AI Network Visualization

AI Perception Lab

Engineering adaptive AI perception through human-machine-environment synthesis—enabling ethical autonomy in intelligent infrastructures and human-machine collaboration.

Computer Vision
Causal AI
Human-AI Collaboration

About the Lab

Redefining research through open exploration and collaborative innovation

The Problem

Closed Doors, Narrow Paths

Traditional research labs often exclude students through rigid admissions, hyper-specialized focuses, and opaque selection criteria—leaving many unsure how to begin or pivot.

Access barriers: Fixed application cycles and GPA cutoffs exclude self-motivated learners
Narrow scope: Overly specialized projects limit interdisciplinary growth
Uncertain fit: Students hesitate to commit without testing diverse research approaches

Our Solution

Open Exploration

Your research, your trajectory—join anytime and contribute to meaningful innovation.

Continuous Intake: Join anytime—no rigid deadlines or semesters
Diverse Focus Areas: Contribute to ongoing projects or propose your own ideas
Purpose-Driven Impact: Prioritize meaningful innovation over publication volume

Mentorship

Guidance Tailored to You

Accessible Experts

Consult mentors actively engaged in both academia and industry

Collaborative Support

Peer and mentor-reviewed work, cross-project workshops, and open lab resources

Skill Development

Gain expertise through collaborative coding standards and hands-on learning

Structured Autonomy

Progress through collaboration

Your journey follows a tiered roadmap, exposing you to the full research lifecycle:

1
New Member: Immerse in lab culture and develop foundational skills
2
Active Member: Contribute to projects and collaborate with peers
3
Mentor: Guide others while deepening technical abilities
4
Project Lead: Oversee initiatives and drive innovation

Research Projects

Advancing AI perception through innovative research initiatives

CausalVision

Advancing semantic segmentation through causal inference and knowledge graphs to improve interpretability and robustness in image understanding, moving beyond correlation to model object interactions and contextual dependencies.

Computer VisionCausal AIKnowledge Graphs

Adaptive NLP

Developing uncertainty-aware dialogue systems using probabilistic modeling and knowledge graphs to enable adaptive, context-sensitive conversations that reconcile ambiguity with user-specific needs.

NLPDialogue SystemsUncertainty

Propose Research

Inspired by a different direction in AI perception? Share your vision and lead your own project with the support of our lab's resources and mentorship.

Our Team

Meet the researchers driving innovation in AI perception

Core Team

AS

Alexzander Sansiveri

Lab Lead

AC

Anthony Campos

Operations Manager

Advisor

EM

Dr. Ennio Mingolla

Faculty Advisor

Collaborators

MI

Mert Inan

Research Collaborator

IS

Ian Steenstra

Research Collaborator

GM

Girik Malik

Research Collaborator

Active Members

Be the first to join!

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Publications

Research contributions and academic publications

Publications Coming Soon!

Our research is in progress. Check back soon for our latest publications and findings.

Contact Us

Ready to collaborate? Let's explore opportunities together

Get in Touch

Emailcontact@aiperceptionlab.com
Phone+1 (555) 123-4567
Location123 Tech Innovation Center
Research Park
San Francisco, CA 94107

Join Our Lab

Ready to start your research journey? Follow these simple steps

1

Access the AI Club Notion

Join Northeastern's AI Club Notion workspace to get started with our community.

Join Notion Workspace →
2

Complete the Membership Form

Fill out the membership access form available on the Notion homepage to apply.

3

Request Lab Access

Submit a request to join the AI Perception Lab Teamspace through Notion.

4

Await Approval

Your request will be reviewed within 3 business days. We'll be in touch soon!

Questions about the application process?

Contact Us