Dr. Ruchir Puri is the Chief Scientist of IBM Research, an IBM Fellow, and Vice-President of IBM Corporate Technology and Technical Community. He led IBM Watson as its CTO and Chief Architect from 2016-19 and has held various technical, research, and engineering leadership roles across IBM’s AI and Research businesses. Dr. Puri is a Fellow of the IEEE, and has been an ACM Distinguished Speaker, an IEEE Distinguished Lecturer, and was awarded 2014 Asian American Engineer of the Year. Ruchir is the recipient of the prestigious Distinguished Alumnus Award from Indian Institute of Technology (IIT), Kanpur and has been an adjunct professor at Columbia University, NY, and a visiting scientist at Stanford University, CA. He was honored with John Von-Neumann Chair at Institute of Discrete Mathematics at Bonn University, Germany. He is an inventor of over 70 US patents and has authored over 120 scientific papers. Specifying exact circuit algorithms in universal transformers Taku Ito Ruchir Puri et al. 2025 NeurIPS 2025 Workshop paper Specifying exact circuit algorithms in universal transformers Taku Ito Ruchir Puri et al. ITBench: Evaluating AI Agents across Diverse Real-World IT Automation Tasks Saurabh Jha Rohan Arora et al. 2025 ICML 2025 Conference paper ITBench: Evaluating AI Agents across Diverse Real-World IT Automation Tasks Saurabh Jha Rohan Arora et al. Customizing a Large Language Model for VHDL Design of High-Performance Microprocessors Nicolas Dupuis Ravi Nair et al. 2025 ICLAD 2025 Conference paper Customizing a Large Language Model for VHDL Design of High-Performance Microprocessors Nicolas Dupuis Ravi Nair et al. Agent Trajectory Explorer: Visualizing and Providing Feedback on Agent Trajectories Michael Desmond Ja Young Lee et al. 2025 AAAI 2025 Demo paper Agent Trajectory Explorer: Visualizing and Providing Feedback on Agent Trajectories Michael Desmond Ja Young Lee et al. Michael Desmond Transforming The Hybrid Cloud for Emerging AI Workloads Deming Chen Alaa Youssef et al. 2024 arXiv Paper Transforming The Hybrid Cloud for Emerging AI Workloads Deming Chen Alaa Youssef et al. Qiskit Code Assistant: Training LLMs for generating Quantum Computing Code Nicolas Dupuis Luca Buratti et al. 2024 LAD 2024 Conference paper Qiskit Code Assistant: Training LLMs for generating Quantum Computing Code Nicolas Dupuis Luca Buratti et al. Qiskit HumanEval: An evaluation benchmark for Quantum Code Generative Models Sanjay Kumar Lalta Prasad Vishwakarma Frank Harkins et al. 2024 QCE 2024 Conference paper Qiskit HumanEval: An evaluation benchmark for Quantum Code Generative Models Sanjay Kumar Lalta Prasad Vishwakarma Frank Harkins et al. Sanjay Kumar Lalta Prasad Vishwakarma Scaling Granite Code Models to 128K Context Matthew Stallone Vaibhav Saxena et al. 2024 arXiv Paper Scaling Granite Code Models to 128K Context Matthew Stallone Vaibhav Saxena et al. Matthew Stallone Ask-EDA: A Design Assistant Empowered by LLM, Hybrid RAG and Abbreviation De-hallucination Luyao Shi Michael Kazda et al. 2024 LAD 2024 Conference paper Ask-EDA: A Design Assistant Empowered by LLM, Hybrid RAG and Abbreviation De-hallucination Luyao Shi Michael Kazda et al. Granite code models: A family of open foundation models for code intelligence Mayank Mishra Matthew Stallone et al. 2024 arXiv Paper Granite code models: A family of open foundation models for code intelligence Mayank Mishra Matthew Stallone et al. Matthew Stallone

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