More About Me
Career Path
Now, I’m on the architecture team at d-Matrix, advancing the future of ultra-low-latency, sustainable LLM inference through the world’s first compute-in-memory accelerator. At d-Matrix, I optimize end-to-end hardware–software co-design for attention and mixture-of-experts (MoE) models, and collaborate closely with compiler, systems, and design teams to achieve orders-of-magnitude efficiency gains—all while wearing many hats in a fast-paced startup environment. What I appreciate most about this setting is the chance to tackle diverse challenges. This variety not only aligns with my skills in hardware–software codesign and machine learning but also pushes me to grow in ML compilers, emerging technologies, novel designs, and real-world applications. I enjoy the balance of applying what I know and continuously learning, ensuring each day brings a new dimension to my expertise.
Previously, I was at Rain AI for two years. As one of the initial technical hires, I embraced a role that was as varied as it was fulfilling. My day-to-day involved realizing our AI accelerator architecture—breaking the memory wall with compute-in-memory, driving radical hardware–software codesign across ML workloads (from LLM attention to CNN convolutions), and leading technical presentations and customer interactions.
Before Rain AI, I worked as a machine learning researcher at SK hynix, focusing on the intersection of hardware, software, and CMOS image sensors (CIS) to enable efficient execution of cutting-edge computer vision workloads. Later, I co-designed compression accelerators (LZ4 and ZSTD) for computational SSDs and explored processing-in-memory (PIM) concepts on Hybrid Memory Cubes (HBMs).
In 2018, I had the enriching experience of interning on Google’s Video Understanding Team, where I contributed to designing DNN models for YouTube video analysis—an opportunity that deepened my machine learning and video-analytics expertise in a high-impact setting.
Academic Background
I got my Ph.D. and Masters’s degrees in computer science from the Georgia Institute of Technology. I had the pleasure to work with Professor Hyesoon Kim at HPArch lab. My research interests lie within computer architecture, but I am always eager to explore new areas. Specifically, I have worked on processing in and near memory, edge devices, robotics, and deep learning. My thesis focused on enabling edge and IoT devices (i.e., resource-constrained devices, robots, and drones) to execute deep neural networks (DNNs) collaboratively, efficiently, securely, and reliably. I am excited to continue this work in industry and explore new ways of pushing the boundaries of edge systems.
My academic journey began at the Sharif University of Technology, where I earned a bachelor’s degree in Electrical Engineering. In my senior year, I took on a significant role, managing our Microprocessor Systems Laboratory (MicroLab). This lab was a pivotal resource for undergraduates, being the only place offering access to advanced FPGA boards, MCUs, and processors beyond the basic 8051 model. Working with a range of technologies, from Altera to Xilinx FPGA boards, alongside robotics, microprocessors, and microcontrollers, was a defining experience. It deeply influenced my career path, steering me towards a focus in computer architecture.
Early Inspirations and Interests
Astronomy captivated me during my high school years, leading to significant achievements in national and international olympiads, including two silver and one gold medal at the IOAA. Unlike other disciplines such as mathematics or chemistry, astronomy was not a standard part of high school curriculums. This gap compelled me to embark on a self-learning journey, where I had to seek out resources independently, establish a community, and teach myself. This early experience in self-education not only fueled my passion for astronomy but also instilled in me a lifelong habit of self-directed learning. This skill has been invaluable, enabling me to seamlessly transition into electronics and computer science, and continues to be a cornerstone of my personal and professional development.
Personal Pursuits
In my leisure time, I spend time on board games or grand strategy games by Paradox Interactive to hands-on maintenance of my car, I find joy in a variety of activities. This includes figuring out and teaching myself new skills, like designing custom boards with sensors, fixing an oil-fired boiler, and wood working. These DIY projects not only satisfy my curiosity but also resonate with my advocacy for open-source software, free internet, and the right to repair. I aspire to play post-rock music. Nature also offers me solace, and I pursue outdoor sports like squash, tennis, ping pong, soccer, rock climbing (especially bouldering), cycling, skiing, and backpacking.