Ni Lao — Homepage

About

I am a research scientist at Google DeepMind, working on large pretrained models.

Previously I have studied a wide range of topics such as robotic soccer, computer system diagnosis, product search, and question answering.

I graduated from the Language Technologies Institute, School of Computer Science at Carnegie Mellon University. My thesis was advised by professor William W. Cohen. I worked at Google and Apple on language understanding and question answering, and was chief scientist at SayMosaic.

I TAed Machine Learning with Large Datasets (2012) and Machine Learning (2010). Here is my collection of interesting stuff.

Publications most recent first

Z Liu, N Lao, Z Wang, J Jiao, G Mai, GAIR: Location-Aware Self-Supervised Contrastive Pre-Training with Geo-Aligned Implicit Representations

ISPRS J. of Photogrammetry and Remote Sensing 237: 166–182, 2026

L Chen, J Li, C Liang, N Lao, Q Liu, Training-Free Looped Transformers

arXiv:2605.23872, 2026

L Chen, J Li, Q Wang, R Liao, S Li, C Liang, N Lao, Q Liu, φ-Balancing for Mixture-of-Experts Training

ICML 2026

M D Siampou, G Mai, N Lao, J Rao, N Arora, C Shahabi, S Choudhury, TRAJGANR: Trajectory-Centric Urban Multimodal Learning via Geospatially Aligned Neural Representations

arXiv:2605.06990, 2026

Earlier publications — scroll for the full list

Z Wang, Z Liu, J Zhang, Z Zhou, Q Cao, N Wu, L Mu, Y Song, Y Xie, N Lao, et al., LocDiff: Identifying Locations on Earth by Diffusing in the Hilbert Space

NeurIPS 38: 620–647, 2026

G Mai, N Lao, J Zhang, L Mao, Z Wang, N Wu, K Janowicz, K Wu, J Rao, et al., On the Ethics of Generative GeoAI: Explainability, Bias, Hallucination, Accountability, Privacy, and Trust

Geography According to Foundation Models, 215–232, 2026

L Chen, J Li, K Liang, B Su, C Xie, N W Pierse, C Liang, N Lao, Q Liu, Cautious Weight Decay

arXiv:2510.12402, 2025

Z Wang, N Wu, Q Cao, J Xia, Z Liu, Y Xie, A Nambi, T Ganu, N Lao, N Liu, et al., GeoBS: Information-Theoretic Quantification of Geographic Bias in AI Models

arXiv:2509.23482, 2025

K Janowicz, G Mai, W Huang, R Zhu, N Lao, L Cai, GeoFM: How Will Geo-Foundation Models Reshape Spatial Data Science and GeoAI?

Int. J. Geographical Information Science 39(9): 1849–1865, 2025

G Comanici, E Bieber, M Schaekermann, N Lao, et al. (Google DeepMind), Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

arXiv:2507.06261, 2025

G Mai, Y Xie, X Jia, N Lao, J Rao, Q Zhu, Z Liu, The Evolution of Geospatial Artificial Intelligence

GeoAI and Human Geography, 13–27, 2025

G Mai, Y Xie, X Jia, N Lao, J Rao, Q Zhu, Z Liu, Y-Y Chiang, J Jiao, Towards the Next Generation of Geospatial Artificial Intelligence

Int. J. Applied Earth Observation and Geoinformation 136, 2025

N Wu, Q Cao, Z Wang, Z Liu, Y Qi, J Zhang, J Ni, X Yao, H Ma, L Mu, N Lao, et al., TorchSpatial: A Location Encoding Framework and Benchmark for Spatial Representation Learning

NeurIPS 37: 81437–81460, 2024

G Mai, X Yao, Y Xie, J Rao, H Li, Q Zhu, Z Li, N Lao, SRL: Towards a General-Purpose Framework for Spatial Representation Learning

ACM SIGSPATIAL 2024

Z Zhou, J Zhang, Z Guan, M Hu, N Lao, L Mu, S Li, G Mai, Img2Loc: Revisiting Image Geolocalization using Multi-Modality Foundation Models and Image-Based RAG

ACM SIGIR 2024

G Mai, W Huang, J Sun, S Song, D Mishra, N Liu, S Gao, T Liu, G Cong, N Lao, et al., On the Opportunities and Challenges of Foundation Models for GeoAI

ACM Transactions on Spatial Algorithms and Systems 10(2): 1–46, 2024

Z Wang, G Mai, K Janowicz, N Lao, MC-GTA: Metric-Constrained Model-Based Clustering using Goodness-of-Fit Tests with Autocorrelations

arXiv:2405.18395, 2024

G Mai, Z Li, N Lao, Spatial Representation Learning in GeoAI

Handbook of Geospatial Artificial Intelligence, 99–120, 2023

H Li, J Wang, J M Zöllner, G Mai, N Lao, M Werner, Rethink Geographical Generalizability with Unsupervised Self-Attention Model Ensemble: OpenStreetMap Missing Building Detection in Africa

ACM SIGSPATIAL 2023

Y Hu, G Mai, C Cundy, K Choi, N Lao, W Liu, G Lakhanpal, R Z Zhou, et al., Geo-Knowledge-Guided GPT Models Improve the Extraction of Location Descriptions from Disaster-Related Social Media Messages

Int. J. Geographical Information Science 37(11): 2289–2318, 2023

G Mai, N Lao, W Sun, Y Ma, J Song, C Meng, H Ma, J Rao, Z Li, S Ermon, SSIF: Learning Continuous Image Representation for Spatial-Spectral Super-Resolution

arXiv:2310.00413, 2023

G Mai, Y Xuan, W Zuo, Y He, J Song, S Ermon, K Janowicz, N Lao, Sphere2Vec: A General-Purpose Location Representation Learning over a Spherical Surface for Large-Scale Geospatial Predictions

ISPRS J. of Photogrammetry and Remote Sensing 202: 439–462, 2023

L Gao, Z Dai, P Pasupat, A Chen, A T Chaganty, Y Fan, V Zhao, N Lao, et al., RARR: Researching and Revising What Language Models Say, Using Language Models

ACL 2023

G Mai, N Lao, Y He, J Song, S Ermon, CSP: Self-Supervised Contrastive Spatial Pre-Training for Geospatial-Visual Representations

ICML 2023

G Mai, C Jiang, W Sun, R Zhu, Y Xuan, L Cai, K Janowicz, S Ermon, N Lao, Towards General-Purpose Representation Learning of Polygonal Geometries

GeoInformatica 27(2): 289–340, 2023

C Haberland, N Lao, Kabyle ASR Phonological Error and Network Analysis

Analysis and Application of Natural Language and Speech Processing, 45–66, 2023

G Mai, C Cundy, K Choi, Y Hu, N Lao, S Ermon, Towards a Foundation Model for Geospatial Artificial Intelligence (Vision Paper)

ACM SIGSPATIAL 2022

I Montero, S Longpre, N Lao, A Frank, C DuBois, Pivot Through English: Reliably Answering Multilingual Questions without Document Retrieval

Workshop on Multilingual Information Access (MIA), 16–28, 2022

G Mai, W Huang, L Cai, R Zhu, N Lao, Narrative Cartography with Knowledge Graphs

J. of Geovisualization and Spatial Analysis 6(1): 4, 2022

G Mai, K Janowicz, Y Hu, S Gao, B Yan, R Zhu, L Cai, N Lao, A Review of Location Encoding for GeoAI: Methods and Applications

Int. J. Geographical Information Science 36(4): 639–673, 2022

G Mai, K Janowicz, R Zhu, L Cai, N Lao, Geographic Question Answering: Challenges, Uniqueness, Classification, and Future Directions

AGILE: GIScience Series 2: 8, 2021

C Haberland, N Lao, Orthographic Transliteration for Kabyle Speech Recognition

4th Int. Conf. on Natural Language and Speech Processing (ICNLSP), 2021

G Mai, K Janowicz, L Cai, R Zhu, B Regalia, B Yan, M Shi, N Lao, SE-KGE: A Location-Aware Knowledge Graph Embedding Model for Geographic Question Answering and Spatial Semantic Lifting

Transactions in GIS 24(3): 623–655, 2020

G Mai, K Janowicz, S Prasad, M Shi, L Cai, R Zhu, B Regalia, N Lao, Semantically-Enriched Search Engine for Geoportals: A Case Study with ArcGIS Online

AGILE 2020

G Mai, K Janowicz, B Yan, R Zhu, L Cai, N Lao, Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells

ICLR 2020

F Wu, B Li, L Wang, N Lao, J Blitzer, K Q Weinberger, Integrated Triaging for Fast Reading Comprehension

arXiv:1909.13128, 2019

G Mai, K Janowicz, B Yan, R Zhu, L Cai, N Lao, Contextual Graph Attention for Answering Logical Queries over Incomplete Knowledge Graphs

K-CAP 2019, 171–178

J Biloki, C Liang, N Lao, Neural Program Planner for Structured Predictions

ICLR 2019 Workshop

F Wu, B Li, L Wang, N Lao, J Blitzer, K Q Weinberger, FastFusionNet: New State-of-the-Art for DAWNBench SQuAD

arXiv:1902.11291, 2019

G Mai, K Janowicz, C He, S Liu, N Lao, POIReviewQA: A Semantically Enriched POI Retrieval and Question Answering Dataset

12th Workshop on Geographic Information Retrieval (GIR 2018)

T Mitchell, W Cohen, E Hruschka, P Talukdar, B Yang, J Betteridge, N Lao, et al., Never-Ending Learning

Communications of the ACM 61(5): 103–115, 2018

J Li, M Zhou, G Qi, N Lao, T Ruan, J Du, Knowledge Graph and Semantic Computing: Language, Knowledge, and Intelligence (CCKS 2017)

Springer CCIS, 2018

C Liang, M Norouzi, J Berant, Q V Le, N Lao, Memory Augmented Policy Optimization for Program Synthesis and Semantic Parsing

NeurIPS 2018

F Yang, J Nie, W W Cohen, N Lao, Learning to Organize Knowledge and Answer Questions with N-Gram Machines

arXiv:1711.06744, 2017 (ICLR 2018 Workshop)

F Wu, N Lao, J Blitzer, G Yang, K Weinberger, Fast Reading Comprehension with ConvNets

arXiv:1711.04352, 2017

C Liang, J Berant, Q Le, K D Forbus, N Lao, Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision

ACL 2017

N Lao, E Minkov, W Cohen, Learning Relational Features with Backward Random Walks

ACL 2015

W Y Wang, K Mazaitis, N Lao, W W Cohen, Efficient Inference and Learning in a Large Knowledge Base: Reasoning with Extracted Information using a Locally Groundable First-Order Probabilistic Logic

Machine Learning 100(1): 101–126, 2015

X Dong, E Gabrilovich, G Heitz, W Horn, N Lao, K Murphy, T Strohmann, S Sun, W Zhang, Knowledge Vault: A Web-Scale Approach to Probabilistic Knowledge Fusion

KDD 2014

N Lao, J Zhu, Contrastive Feature Induction for Efficient Structure Learning of Conditional Random Fields

arXiv:1406.7445, 2014

N Lao, A Subramanya, F Pereira, W Cohen, Reading the Web with Learned Syntactic-Semantic Inference Rules

EMNLP 2012

N Lao, W W Cohen, Personalized Reading Recommendations for Saccharomyces Genome Database

DILS 2012

J Zhu, N Lao, N Chen, E P Xing, Conditional Topical Coding: an Efficient Topic Model Conditioned on Rich Features

KDD 2011

N Lao, T Mitchell, W Cohen, Random Walk Inference and Learning in a Large Scale Knowledge Base

EMNLP 2011

N Lao, W W Cohen, Relational Retrieval using a Combination of Path-Constrained Random Walks

Machine Learning 81(1): 53–67, 2010 (ECML 2010)

J Zhu, N Lao, E P Xing, Grafting-Light: Fast, Incremental Feature Selection and Structure Learning of Markov Random Fields

KDD 2010

N Lao, W W Cohen, Fast Query Execution for Retrieval Models based on Path-Constrained Random Walks

KDD 2010

N Lao, J Zhu, L Liu, Y Liu, W W Cohen, Efficient Relational Learning with Hidden Variable Detection

NeurIPS 2010

W Zuo, N Lao, Y Geng, K Ma, GeoSVM: an Efficient and Effective Tool to Predict Species' Potential Distributions

J. of Plant Ecology 1(2): 143–145, 2008

H Shima, N Lao, E Nyberg, T Mitamura, Complex Cross-Lingual Question Answering as a Sequential Classification and Multi-Document Summarization Task

NTCIR-7, 2008

N Lao, H Shima, T Mitamura, E Nyberg, Query Expansion and Machine Translation for Robust Cross-Lingual Information Retrieval

NTCIR-7, 2008

Y Yang, A Lad, N Lao, A Harpale, B Kisiel, M Rogati, Utility-Based Information Distillation over Temporally Sequenced Documents

SIGIR 2007, 31–38

C Yuan, N Lao, J-R Wen, J Li, Z Zhang, Y-M Wang, W-Y Ma, Automated Known Problem Diagnosis with Event Traces

EuroSys 2006 (ACM SIGOPS OSR 40(4): 375–388)

N Lao, J-R Wen, W-Y Ma, Y-M Wang, Combining High Level Symptom and Low Level State Information for Configuration Fault Diagnosis

LISA 2004

J-R Wen, N Lao, W-Y Ma, Probabilistic Model for Contextual Retrieval

SIGIR 2004

A Ganapathi, Y-M Wang, N Lao, J-R Wen, Why PCs Are Fragile and What We Can Do About It: A Study of Windows Registry Problems

DSN 2004, 561–566

J Yao, N Lao, F Yang, Y Cai, Z Sun, Technical Solutions of TsinghuAeolus for Robotic Soccer

RoboCup 2003, 205–213

Patents 7

N Lao, L M Kaiser, N Gupta, A Mohiuddin, P Popat, Answer to Question Neural Networks

Google LLC · US11093813B2 (granted 2021) · WO2018097907A1, GB2557014A

N Lao, J Nie, F Yang, Natural Language Processing with an N-Gram Machine

Google LLC · US11256866B2 (2022), US11947917B2 (2024) · WO2019083519A1, EP3625699A1, CN111095259B

A Subramanya, F Pereira, N Lao, J Blitzer, R Gupta, Querying a Data Graph using Natural Language Queries

Google LLC · US10810193B1 (2020), US11403288B2 (2022) · granted

N Lao, C Liang, Q V Le, J Blitzer, Neural Question Answering System

Google LLC · US20190130251A1 · application, 2019

G Mai, C He, S Liu, N Lao, System and Method for NLP-Based Searching and Question Answering

SayMosaic Inc · US20200218722A1 · application, 2020

C He, N Lao, X Tan, S Liu, Method and Apparatus for Searching Historical Data

SayMosaic Inc · US20190370398A1 · application, 2019

K B Collins-Thompson, N Lao, Context-Aware Query Alteration

Microsoft · US20120233140A1 · application, 2012

Manuscripts & Presentations

Ni Lao, Taxonomy of Ancient Ideas, 2026

An interactive map of concepts from ancient philosophy across traditions — surfacing their equivalences, resonances, and contradictions in a single explorable graph.

Ni Lao, Neuroscience and AI, 2026

In this talk we compare the algorithms in neuroscience against their corresponding algorithms in AI.

Ni Lao, Learning to Understand Questions and Organize Knowledge, 2021

I first introduce previous work in query understanding — weakly supervised semantic parsing and related issues such as symbolic representations for efficient inference, unbiased low-variance gradient estimation with experience replays, and sequence reranking model design and training. Then I discuss preliminary work in document understanding, aiming for generalizability, scalability and accountability beyond current large sequence models.

Ni Lao, A Review of Google's Lingvo, 2019

By invitation of Synced. Thanks to Patrick Nguyen and Esther Lee.

Ni Lao, Yann LeCun's Cake Explained, 2019

Based on an interview from Robin.ly

Ni Lao, Weakly Supervised Natural Language Understanding, JiangMen tutorial, 2019

video

Ni Lao, Weakly Supervised Natural Language Understanding, AIFrontiers tutorial, 2018

Ni Lao, Do Androids Dream of Great Success?, 2018

Ni Lao, Neural Symbolic Language Understanding, 2017

Ni Lao, Text Generation Survey, 2017

Ni Lao, Xipeng Qiu, Knowledge Acquisition, 2017

Ni Lao, NIPS 2016 Overview, 2016

Ni Lao, Neural Symbolic Machines, 2016

Ni Lao, New Development in Knowledge Acquisition, Inference, and Applications, 2015

A lecture at CCF ADL65, with my take on the relationship between connectionism and symbolism.

Ni Lao, Elephant and AI, LTI Colloquium Report, Spring 2012

Ni Lao, Programming by Demonstrations and Verbal Commands, LTI Colloquium Report, Spring 2012

Ni Lao, Beyond Shallow Semantics, LTI Colloquium Report, Fall 2011

Ni Lao, CCG, Fractal, and Emergence, LTI Colloquium Report, Spring 2011

Ni Lao, Reinforcement Learning In An Unknown Domain (slides), 2011

Ni Lao, Probabilistic Ontology Model, LTI Colloquium Report, Fall 2010

Ni Lao, Split-Emit Process for Natural Language Generation, Advanced NLP seminar, 2009

Ni Lao, Jun Zhu, Contrastive Feature Induction for Efficient Structure Learning of Conditional Random Fields, 2009

Ni Lao, T. Mitamura, E. Nyberg, Tree Representations for Chinese Semantic Role Labeling, 2009

Ni Lao, Read The Web (slides), Advanced IR seminar, 2007

Ni Lao, Schema Extraction Model, Advanced IR seminar, 2007

Ni Lao, Knowledge Acquisition From Text — A Survey, Statistical NLP class, 2007

Thesis

PhD thesis, 2012. Efficient Random Walk Inference with Knowledge Bases (slides). Carnegie Mellon University

Master thesis, 2006. Data Mining Problems in Automatic Computer Diagnosis. Tsinghua University

Bachelor thesis, 2003. Mining Spatial-Temporal Data Using Constructive Induction. Tsinghua University

Code & Data

Code

2012 — Path Ranking Algorithm, a system for relational retrieval on heterogeneous graphs (github)

2006 — geoSVM, a predictive system for modeling species potential distributions based on SVM. See Wenyun's page

Data Sets

2012 — NELL v165, NELL knowledge graph in both triple format and PRA format

2010 — yeast2, updated yeast data with extra information about Mesh headings, chemicals and affiliations (321K entities, 6.1M links)

2010 — fly, a biological literature graph with 770K entities and 3.5M links

2010 — yeast, a biological literature graph with 164K entities and 2.8M links

Academic Services

2023: ACL*, EMNLP*, ICML, IJGIS, Neurips*, TALLIP, Computers & Security (*Area chair for large language models and reasoning)

2022: ACL, CoNLL, EMNLP, ICLR, KDD, Neurips, TGIS

2021: ACL, AAAI, CoNLL, EMNLP, ICLR, NAACL, SIGIR, TALLIP, GeoAI, NLP4ConvAI

2020: ACL, AAAI, COLING, CoNLL, EACL, EMNLP, ICLR, ICML, IJCAI, Neurips, SIGIR, TALLIP, TKDE

I co-organized the Deep RL Meets Structured Prediction workshop, 2019 — ICLR page, homepage, intro slides

2019: ACL, AAAI, CCL, CoNLL, EMNLP, ICLR, IJCAI, NAACL, SIGIR, TKDE

2018: ACL, CCKS, COLING, EMNLP, NAACL, NLPCC, NIPS, SIGIR

2017: ACL, CCKS, EMNLP, IJCAI, IJCNLP, SIGIR, TKDE, WSDM, Google Research Grants

2016: CIKM, COLING, IJCAI, NAACL, TKDE, WWW, Google Research Grants

2015: CIKM, ICML, IJCAI, MLJ, NIPS, TKDE

Since 2012 I have been the manager of the Machine Learning News Google Group, which seems to be quite popular in academia.

Interesting Stuff

At the age of eleven, I began Euclid, with my brother as my tutor. This was one of the great events of my life, as dazzling as first love.— Bertrand Russell