Summary
Qilong Wang is a graduate researcher and incoming PhD student with 10+ years of programming experience and competitive medals at national and international contests, now focusing on production-ready ML systems. Over the past 2+ years he has driven research on Large Language Models, multimodal and time-series forecasting, and hardware-aware transformer optimization鈥攚ork that produced a DATE 2026 paper on ultra-efficient causal attention and practical gains in financial forecasting using GPT-4o-mini pipelines. He combines systems thinking (distributed and operating systems coursework) with hands-on model optimization: low-bit quantization, MoE routing, and HLS-driven ASIC prototyping to shrink latency, area, and energy. Qilong has also built end-to-end ML products in healthcare and mobile apps, shipping synthetic-data pipelines, AWS-deployed tools, and cross-platform apps with AI features. Looking to transition into industry, he brings a rare mix of research rigor, production engineering, and hardware鈥搒oftware co-design experience that makes models run faster and cheaper in the real world.
2 years of coding experience
2 years of employment as a software developer
Master of Science - MS, Computer Science and Engineering, Master of Science - MS, Computer Science and Engineering at University of Michigan
Bachelor of Science - BS, Computer Science & Biology, 4.75 / 5.00, Bachelor of Science - BS, Computer Science & Biology, 4.75 / 5.00 at Huazhong University of Science and Technology