Matt Pfile

Matt Pfile is the founder and CEO of Crane Data Centers Inc., a data center developer and operator with a strong commitment to sustainability, customer centricity, and innovation. He has over 25 years of experience in telecom engineering, critical infrastructure acquisition, corporate banking, management consulting, and commercial negotiations. Prior to Crane, he spent 12+ years at Google leading over $5B of global infrastructure acquisitions and led the entry of Google Cloud Platform (GCP) into Australia and Japan, data center site selection strategy, third-party data center leasing, utility interconnections, and land acquisitions across the Americas and Asia. He received a degree in finance from Georgetown University and an MBA from Washington University in St. Louis.

Assaf Gad

Assaf Gad is the Chief Strategy Officer and General Manager at Intuition Robotics, focusing on bridging the gap between technology and real-world challenges, particularly for vulnerable populations. A seasoned product leader, Gad's career is driven by a passion for creating innovative user experiences using cutting-edge technology, creative problem-solving, and business insight.

With extensive experience in both hardware and software product development, Gad has led teams from ideation to market, emphasizing meaningful technology. He uses storytelling to connect technology with people, highlighting the interplay between user experience, innovation, and consumer brands.

Gad has a history of pioneering new user experiences. At N-trig, he introduced digital writing technologies that led to its acquisition by Microsoft for the Surface portfolio. At PointGrab, he integrated computer vision solutions into devices by Samsung, TCL, and Lenovo. Prior to Intuition Robotics, he led marketing and strategic partnerships at Audioburst and mentors startups at Techstars Barclays Accelerator in Tel Aviv. He also held leadership roles at Powermat Technologies, modu Mobile, and Telmap Ltd (acquired by Intel). Gad holds a BSc. in Computer Science from The Interdisciplinary Center Herzliya.

Steven Woo

I was drawn to Rambus to focus on cutting edge computing technologies. Throughout my 15+ year career, I’ve helped invent, create and develop means of driving and extending performance in both hardware and software solutions. At Rambus, we are solving challenges that are completely new to the industry and occur as a response to deployments that are highly sophisticated and advanced.

As an inventor, I find myself approaching a challenge like a room filled with 100,000 pieces of a puzzle where it is my job to figure out how they all go together – without knowing what it is supposed to look like in the end. For me, the job of finishing the puzzle is as enjoyable as the actual process of coming up with a new, innovative solution.

For example, RDRAM®, our first mainstream memory architecture, implemented in hundreds of millions of consumer, computing and networking products from leading electronics companies including Cisco, Dell, Hitachi, HP, Intel, etc. We did a lot of novel things that required inventiveness – we pushed the envelope and created state of the art performance without making actual changes to the infrastructure.

I’m excited about the new opportunities as computing is becoming more and more pervasive in our everyday lives. With a world full of data, my job and my fellow inventors’ job will be to stay curious, maintain an inquisitive approach and create solutions that are technologically superior and that seamlessly intertwine with our daily lives.

After an inspiring work day at Rambus, I enjoy spending time with my family, being outdoors, swimming, and reading.

Education

• Ph.D., Electrical Engineering, Stanford University
• M.S. Electrical Engineering, Stanford University
• Master of Engineering, Harvey Mudd College
• B.S. Engineering, Harvey Mudd College

Shreya Singhal

Shreya Singhal works in Generative AI Research & Development at Aristocrat Gaming and is a Graduate Research Assistant at the University of Texas at Austin. Her work spans large language models (LLMs), reinforcement learning, and optimization for scalable and interpretable AI systems.

Shreya has hands-on experience fine-tuning open-source models like Gemma 2B for under-resourced languages, deploying compressed generative models in low-resource environments, and implementing bias and fairness evaluation pipelines using interpretable subspace analysis. She has previously worked at Dell Technologies, Charles Schwab, Deloitte, and Accenture, contributing to AI-powered solutions across gaming, finance, and enterprise automation.

Her current research focuses on efficient LLM training and evaluation pipelines, fairness-aware model design, and bringing generative AI to edge and enterprise use cases. She is passionate about making AI more inclusive, scalable, and grounded in real-world constraints.