision & Negotiation. Developed the voting algorithm for IAAI 2018 Best Paper selection.

Curriculum Vitae

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