Welcome to

AIM

Inclusive & Multimodal AI

About AIM Lab

AIM is a research lab in the Department of Computer Science and Engineering at Santa Clara University (SCU) . Our students explore Artificial Intelligence (AI) at the intersection of language and vision, developing novel multimodal models, tasks, and datasets.

Our aim is to advance equitable AI across diverse demographics, spanning income levels, languages, cultures, age groups, and gender. We emphasize inclusive, responsible, and human-centered approaches that address real-world challenges.

Update: We will not be recruiting students for Winter–Spring 2026. Prospective graduate students can explore the MS in AI at SCU. 🌹

To extend impact beyond the lab, we collaborate closely with partners such as the Miller Center for Global Impact and the Frugal Innovation Hub .

We co-organize the NLP for Positive Impact Workshop (NLP4PI) , fostering research that connects technical innovation with societal benefit.

We also co-host ACL Mentorship, a global initiative featuring panel sessions with AI researchers from academia and industry. Watch the recordings or join live as a mentee or mentor. Open to everyone, with a strong focus on underrepresented communities.

Learn more about the CSE PhD program at Santa Clara University.

Ultimately, research is for people and can enable demographic-aware technologies that make a lasting positive impact on society.

Lab Members

Current

Profile 1

Oana Ignat

Assistant Professor

oignat at scu

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Parth Bhalerao

PhD Student

pbhalerao at scu

Profile 2

Ruiwen Guan

Master Student

rguan at scu

Profile 2

Diola Dsouza

Master Student

dcdsouza at scu

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Peiyi Zhang

Master Student

pzhang4 at scu

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Yuming Zhao

Master Student

yzhao4 at scu

Alumni

Profile 2

Ragha Yalamarty

Master Student

2024-2025

ryalamarty at scu

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Shuowei Li

Master Student

2024-2025

sli19 at scu

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Arushi Mangla

Master Student

2024-2025

amangla at scu

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Brian Trinh

Master Student

2024-2025

btrinh at scu

Selected Publications (Paper, Poster & Code)

AI for All

Why AI Is WEIRD and Shouldn't Be This Way: Towards AI for Everyone, with Everyone, by Everyone

  Rada Mihalcea*, Oana Ignat*, Longju Bai, {...}
  AAAI 2025

NLP for Social Good: A survey of challenges, opportunities, and responsible deployment

  Antonia Karamolegkou, {...}, Oana Ignat, {...}
  Under Review

Brighter: Bridging the gap in human-annotated textual emotion recognition datasets for 28 languages

  Shamsudden H Muhammad, {...}, Oana Ignat, {...}
  ACL 2025
🏆 Best Resource Paper Award

MAiDE-up: Multilingual Deception Detection of GPT-generated Hotel Reviews

  Oana Ignat, Xiaomeng Xu, Rada Mihalcea
 NAACL 2025

Inspiration Detection

Cross-cultural Inspiration Detection and Analysis in Real and LLM-generated Social Media Data

  Oana Ignat*, Gayathri Ganesh Lakshmy*, Rada Mihalcea
  C3NLP at NAACL 2025
🏆 Best Paper Award

Detecting Inspiring Content on Social Media

  Oana Ignat, Y-Lan Boureau, Jane A. Yu, Alon Halevy
  ACII 2021

Inclusive Language-Vision Models & Datasets

The Power of Many: Multi-Agent Multimodal Models for Cultural Image Captioning

  Longju Bai, Angana Borah, Oana Ignat, Rada Mihalcea
  NAACL 2025

Multi-Agent Multimodal Models for Multicultural Text to Image Generation

  Parth Bhalerao, Mounika Yalamarty, Brian Trinh, Oana Ignat
  Under Review

CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark

  David Romero, Chenyang Lyu, {...} Joan Nwatu, Oana Ignat, Rada Mihalcea, Thamar Solorio, Alham Fikri Aji
  NeurIPS 2025

Uplifting Lower-Income Data: Strategies for Socioeconomic Perspective Shifts in Vision-Language Models

  Joan Nwatu, Oana Ignat, Rada Mihalcea
  NAACL 2025