Michael Bahr

Mike Bahr joined DRW Holdings in 2013 and has built co-locations and stand-alone data centers for trading firms all over the world. Mike is also in charge of all MEP designs for all company offices globally. Mike also is co-founder of a start-up, Co-Low.com, a true subscription based colocation/data center finder for all IT needs. Mike lives in Crown Point, IN with his wife Colleen and his four children.

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.

Aswini Atibudhi

Aswini is a Distinguished Architect at Walmart Global Tech, with over 22 years of IT experience in designing scalable AI/ML, micro frontend, microservices, and cloud applications. His professional expertise encompasses diverse domains including  e-commerce, finance, telecom and healthcare meticulously developed through his tenure at Walmart, Cisco, Equinix, Finastra, and TCS. Over seven years at Walmart, he has been a founding member of critical platforms like Last Mile Delivery, Fleet Management, MerchOne, Supplier Portal and several others. As a recognized expert in generative AI, Aswini specializes in leveraging machine learning and large language models to create transformative digital experiences, including personalized content generation and AI-driven customer engagement.

He has received numerous awards including Walmart’s Innovation Award, Equinix’s Top Performer Award, and Cisco’s Group Race Award. With many certifications in AI, machine learning, and cloud technologies, he stays at the forefront of innovation. Known for his strategic insights, Aswini has a proven ability to deliver transformative AI solutions across industries. 

Prashanth Thinakaran

Prashanth Thinakaran is a Distinguished AI Infrastructure Engineer at Clockwork Systems, a pioneer in nano-second precise network telemetry and software-driven resilience that addresses the unprecedented scale, performance, and reliability Modern AI workloads demand from GPU clusters. In this role, he partners with AI Infrastructure teams at enterprises, hyperscalers and neoclouds to increase their visibility into issues impacting cluster uptime and optimize their availability and utilization with Clockwork’s solution. 

Previously, he helped AI-native companies build on cloud-based GPU platforms, providing deep technical guidance on distributed training and inference, multi-node scaling, and performance tuning across complex infrastructure stacks. His Neocloud experience bridged the gap between product engineering and customer enablement, helping fast-moving teams adopt best practices in massive-scale model deployment and operations. Prior to that, Prashanth played a pivotal role at Cerebras Systems -  a market leader in high-speed inferencing, - in the design, and deployment of Condor Galaxy 1, a Wafer-scale supercomputer. His work enabled rapid deployment timelines and seamless scaling of AI infrastructure across globally distributed data centers designed for both Inference and Training.

Prashanth also holds a Ph.D. in Computer Science and Engineering from Penn State, where his research focused on high-performance computing and cloud systems. His academic work has been published in top-tier venues including USENIX NSDI, ACM Middleware, ICDCS, and ACM SoCC. He has authored over a dozen peer-reviewed papers and a book chapter, and served as a reviewer for journals such as IEEE TPDS and TCC. During his Ph.D., he held teaching roles in systems programming, and computer architecture, and collaborated with Intel, VMware, and Adobe Research through internships, solving systems challenges at the intersection of academia and industry.