HUMANS LAB
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USC · Thomas Lord Department of Computer Science

We study how humans and machines shape each other.

The HUMANS Lab — HUmans, MAchines, Networks & Social Systems — is a group of researchers at the University of Southern California working on social bots and influence operations, the safety and bias of AI systems, and the science of networked human-machine societies.

A research group of the Machine Intelligence & Data Science (MINDS) initiative · directed by Emilio Ferrara

! For the upcoming PhD admission cycle, I will only recruit students who are self-funded with individual fellowships. If you have one and you’re interested in joining us, please reach out.

Our researchMeet the team
Emilio FerraraLuca LuceriFaith BacaLeonardo BlasEun Cheol ChoiPriyanka DeyPatrick GerardBijean GhafouriBumju JungDaniel RuizVictoria Bingxin XuJinyi YeSiyi ZhouArnav AgrawalShreeya ChandShireen ChandDaniel ChenZhiyi ChenIsabel EpistelomogiKY HongFrancesca KubicaGrace LiAllison LimEsteban MurrilloAmisha NambiarRichard PengPreyashi PoddarPeiran QiuBryan Ramirez-GonzalezDiya SarafNeta ShubinBeverlyn TsaiGiovanni VurroChristina YouVito Zou

The people of the HUMANS Lab.

Now

Latest from the lab

auto-synced — arXiv · Crossref · GitHub
  • PaperOur work on backdoor attacks in vision-language models is accepted to Findings of ACL 2026
  • TalkClosing lecture at SICSS Singapore (NUS) — From Bots to Agents
  • PreprintManufactured Divisiveness, on invective across seven state-backed influence campaigns, posted as arXiv:2607.14491
  • PaperCommunity Detection as Adaptive Diffusion accepted at ACM AI Letters
  • DatasetWe release QuantiBias, a benchmark for quantization-induced bias in LLMs, on Hugging Face
  • PaperDefeat Devices in AI Systems published in Future Internet
  • PaperECHO: Encoding Communities via High-order Operators published in Machine Learning with Applications
  • PaperTwo papers at ICWSM 2026: coordinated inauthentic behavior on TikTok, and cross-platform narrative networks
  • PaperChange is Hard: Consistent Player Behavior Across Games with Conflicting Incentives accepted at CHI PLAY 2026

Programs

What we work on

Six programs, one question: what happens when human societies and intelligent machines become one system?

01

Social Bots & Influence Ops

Detecting automated and coordinated accounts; measuring platform manipulation at scale.

02

AI Safety & Bias Auditing

Behavioral audits of LLMs — deceptive behavior, quantization-induced bias, cultural safety.

03

Misinformation & Integrity

How false and divisive content spreads, and which interventions actually work.

04

Network Science

Community detection and diffusion — from theory to scalable open-source tools.

05

Computational Social Science

Large-scale measurement of collective behavior: elections, crises, human-AI interaction.

06

Human-Centered AI

Designing AI that serves people and communities: interaction, trust, and alignment.

The team

People

The lab is its people — faculty, research scientists, and students across computer science, communication, political science, and beyond.

Leadership
Emilio Ferrara
Emilio FerraraPI, Professor
Luca Luceri
Luca LuceriLead Scientist, Research Asst. Prof
PhD Students
Faith Baca
Faith BacaCS PhD
Leonardo Blas
Leonardo BlasCS PhD
Eun Cheol Choi
Eun Cheol ChoiComm. PhD
Priyanka Dey
Priyanka DeyCS PhD
Patrick Gerard
Patrick GerardCS PhD
Bijean Ghafouri
Bijean GhafouriPoli-Sci PhD
Bumju Jung
Bumju JungComm. PhD
Daniel Ruiz
Daniel RuizCS PhD
Victoria Bingxin Xu
Victoria Bingxin XuCS PhD
Jinyi Ye
Jinyi YeCS PhD
Siyi Zhou
Siyi ZhouComm. PhD
Students & Researchers
Arnav Agrawal
Arnav AgrawalCS BSc
Shreeya Chand
Shreeya ChandCS BSc
Shireen Chand
Shireen ChandCS MSc
Daniel Chen
Daniel ChenCS BSc
Zhiyi Chen
Zhiyi ChenComm. MSc
Isabel Epistelomogi
Isabel EpistelomogiCS BSc
KY Hong
KY HongCS BSc
Francesca Kubica
Francesca KubicaCS BSc
Grace Li
Grace LiCS BSc
Allison Lim
Allison LimCS BSc
Esteban Murrillo
Esteban MurrilloCS BSc
Amisha Nambiar
Amisha NambiarCS BSc
Richard Peng
Richard PengCS BSc
Preyashi Poddar
Preyashi PoddarCS BSc
Peiran Qiu
Peiran QiuCS BSc
Bryan Ramirez-Gonzalez
Bryan Ramirez-GonzalezCS BSc
Diya Saraf
Diya SarafCS MSc
Neta Shubin
Neta ShubinCS BSc
Beverlyn Tsai
Beverlyn TsaiCS BSc
Giovanni Vurro
Giovanni VurroMSCS MSc
Christina You
Christina YouCS BSc
Vito Zou
Vito ZouCS BSc

Alumni hall of fame. Former members of the lab now hold faculty positions at UCLA, Dartmouth, and the University of Copenhagen, and research roles at Capital One, Google, Meta, Amazon, and beyond. See where our alumni are →

Selected

Publications

A selection of the lab’s work. The full list keeps itself current from arXiv, Crossref, and ORCID.

→ all publications

Open Science

Data & Software

Benchmarks, corpora, and tools the community builds on.

QuantiBias ↗

Benchmark for quantization-induced bias and safety drift in compressed LLMs.

huggingface.co2026

ECHO-GNN ↗

Graph-neural community detection: encoding communities via high-order operators.

github.com2026

Generalized Louvain ↗

A scalable, open-source revival of the generalized Louvain method for community detection.

github.com2026

US 2020 Election Tweets ↗

A large-scale Twitter dataset tracking the 2020 U.S. presidential election.

github.com2020

COVID-19 Twitter Dataset ↗

One of the most widely used pandemic social-media corpora in the field.

github.com2020

League of Legends Dataset ↗

Behavioral traces from team-based online games for studying performance.

Harvard Dataverse2018

GEM ↗

Graph Embedding Methods: a Python library of node-embedding algorithms (Goyal & Ferrara).

github.com2018

CONCLUDE ↗

Fast community detection in large networks via diffusion.

emilio.ferrara.name2016

WERW-Kpath Centrality ↗

Random-walk edge-and-node centrality for very large graphs.

emilio.ferrara.name2016
→ all data & software