Principal Engineer & Research Manager  ·  Intel

Saurav Sahay
AI Researcher & Leader

14+ years advancing safe, responsible, and intelligent AI systems.
Specializing in AI Safety, Agentic AI, Conversational AI, and Multimodal AI at Intel Labs. Ph.D., Georgia Institute of Technology.

14+
Years in AI
30+
Publications
5
Patents

About

Building AI that is powerful and trustworthy

I am a Principal Engineer and Research Engineering Manager at Intel's AI Innovation Group, where I lead research across two interconnected frontiers: Agentic AI systems — including cost-aware planning, routing, and orchestration for heterogeneous inference environments — and AI Safety, with active published research on efficient guardrail systems that make safe, responsible LLM deployment practical at scale. I also contribute to Intel's Responsible AI policy development and internal compliance programs.

Beyond Intel, I actively contribute to the MLCommons AI Risk & Reliability (AIRR) working group, co-authoring benchmarks and methodologies covering model security, jailbreak robustness, and agentic AI safety evaluation. My research spans the full spectrum of modern AI: from foundational NLP and dialog systems to LLM safety, bias detection, and enterprise AI adaptation for industrial environments.

I hold a Ph.D. in Computer Science from Georgia Institute of Technology, where my dissertation explored Socio-Semantic Conversational Information Access. Before Intel, I built healthcare AI at Siemens, worked on IBM's Watson (DeepQA) project, and co-founded a venture-backed healthcare AI startup. I serve on the program committees of ICML, NeurIPS, ICLR, ACL, EMNLP, and COLM.

Core Expertise

🛡️
AI Safety & Responsible AI
LLM safety benchmarking (MLCommons AIRR), jailbreak robustness methodology, RAI policy, bias detection, and production guardrail systems.
🤖
Agentic AI Systems
Multi-agent architectures with cost-aware planning, routing, and orchestration for heterogeneous inference. Agentic product maturity frameworks.
💬
Conversational AI
15+ years building dialog systems, NLU pipelines, and task-oriented agents across education, manufacturing, and assistive technology.
🧠
Large Language Models
Domain adaptation, PEFT, knowledge-enhanced LLMs, red-teaming for enterprise, and bias mitigation through model merging and fine-tuning.
👁️
Multimodal AI
Vision-language systems, multimodal fusion architectures, emotion understanding, and task guidance systems for industrial smart manufacturing.
🎓
Research Leadership
Managing distributed teams across US, Mexico, Germany, and Taiwan. University partnerships, grant writing experience, and mentorship.

Experience

Career Timeline

Principal Engineer & Research Engineering Manager Sept 2025 – Present
Multimodal Dialog & Interaction (MDI) · AI Innovation Group · Intel

Leading pathfinding research on Agentic AI systems: cost-aware planning, routing, guardrails, and orchestration within heterogeneous inference system development. Core contributor to Intel's Responsible AI policy development and internal compliance programs.

Contributor / Volunteer Jan 2024 – Present
MLCommons AI Risk & Reliability (AIRR) Working Group

Active contributor on LLM model evaluations, security (jailbreaks), and agentic benchmark development. Co-author of the AI Safety Benchmark v0.5 and the jailbreak robustness methodology pre-print.

Principal Engineer & AI Research Science Manager Feb 2024 – Aug 2025
Multimodal Dialog & Interaction Lab · Intelligent Systems Research Division · Intel Labs

Led a team on LLM applications spanning Responsible AI and Agentic AI: domain adaptation for enterprise data, agentic analytics for semiconductor manufacturing sensor data, and multimodal task guidance for industrial smart manufacturing.

Staff Scientist & Manager Feb 2019 – Jan 2024
Multimodal Dialog & Interaction Lab · Intelligent Systems Research Division · Intel Labs

Led a globally distributed team of scientists and contractors across the US, Mexico, Germany, and Taiwan. Delivered projects in education (multimodal dialog systems), manufacturing (vision-language systems), collaboration (multimodal meeting assistance), and assistive computing. Managed university-funded research on Few-Shot Learning and Dialog Systems. Core member of Intel's Responsible AI Council.

Senior Research Scientist Feb 2017 – Feb 2019
Anticipatory Computing Lab · Software & System Research Division · Intel Labs

Multimodal emotion understanding and dialog systems. Extended NLU and dialog management algorithms for the open-source Rasa platform. Led researchers and interns in a tech-lead capacity.

Research Scientist Oct 2012 – Feb 2017
Anticipatory Computing Lab · Software & System Research Division · Intel Labs

Developed the Cognitive Linguistics Information Platform featuring keyterm extraction, intent recognition, colloquial text normalization, knowledge-based missing information fulfillment, topic discovery, and sentiment analysis.

Research Scientist Aug 2011 – Oct 2012
Translational Informatics & Special Projects · Siemens Corporate Research · Princeton, NJ

Healthcare decision support, text analytics, semantic search, ontology-based reasoning, and data mining for patient-physician information systems.

CTO & Co-founder Aug 2010 – July 2011
Cobot Health Corporation · Georgia Tech VentureLab Spin-out

Founded a healthcare AI startup based on dissertation research with venture funding from Georgia Tech's VentureLab. Developed and deployed the Cobot Intelligent Assistant widget on a third-party platform.

Research Intern Summers 2005, 2006, 2010
IBM T.J. Watson Research Center · Hawthorne, NY & New Delhi, India

Contributed to the Watson (DeepQA) project with the medical team. Built biomedical semantic search and relation extraction systems. Customized the Slot Grammar Parser for medical ontologies and ontology-based semantic distances for improved answer-type detection.

Research

Selected Publications

Recent and representative work — spanning AI Safety, Agentic AI, LLMs, and Conversational AI. Full list on Google Scholar.

A Robust, Defensible, and Reproducible Methodology for Benchmarking Single-Turn Jailbreak Attacks on Large Language Models
Carsten Maple, Saurav Sahay, et al.
MLCommons · 2026 ↗ Paper
Agentic Product Maturity Ladder V0.1
Sean McGregor, Saurav Sahay, et al.
MLCommons · 2026 ↗ Paper
AILuminate: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons
Shaona Ghosh, Saurav Sahay, et al.
ArXiv 2503.05731 · 2025
Safeguard Fine-Tuned LLMs Through Pre- and Post-Tuning Model Merging
Hua Farn, Hsuan Su, Shachi H Kumar, Saurav Sahay, Shang-Tse Chen, Hung-yi Lee
EMNLP Findings · 2025 ↗ ArXiv
Thoughts without Thinking: Reconsidering the Explanatory Value of Chain-of-Thought Reasoning in LLMs through Agentic Pipelines
Ramesh Manuvinakurike, Emanuel Moss, Elizabeth Watkins, Saurav Sahay, et al.
HCXAI @ CHI · 2025 ↗ ArXiv
Decoding Biases: Automated Methods and LLM Judges for Gender Bias Detection in Language Models
Shachi H Kumar, Saurav Sahay, Sahisnu Mazumder, Eda Okur, Ramesh Manuvinakurike, et al.
NeurIPS 2024 · Red Teaming GenAI Workshop
Introducing v0.5 of the AI Safety Benchmark from MLCommons
Bertie Vidgen, Saurav Sahay, et al.
ArXiv 2404.12241 · 2024
Systematic Analysis for Pretrained Language Model Priming for Parameter-Efficient Fine-tuning
Shih-Cheng Huang, Shih-Heng Wang, Min-Han Shih, Saurav Sahay, Hung-yi Lee
NAACL · 2024
Learning from Red Teaming: Gender Bias Provocation and Mitigation in Large Language Models
Hsuan Su, Cheng-Chu Farn, Shachi H Kumar, Saurav Sahay, Shang-Tse Chen, Hung-yi Lee
ArXiv 2310.11079 · 2023
Low Rank Fusion based Transformers for Multimodal Sequences
Saurav Sahay, Eda Okur, Shachi H Kumar, Lama Nachman
ACL · Human Multimodal Language Workshop · 2020
Technology Solutions to Combat Online Harassment
George Kennedy, Andrew McCollough, Edward Dixon, Alexei Bastidas, John Ryan, Chris Loo, Saurav Sahay
ACL · Workshop on Abusive Language Online · 2017
View all 30+ publications on Google Scholar ↗

Patents

US 10,380,256 Technologies for Automated Context-Aware Media Curation — Nachman, Sahay et al. (2019)
US 9,781,392 Saurav Sahay, Nachman et al. — Facilitating Personal Assistance for Curation of Multimedia and Generation of Stories (2017)
WO2016105803 Pereg, Wasserblat, Sahay et al. — Hybrid Techniques for Sentiment Analysis (2016)
US20180174244 Savage, Nachman, Sahay, Raffa — Socially and Contextually Appropriate Recommendation Systems (2015)
US 9,948,689 Savage, Wouhaybi, Nachman, Sahay — Online Social Persona Management (2014)

Program Committee & Community Service

ICML NeurIPS ICLR ACL EMNLP COLM MLCommons AIRR Intel Responsible AI Council

Technical Skills

Languages
Python Java C++ C Perl
Frameworks
PyTorch Transformers vLLM OpenVINO Ray Rasa
Tools
Docker Kubernetes Git Slurm

Thought Leadership

Writing & Commentary

On AI Safety, bias in language models, and responsible development of intelligent systems.

✍️
Understanding and Addressing Bias in Conversational AI
An in-depth exploration of the challenges in building fair, transparent, and safe conversational AI systems — covering sources of bias in language models, mitigation strategies, and practical approaches for responsible deployment. Published on Intel Technology Community.
Intel Technology Community Portal

Education

Academic Background

Ph.D., Computer Science
Georgia Institute of Technology
2004 – 2011  ·  Atlanta, Georgia
Thesis: Socio-Semantic Conversational Information Access
M.S., Computer Science
Georgia Institute of Technology
2004 – 2009  ·  Atlanta, Georgia
Also completed coursework for the MS Bioinformatics program

Connect

Get in Touch

Open to conversations about AI Safety, Responsible AI, Agentic systems, research collaborations, and speaking opportunities.