I'm proficient in extracting useful insights from large amounts of data via probabilistic methods including graph analysis, machine learning and deep learning. My focus is on threat and vulnerability detection.

Anomaly detection, tabular data, metric learning, explainability, AI security.

Graph-based anomaly detection solutions on big data.

Senior Software Engineer at Lyft

Learning AI and LLM integration!

A lot

am an ML Researcher specializing in 3D Computer Vision and Computer Graphics, leveraging machine learning to push the boundaries of 3D content generation, view synthesis, and image manipulation. My expertise spans deep learning, generative AI, and computer vision, with a strong focus on diffusion models and neural radiance fields (NeRFs). At Ubisoft Toronto’s La Forge team, I worked on designing generative solutions for constructing ultra-realistic face models, reducing model creation time by over 90%. I integrated state-of-the-art generative models such as StyleGAN, Real-ESRGAN, and Pix2Pix, optimizing large-scale training pipelines on GPU clusters. At the Vector Institute, I served as an ML Engineer Technical Advisor, supporting startups and businesses in ML deployment.

Computer vision, Generative models, Video Diffusion, 3D/4D generation

Currently researching video diffusion distillation and autoregressive generation paradigms (diffusion forcing, self-forcing). On the applied side, I am building a gaze correction pipeline combining SAM2 with Wan2.1-VACE for human-centric video editing.

Sanaz Naseribonari is a Data Scientist at Chubb, with a background in Artificial Intelligence and a passion for building evaluation pipelines.

I’m interested in attending this workshop since it will allow me to have hands-on experience with building an evaluation pipeline, which is crucial when you want to create a successful AI system. Also, I want to meet and connect with people who are AI enthusiast

UofT alumn | Data Analyst | Health-Tech Product passioante

AI for healthcare, tele-rehabilitation, virtual assistants, movement analysis, AI-driven patient exercise feedback, digital technologies for older adults, AI project development, machine learning, healthcare innovation.

Some sort of connecting app for people.

Full-Stack Software Engineer in Toronto. I build scalable web apps and AI tools (Java/Spring Boot, React/TypeScript, PostgreSQL, Python). I volunteer as a TEDx web developer, mentor students at Concordia, and join hackathons to ship fast. Interests: AI agents, rapid prototyping, and useful, real-world products.

I focus on building AI-powered prototypes and full-stack applications that connect backend systems with user-friendly interfaces. My experience includes developing enterprise platforms with Java Spring Boot, PostgreSQL, and React/TypeScript, as well as creating community websites for TEDx events with multilingual support and smooth deployment.

I’m building AI-driven prototypes that combine backend logic with interactive UIs, experimenting with agentic workflows through the OpenAI API. I also work on React/TypeScript projects for community platforms like TEDx websites, handling design, multilingual features, and deployment. I enjoy learning fast, testing ideas, and shipping working demos.