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I am a postdoctoral researcher at CSAIL-MIT in the group of prof. T. Jaakkola and prof. R. Barzilay. I am part of the AI Cures initiative, MLPDS consortium and the Darpa AMD project.

Previously I obtained my PhD from the Data Analytics Lab at ETH Zurich under the supervision of prof. Thomas Hofmann.


Research Interests

I am broadly interested in representation learning for unstructured data (graphs), 3D objects (e.g. molecules), text or images through statistical or geometric models that could be devised and understood in a mathematically principled and elegant manner. In particular, I explored non-Euclidean geometries in Machine Learning to overcome some of the current difficulties in graph representation learning and generation, e.g. finding and learning latent hierarchical structures in data via hyperbolic geometry, as well as combining optimal transport and graph neural networks for better models that deal with graphs. I am currently applying my models to problems related to computational chemistry such as drug discovery.

Student projects:

Currently offering student projects in the areas of "Riemannian manifolds in machine learning" and "Molecular representations", please contact me.

Research Publications

All publications: Google Scholar

Checkout the Slides and Blog summarizing some of my work on non-Euclidean representationss.


Featured Publications



Optimal Transport Graph Neural Networks

Gary Bécigneul*, Octavian-Eugen Ganea*, Benson Chen*, Regina Barzilay, Tommi Jaakkola

Under review.

[Paper] [Slides] [Data + Code]



Hyperbolic Neural Networks

Octavian-Eugen Ganea*, Gary Bécigneul*, Thomas Hofmann.

Full paper @ NeurIPS 2018: Conference on Neural Information Processing Systems.

Spotlight (top 4% of all submitted papers).

[Paper] [Video] [Poster] [BLOG] [Data + Code]



Deep Joint Entity Disambiguation with Local Neural Attention

Octavian-Eugen Ganea, Thomas Hofmann.

Full paper @ EMNLP 2017: Conference on Empirical Methods in Natural Language Processing.

[PDF] [Slides] [Poster] [Data + Code]



Hyperbolic Entailment Cones for Learning Hierarchical Embeddings

Octavian-Eugen Ganea, Gary Bécigneul, Thomas Hofmann.

Full paper @ ICML 2018: International Conference on Machine Learning. Oral talk.

[PDF] [Slides] [Poster] [Data + Code]




All Publications



Computationally Tractable Riemannian Manifolds for Graph Embeddings

Calin Cruceru, Gary Bécigneul, Octavian-Eugen Ganea

Full paper @ AAAI 2021: The Thirty-Fifth AAAI Conference on Artificial Intelligence.

[Paper] [Poster] [Code + Data]



Message Passing Networks for Molecules with Tetrahedral Chirality

Lagnajit Pattanaik, Octavian-Eugen Ganea, Ian Coley, Klavs Jensen, William Green, Connor Coley.

Paper @ NeurIPS'20 Machine Learning for Molecules Workshop

[Paper] [Video + Slides] [Data + Code]



Constant Curvature Graph Convolutional Networks

Gregor Bachmann, Gary Bécigneul, Octavian-Eugen Ganea

Full paper @ ICML 2020: International Conference on Machine Learning.

[Paper] [Slides] [Blog post]



Hierarchical Image Classification using Entailment Cone Embeddings

Ankit Dhall, Anastasia Makarova, Octavian-Eugen Ganea, Dario Pavllo, Michael Greeff, Andreas Krause

Paper @ DiffCVML 2020: Intl. Workshop on Differential Geometry in Computer Vision and Machine Learning

[Paper] [Slides] [Blog post] [Code + Data]



Mixed-curvature Variational Autoencoders

Ondrej Skopek, Octavian-Eugen Ganea, Gary Bécigneul.

Full paper @ ICLR 2020: International Conference on Learning Representations.

[Paper] [Blog post] [Code + Data] [Slides + Video]



Breaking the Softmax Bottleneck via Learnable Monotonic Pointwise Non-linearities

Octavian-Eugen Ganea, Sylvain Gelly, Gary Bécigneul, Aliaksei Severyn.

Full paper @ ICML 2019: International Conference on Machine Learning.

[Paper] [Slides]



Poincaré GloVe: Hyperbolic Word Embeddings

Alexandru Tifrea*, Gary Bécigneul*, Octavian-Eugen Ganea*. (equal contribution)

Full paper @ ICLR 2019: International Conference on Learning Representations.

[Paper] [Blog] [Data + Code] [Poster]



Riemannian Adaptive Optimization Methods

Gary Bécigneul, Octavian-Eugen Ganea

Full paper @ ICLR 2019: International Conference on Learning Representations.

[PDF] [External Code] [Poster]



End-to-end Neural Entity Linking

Nikolaos Kolitsas*, Octavian-Eugen Ganea*, Thomas Hofmann.

Full paper @ CoNLL 2018: Conference on Natural Language Learning.

[PDF] [Data + Code]



Probabilistic Bag-Of-Hyperlinks Model for Entity Linking

Octavian-Eugen Ganea, Marina Ganea, Aurelien Lucchi, Carsten Eickhoff, Thomas Hofmann.

Full paper @ WWW 2016: International World Wide Web Conference. Oral talk.

[PDF] [Slides] [Poster] [Data + Code] [Online system (Gerbil - D2KB)] [Comparison with existing systems (Jan 2018)]



Learning and Evaluating Sparse Interpretable Sentence Embeddings

Valentin Trifonov, Octavian-Eugen Ganea, Anna Potapenko, Thomas Hofmann.

Paper @ EMNLP'18 Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP. 2018.

[PDF]



Property Prediction for 2-Molecule Mixtures

Allison Tam, Octavian-Eugen Ganea, Gary Bécigneul, Regina Barzilay

AI Powered Drug Discovery and Manufacturing Conference, Cambridge MA 2020



Neural Multi-Step Reasoning for Question Answering on Semi-Structured Tables

Till Haug, Octavian-Eugen Ganea, Paulina Grnarova .

Short paper @ ECIR 2018: European Conference on Information Retrieval.

[PDF] [Slides]



Web2Text: Deep Structured Boilerplate Removal

Thijs Vogels, Octavian-Eugen Ganea, Carsten Eickhoff .

Long paper @ ECIR 2018: European Conference on Information Retrieval.

[PDF] [Slides] [Source Code]

Awards

2019 - Fellowship Grant - Institute for Advanced Study for the special-year program 2019 - 2020 in Machine Learning led by Sanjeev Arora. (declined)
2010 - Excellence scholarship - Dinu Patriciu foundation (Romania) - for master studies at EPFL
2009 - 1st prize - International Mathematical Contest for University Students IMC (www.imc-math.org) - the equivalent of IMO for BSc students
2008 - Gold Medal - South Eastern Mathematical Olympiad for University Students -- SEEMOUS - Athens, Greece
2008 - 2nd prize - International Mathematical Contest for University Students IMC (www.imc-math.org)
2007 - 2nd prize - International Mathematical Contest for University Students IMC (www.imc-math.org)
2007 - Silver Medal - South Eastern Mathematical Olympiad for University Students -- SEEMOUS - Cyprus
2008, 2009 - Honorable Mention - CM programming contest, SouthEastern European Region (http://www.acm.ro/)
2005 - Silver Medal (3 rd place) - Tuymada International Olympiad in Mathematics, Yakutsk, Russia
2005 - Silver Medal - Balkan Mathematical Olympiad -- Iasi, Romania
2001 to 2006 (every year) - one of the first 7 places every year at National Mathematical Olympiad, Romania
2013 - Top 5% in Google Code Jam programming contest

Invited Talks

July 2020: Georgia Institute of Technology, host: Le Song
July 2020: Northeastern University, hosts: Tina Eliassi-Rad, Dmitri Krioukov, Rose Yu
December 2020: Bowdoin College, guest lecture, host: Jennifer Taback
April 2020: Machine Learning for Pharmaceutical Discovery and Synthesis Consortium, https://mlpds.mit.edu/
March 2020: IBM Global Business Services, host: Lucia Stavarache
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February 2020: University of Massachusetts Amherst, host: Andrew McCallum



January 2020: Relational.ai, host: Nikos Vasilakis

October 2019: Aggregate Intellect - https://aisc.ai.science, host: Amir Feizpour
October 2019: MIT - Massachusetts Institute of Technology, prof. Tommi Jaakkola’s group
October 2018: Google Brain, Zurich, host: Sylvain Gelly
April 2018: ETH Zurich, Machine Learning Seminar
May 2017: Google Research, Mountain View, California
March 2017: ETH Zurich, Machine Learning Seminar

Supervised theses

I proposed and (co-)supervised a number of MSc and BSc theses projects (6 months) for the following students, some resulting in research publications:

Panayiotou Panayiotis: Permutation Invariant Graph Generation via Optimal Transport
MSc thesis, MIT and ETH, April - October 2020
Octav Dragoi: Permutation Invariant Graph Generation and Optimization
MSc thesis, MIT and TU Munich, April - October 2020
Bachmann Gregor: Constant Curvature Graph Neural Networks, (paper @ICML'20)
MSc thesis (jointly with Gary Becigneul), ETH, March - September 2019
Calin Cruceru: Matrix Graph Embeddings, (paper @ AAAI'21)
MSc thesis (jointly with Gary Becigneul), ETH, April - October 2019
Ondrej Skopek: Mixed-curvature Variational Autoencoders, (paper @ICLR'20)
MSc thesis (jointly with Gary Becigneul), ETH, March - September 2019
Andreas Bloch: Mixed-curvature Recommender Systems,
MSc thesis (jointly with Gary Becigneul), ETH, March - September 2019
Ankit Dhall: Hierarchical Image Captioning using Entailment Cone Representations, (paper @DiffCVML'20)
MSc thesis (jointly with Andreas Krause and Anastasia Makarova), ETH, March - September 2019
Philipp Wirth: Language Models with External Advisers,
MSc thesis (jointly with Gary Becigneul), ETH, March - September 2019
Jovan Andonov: Neural Ordinary Differential Equations for Language Modeling,
MSc thesis (jointly with Gary Becigneul and Paulina Grnarova), ETH, March - September 2019
Alexandru Tifrea: Hyperbolic Word Embeddings, (paper @ ICLR'19)
MSc thesis (jointly with Gary Becigneul), ETH, April - October 2018
Kolitsas Nikolaos: End-to-end Neural Entity Linking, (paper @ CONLL'18)
MSc thesis, ETH, October 2017 - April 2018
Junlin Yao: Detecting Medication and Adverse Drug Events from Electronic Health Records,
MSc thesis (jointly with Carsten Eickhoff), ETH, September 2017 - March 2018
Igor Petrovski: Hyperbolic Sentence Embeddings,
MSc thesis (jointly with Gary Becigneul), ETH, October 2017 - April 2018
Valentin Trivonov: Sparse and Interpretable Embeddings, (paper @ EMNLP'18 Workshop)
MSc thesis (jointly supervised with Anna Potapenko), ETH, December 2017 - May 2018
Andreas Hess: Reinforcement Learning for Question Answering with Semi-structured Tables,
MSc thesis, ETH, December 2016 - May 2017
Yifan Su: Deep Structured Prediction for Joint Entity Linking and Coreference Resolution,
MSc thesis (jointly supervised with Aurelien Lucchi), ETH, July - December 2016
Till Haug: Convolutional and Recursive Neural Networks for Question Answering on Semi-structured Tables , (paper @ ECIR'18)
BSc thesis (jointly supervised with Paulina Grnarova), ETH, August 2016 - January 2017
Severin Bahman: Memory Networks for Entity Linking,
Research project (jointly supervised with Aurelien Lucchi), ETH, March - July 2016
Andreas Georgiadis: Learning Sentence and Entity Representations for Question Answering,
Research project (jointly supervised with Aurelien Lucchi), ETH, March - July 2016
Thijs Vogels: Structured Prediction for Web Page Content Extraction, (paper @ ECIR'18)
Research project (jointly supervised with Carsten Eickhoff), ETH, Sep 2015 - May 2016
Monteiro Freire Ribeiro Joao Pedro: Unsupervised Knowledge Base Fact Prediction using Matrix Word Embeddings,
BSc thesis (jointly supervised with Paulina Grnarova), ETH, Nov 2015 - May 2016

Community Service

Co-founder of OpenConsulting.AI, a free AI consulting platform for societal non-profit projects.
Conference Reviewer: NeurIPS 2020, ICML 2020, NeurIPS 2019, AAAI 2020, ACL 2018, EMNLP 2019, EMNLP 2018.

Besides Research

Completed the longest via ferrata in Switzerland (Leukerbad) - difficulty level K5-6
video
Climbed 10 four-thousand meter summits.
Videos: Zinalrothorn (4221m),    Mönch (4107m),    Mont Blanc traverse (via 3 monts),    Dufourspitze (4634m)
Finished 6 mountain and 1 road marathons.
Member of Forbes "30 under 30", Romania’s 2013 edition