Portrait of Shidu Ryan Ren

World Models · Multimodal Agents · Persistent Visual Memory

Shidu (Ryan) Ren

Hi! I am an undergraduate student in the Department of Electrical and Computer Engineering at the University of Toronto. I am currently a Research Intern at UW–Madison, working with Prof. Xiao Luo. I am also a Software Engineer Intern at Microchip Technology. Previously, I was an AI Research Intern at Memories.ai and a Machine Learning Intern at Themis AI.

My research focuses on world models, multimodal agents, and persistent visual memory. I am interested in building AI systems that can model how environments evolve, reason across visual and language information, and retain useful context from long-form video over time.

Seeking Fall 2028 CS PhD opportunities.

Shidu Ryan Ren in Toronto
Shidu Ryan Ren at an outdoor event
  1. One paper (NeTron) has been accepted to IEEE VLSI 2026! Link

  2. Joined Microchip Technology Inc. as a Software Engineer Intern.

  3. Joined Memories.ai as an AI Research Intern.

  4. Joined UW–Madison as a Research Intern, working with Prof. Xiao Luo.

  5. Joined Themis AI as a Machine Learning Intern.

ICM-Bench identity reasoning tasks across long video memories Open full-size figure ↗

ICM-Bench: Person-Level Identity Reasoning in Multimodal Agents with Long-Term Memory.

Shidu Ren, Yunze Liu, Xing Liu, Chi-Hao Wu, Enmin Zhou, Junxiao Shen

ICM-Bench evaluates whether multimodal agents can remember recurring people and reason about their identities and relationships across long video memories. It contains 839 synthetic clips spanning 141 minutes and 1,217 open-ended questions across three identity-centric memory tasks.

Figure 5 split-inference performance validation in motor and inner-speech decoding Open full-size figure ↗

IEEE VLSI 2026

A Split-Inference Intracortical Interface IC for Battery-Free mm-Scale Magnetoelectrically Powered Brain Implants.

Mustafa Kanchwala*, Jianxiong Xu*, Mohammad Abdolrazzaghi*, Wonjune Kim, Gerard O'Leary, Yu Huang, Junyu Ma, Jose Sales Filho, Sudip Nag, Hanfeng Cai, Qiaosong Deng, Weian Deng, Anush Mutyala, Theeban Kumaresan, Shidu Ren, Chae Lim, Mandana Movahed, Homeira Moradi, George Eleftheriades, Taufik A. Valiante, Jacob T. Robinson, Roman Genov

We present a split-inference intracortical interface IC for battery-free, millimeter-scale brain implants, with validation across motor reach-to-grasp and inner-speech decoding. The work connects low-power neural decoding, spike-sorting pipelines, and system-level evaluation, showing neural output data-rate reductions of 1,066× and 16,732× while preserving decoding performance.

Research and engineering experience.

May 2026 - Present

Software Engineer Intern · Microchip Technology Inc.

Working on research-driven FPGA EDA tools for PolarFire 2, combining timing and power analysis with AI and LLM-assisted approaches for interconnect timing modeling and design automation.

Jan 2026 - May 2026

AI Research Intern · Memories.ai

Researched LLM post-training, long-video understanding, and memory-augmented models for persistent visual intelligence.

Dec 2025 - Present

Research Intern · UW–Madison

Focused on LLM post-training and agent applications under the supervision of Professor Xiao Luo.

May 2025 - Sep 2025

Research Assistant · University of Toronto

Contributed to VLSI 2026 work and developed low-power neural decoding and spike-sorting pipelines for neural interface systems.

May 2025 - Sep 2025

Machine Learning Intern · Themis AI

Built an active-learning data labeling framework using uncertainty sampling, clustering-driven selection, and adaptive relabeling.

May 2024 - Sep 2024

Summer Research Intern · BUPT

Researched embodied intelligence trends and applied YOLOv8-based UI detection toward automated iPhone food-ordering workflows.

2023 - 2028 · Five-year program with one year of co-op

University of Toronto

Electrical & Computer Engineering (ECE)

Bachelor of Applied Science (BASc) cGPA 3.83

Reviewer

  1. WACV 2027
  2. LCFM Workshop @ NeurIPS 2026

Open to Fall 2028 PhD opportunities in AI and Computer Science.

I am broadly interested in Artificial Intelligence and its applications. I am currently open to Fall 2028 PhD opportunities in AI and related areas. I am always happy to connect with researchers, students, and practitioners with shared interests — feel free to reach out.