Lalla Mouatadid, PhD.

I just relocated to Switzerland in the spring of 2025 for family reasons.
I'm currently on the Swiss job market looking for research scientist positions in AI/ML and algorithms (C permit holder).

Click here for my CV.

Prior to that, I have been a Staff Research Scientist at Intuit AI Research since 2020.
I'm a mathematician and AI researcher with experience in developing graph algorithms and innovative ML solutions. My work bridges theoretical mathematics with applied AI, where I design algorithms and develop models to solve real-world problems at scale. I have worked on cross-disciplinary projects from graph mining on knowledge graphs to LLM reliability, and hybrid AI, with multiple patents issued and publications in both Maths journals and AI/CS conferences.

I completed both my PhD and my MSc in Theoretical Computer Science (TCS) at the University of Toronto under the supervision of Allan Borodin and Derek Corneil, and my BSc (with a minor in Maths) at Vancouver Island University, graduating with distinction (magna cum laude).

While my day-to-day work for the past four years has focused on building practical Al solutions, I continue to pursue maths in my free time, collaborating with colleagues across the world. My TCS/Maths research focuses on graph theory, particularly on algorithmic and structural graph theory, modular decomposition, convex geometries and antimatroids.

[ CV ] [ Publications ] [ Patents ] [ PhD thesis ] [ Misc ] [ My sister's work ]

Sporadic Updates
  • [ Media ] Here's a blog post about our recent work on LLM uncertainty.
  • [ Talk ] I'm invited to speak at the Graph + AI Summit.
  • [ Talk ] I'm invited to speak at the ICALP workshop Graph Width Parameters: from Structure to Algorithms.
  • [ Talk ] I'll be giving a talk at the Stanford Theory Seminar in October.
  • [ Award ] I've been awarded the NSERC PostDoc Fellowship for 2019-2021! [Declined]
  • [ Research Visit ] I'll be visiting Blair Sullivan@NC State on August.
  • [ Talk ] I'll be giving a talk at the Princeton Math Seminar on Graph Searches on Structured Graph Classes.
  • [ Research Visit ] I'm visiting Princeton this November.
  • [ Talk ] In China for a conference + talks, see you at Shanghai Jiao Tong University!
  • [ Seminar ] I'm in the organizing committee of GROW 2017 at the Fields Institute.
  • [ Research Visit ] I'm visiting Brandenburg University for the summer.
  • [ HLF ] I've been invited by Steve Cook to participate in the Heidelberg Laureate Forum 2016!
  • [ Research Visit ] I'm visiting Université Paris Diderot for the summer.
  • [ Teaching ] I'll be teaching CSC373 (Algorithms & Complexity at UofT)!

Publications
  1. (α, β)-Modules in Graphs
    Michel Habib, Lalla Mouatadid, Eric Sopena, Mengchuan Zou
    Journal: SIAM Journal on Discrete Mathematics (SIDMA), 2024
  2. SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models
    Xiang Gao, Jiaxin Zhang, Lalla Mouatadid, & Kamalika Das
    Conference: European Chapter of the Association for Computational Linguistics (EACL), 2024
  3. RE2: Region-Aware Relation Extraction from Visually Rich Documents
    Pritika Ramu, Sijia Wang, Lalla Mouatadid, Joy Rimchala, & Lifu Huang
    Conference: North American Chapter of the Association for Computational Linguistics (NAACL), 2024
  4. DECDM: Document Enhancement using Cycle-Consistent Diffusion Models
    Jiaxin Zhang, Joy Rimchala, Lalla Mouatadid, Kamalika Das, & Kumar Sricharan
    Conference: IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2024
  5. A New Graph Parameter To Measure Linearity
    Pierre Charbit, Michel Habib, Lalla Mouatadid, and Reza Naserasr
    Journal: Journal of Graph Theory (JGT), 2023
    Conference: International Conference on Combinatorial Optimization and Applications (COCOA), 2017
  6. Mining Frequent Patterns on Knowledge Graphs
    Lalla Mouatadid
    Conference: International Conference on Web Search and Data Mining (WSDM), 2022
  7. Actionable Recommendations With Hybrid AI
    Sudhir Agarwal, Lalla Mouatadid, Anu Sreepathy
    Conference: AAAI Symposium on Machine Learning and Knowledge Engineering (AAAI MAKE), 2022
  8. A Scalable Technique for Weak-Supervised Learning with Domain Constraints
    Sudhir Agarwal, Anu Sreepathy, & Lalla Mouatadid
    Workshop: NeurIPS Workshop: Has it Trained Yet? (Neurips Workshop), 2022
  9. A General Algorithmic Scheme for Modular Decompositions of Hypergraphs
    Michel Habib, Fabien de Montgolfier, Lalla Mouatadid, Mengchuan Zou
    Journal: Theoretical Computer Science (TCS), 2022
    Conference: International Workshop on Combinatorial Algorithms (IWOCA), 2019
    Invited to the Special Issue
  10. Maximum Induced Matching Algorithms via Vertex Ordering Characterizations
    Michel Habib and Lalla Mouatadid
    Journal: Algorithmica, 2020
    Poster: Symposium on Theory of Computing (STOC), 2017
    Conference: International Symposium on Algorithms and Computation (ISAAC), 2017
    Invited to the Special Issue
  11. Approximating Modular Decomposition is Hard
    Michel Habib, Lalla Mouatadid, Mengchuan Zou
    Conference: Conference on Algorithms and Discrete Applied Mathematics (CALDAM), 2020
  12. Graph Searches and Geometric Convexities in Graphs
    Feodor Dragan, Michel Habib, and Lalla Mouatadid
    Conference: International Colloquium on Graph Theory (ICGT), 2018
    Manuscript
  13. A note on the De Bruijn-Erdos Theorem for Asteroidal-Triple Free Graphs
    Lalla Mouatadid
    Manuscript: 2017
  14. A Fast, Simple Algorithm for Computing the Bump Number of a Poset
    Derek Corneil, Lalla Mouatadid, & Gara Pruesse
    Technical report, Manuscript, 2018
    Slides: Gara's talk at Connections in Discrete Math at SFU
  15. Linear Time Maximum Weighted Independent Set on Cocomparability Graphs
    Ekkehard Kohler and Lalla Mouatadid
    Journal: Information Processing Letters (IPL), 2016
    Poster: The ACM Celebrations of Women in Computing (ACMW) 2013
    Best Poster Award
  16. Path Graphs, Clique Trees and Flowers
    Lalla Mouatadid and Robert Robere
    Manuscript: ArXiv, 2015
  17. Linear Time LexDFS on Cocomparability Graphs
    Ekkehard Kohler and Lalla Mouatadid
    Conference: Scandinavian Workshop on Algorithm Theory (SWAT), 2014
  18. Efficient Generation of the Ideals of a Poset
    Lalla Mouatadid
    Conference Slides: MAA MathFest conference 2009.
    BSc thesis under the supervision of Gara Pruesse.

Issued Patents
  1. Storage Structure for Pattern Mining.
    Lalla Mouatadid & Jay Jie-Bing Yu
    US Patent: 11,531,527
  2. Model Based Document Image Enhancement.
    Jiaxin Zhang, Tharathorn Rimchala, Lalla Mouatadid, Kamalika Das, & Sricharan Kumar
    US Patents: 11,769,239 and 12,045,967
  3. Scalable Weak-Supervised Learning with Domain Constraints.
    Sudhir Agarwal, Anu Sreepathy, & Lalla Mouatadid
    US Patent: 11,783,609
  4. Optimizing Questions to Retain Engagement.
    Kevin Furbish, Glenn Scott, & Lalla Mouatadid
    US Patent: 12,093,640


Teaching

Course Instructor
   CSC373 - Algorithm Design and Analysis. (2016)
   CSC373 - Algorithm Design and Analysis. (2014)

Teaching Assistant
   CSC473   -  Advanced Algorithms. (Winter '17)
   CSC2404 -  Computability and Logic (Graduate course). (Fall '16)
   CSC2420 -  Algorithm Design, Analysis and Theory (Graduate course). (Winter '15)
   CSC373   -  Algorithm Design and Analysis. (Winter & Fall '14, Winter '15)
   CSC263   -  Data Structures and Analysis (Fall '15, Winter '16)
   CSC236   -  Introduction to Theory of Computation (Winter '14 & Fall '14, '12)
   CSC165   -  Mathematical Expression and Reasoning for Computer Science. (Winter, Summer, Fall '13 & Fall '16)


Other Projects & Expository Writings

Graph Searching & Perfect Graphs
For some reason (*whispers*: convex geometries), graph searching seems to extract useful algorithmic structure from various graph classes. This structure often leads to elegant and simple linear time algorithms. We illustrate this point with two graph searches on two perfect graph classes: Lexicographic Breadth Search on Chordal Graphs, and Lexicographic Depth First Search on Cocomparability graphs.
[pdf]

Szemerédi's Regularity Lemma
An expository writing where I discuss Diestel's proof of the Regularity Lemma, and the co-NP completeness of regularity testing.
[pdf]

Characterization of complex genetic disease using exomic SNVs and gene expression data
Aziz Mezlini, Lalla Mouatadid, and Anna Goldenberg
A class project for Machine Learning in Computational Biology that Aziz and I worked on, under the supervision of Dr. Goldenberg. We explored combining both exome sequences and gene expression in order to identify harmful genes and to characterize the mechanism, that when disrupted, can cause the disease.
[pdf]

fMRI Classification of Cognitive States Across Multiple Subjects
The problem considered in this study is to differentiate between two cognitive states (reading a sentence or looking at an image), by training one classifier across multiple subjects. Human brains differ anatomically in shape and size. It is therefore complicated to generalize the outcome of fMRI scans, since the number of voxels differ from one subject's brain to another. In this work, I examine the possibility of training one classifier to use across multiple subjects. Succeeding in doing so will allow us to associate brain activities to cognitive states independently from the anatomy of the brain.
[pdf]