Mila > Lab Representatives

Lab Representatives

About the Lab Reps

Lab Reps are a point of contact to facilitate communication between/among students, interns, postdocs, faculty staff, as well as to enhance student involvement in decision-making processes.

The Lab Reps are elected every year by the students at Mila. While the specific initiatives undertaken by Lab Reps vary each year, depending on current context and interest of the members, they are always working to improve the Mila community.

Some of the Lab Reps roles and responsibilities include:

  • Supporting students (channeling feedback / helping solve problems)
  • Providing feedback on Information Technology infrastructure (clusters, wifi, etc.)
  • Managing social activities (reading groups, tea talks, socials)
  • Managing physical spaces (relaxation room, student lounge)
  • Discussing issues around Equity, Diversity and Inclusion
  • Developing conflict resolution procedures
  • Voicing opinion about prospective partnerships
  • Voicing opinion about AI for Humanity research projects

Students in need of advice or resources are welcome and encouraged to reach out to the Lab Reps at any time:

Meet the 2023-24 Lab Reps

Aayush Bajaj

Program : Professional Master’s, UdeM

After spending 2+ years identifying fraud and money laundering patterns with AI at a large UK bank, I decided to explore ways to use Graphical models in identifying large money laundering networks. When I’m not playing financial detective, I enjoy watching period dramas and cooking north Indian food. I write blogs and sometimes poems but they are shy from the limelight.

Simon Dufort-Labbé

Program : PhD, UdeM

Supervisor : Pierre-Luc Bacon

I’m a 3rd-year Ph.D. student at Mila, feeling more and more senior as days pass by. My current research interests revolve around the training dynamics of deep neural networks, with my most recent work ending up as a pruning algorithm that leverages insights from the impact of stochasticity on sparsity. Previous professional experiences include an AI researcher role at Jumio and a scientific in-residence position with Next AI. Outside of work, I am a dad to a 3-year-old boy, an avid reader, and a wannabe baker. We garden and hike in summer, switching to cross-country skiing and out-of-the-blue projects in winter.

Thomas Jiralerspong

Program : Master’s of computer science, UdeM

Supervisors : Yoshua Bengio and Doina Precup

I am a first year Master’s student in computer science co-supervised by Yoshua Bengio and Doina Precup at Mila and Université de Montréal. My primary research interests are: Incorporating inductive biases from cognitive science and neuroscience into our AI models in order to give them more human-like capabilities such as out-of-distribution generalization and long-term planning/reasoning and applying AI to projects that have a concrete positive impact on society, by tackling problems related to drug discovery, healthcare, climate change, autonomous driving, etc. I completed my Bachelor’s in Honours Computer Science at McGill University where I worked with Professor Blake Richards and Dr. Chen Sun on identifying important states for reinforcement learning in sparse reward environments, as well as with Professor Doina Precup and Dr. Khimya Khetarpal on temporally extended models and planning using option models in pixel environments. In my free time I enjoy composing music, watching movies, and learning new things!

Geraldin Nanfack

Program : Postdoctoral researcher, Concordia University

Supervisors : Eugene Belilovsky and Guy Wolf

I am currently a postdoctoral fellow at Concordia University and Mila. Originally from Cameroon, I earned my Ph.D. in Machine Learning (ML) in Belgium. My research interests revolve around fairness and interpretability. Specifically, I am currently focused on developing robust techniques to unravel the inner workings functionality of large-scale models.

Léna Néhale Ezzine

Program : PhD, UdeM

Supervisor : Yoshua Bengio

Hi ! My name is Léna, and I am a PhD student at Mila, supervised by Pr. Yoshua Bengio. I am excited about how AI can help us tackle important societal issues and make our societies better, and my research lies in the intersection of AI and drug discovery. Fun fact : I love sushi, chocolate, and I love music in all its diverse forms.

Emiliano Penaloza

Program : PhD, UdeM

Supervisor : Laurent Charlin 

I am a first-year PhD student working with Laurent Charlin on recommendation systems. Prior to Mila, I did my master’s in statistics at the University of Waterloo and a bachelor’s in data science at Western University.

César Miguel Valdez Cordova

Program : Quantitative Life Sciences, McGill University

Supervisor : Mathieu Blanchette

I am enthusiastic about harnessing the lessons of who I believe is our greatest teacher –nature– to advance the field of machine learning. As such, I seek to develop algorithms inspired from the intricate challenges of understanding natural phenomena across scales, from molecules to populations, aiming to push the boundaries of both computational methods and fundamental scientific knowledge. Originating from Mexicali, the vibrant capital of the beautiful peninsula of Baja California, Mexico, my scientific journey has been one of diverse perspectives: from hands-on bench work during my Nanotechnology and Chemistry Engineering days at Tec de Monterrey to my current research role at the interface of the computational and natural sciences, enabled by a Master’s in Computer Science at the Ensenada Center for Scientific Research and Higher Education in Ensenada, Mexico and a subsequent Master’s in Artificial Intelligence in JKU Linz, Austria.  Confident about the potential of Fair AI to benefit everyone, I seek to be a bridge between people and machines. When not trying to get models to work, you might find me exploring the art of Mexican cuisine, delving into postmodernist literature, dabbling in music production or marveling at and wrangling the magic of fermentation in all its forms and scales.

Haolun Wu

Program : Ph.D. in Computer Science, McGill University

Supervisors: Xue (Steve) Liu, Fernando Diaz

I am a Ph.D. candidate at McGill University and Mila. I am delighted in working with Xue (Steve) Liu and Fernando Diaz. I also collaborate closely with Laurent Charlin and Joelle Pineau, and have them on my supervisory committee. I am also a student researcher at Google Research. My research interests include knowledge modeling, storage, and retrieval in information systems, and also the alignment to social good. I am honored to hold the Borealis AI Fellowship. In my spare time beyond research, I enjoy road trips. I am a master in Chinese Calligraphy. I also played the clarinet for six years and was a member of the Musicians’ Association of Sichuan, China.

Krystal Xuejing Pan

Program : Thesis Msc, McGill University

Supervisor : Blake Richards

Hello! I’m a 2nd-year master’s student in Dr. Blake Richards’ group, working in the intersection of AI and neuroscience. My passion for interdisciplinary research began during my undergraduate studies in cognitive science at McGill. I enjoy engaging in philosophical discussions, watching sitcoms, and learning more about anything and everything through conversations with folks.

Xinyu Yuan

Program: PhD, UdeM

Supervisor: Jian Tang

Xinyu Yuan is a second-year PhD student at Mila, advised by Prof. Jian Tang. Her research passionately delves into the realm of representation learning for biological data, to harness AI’s potential to advance understanding of biological systems and processes, with a particular emphasis on scalability and transferability. From the technique perspective, she specializes in large-scale graph representation learning for knowledge graph completion, and pre-training, transfer learning, and multi-modality learning with language models. In particular, knowledge graphs serve as an important bridge to connect all the different data modalities in biological domain. In the same time, language models serve as foundational tools for each data modality,  to extract effective representations and infer latent patterns and deep structure that go well beyond the capacity of humans. She also spent some time in Intel AI Lab. And she obtained a bachelors’ degree in computer science from Peking University.

Lynn Cherif
Program : MSc, McGill

2022-2023 Lab Reps

  • Subhrajyoti Dasgupta
  • Roy Eyono
  • Vishal Gupta
  • Mats L. Richter
  • Gabriela Moisescu-Pareja
  • Beheshteh T. Rakhshan
  • Alexandra (Sasha) Volokhova
  • Sophie Xhonneux
  • Zhaocheng Zhu

2021-2022 Lab Reps

  • Alekhya Dronavalli
  • Jose Gallego-Posada
  • Kshitij Gupta
  • Alex Hernandez-Garcia
  • Niki Howe
  • Oumar Kaba
  • Dongyan Lin
  • Mandana Samiei
  • Victor Schmidt
  • Mélisande Teng
  • Mashbayar Tugsbayar
  • Ezekiel Williams

2020-2021 Lab Reps

  • Rim Assouel
  • Jose Gallego-Posada
  • Arna Ghosh
  • Manuela Girotti
  • Raghav Gupta
  • Nikolaus H. R. Howe
  • Arushi Jain
  • Sékou-Oumar Kaba
  • Tegan Maharaj
  • Victor Schmidt
  • Martin Weiss

2019-2020 Lab Reps

  • Rim Assouel
  • Sumana Basu
  • Charles C Onu
  • Yunhe Li
  • Tegan Maharaj
  • Vincent Mai
  • Victor Schmidt 
  • Simon Verret
  • Martin Weiss