update members

Author: erachelson

former-members.md

@@ -1,18 +1,19 @@
 ## Former members
 
-- Sandrine Berger (Post-doc 2019-, M. Bauerheim, T. Jardin, E. Rachelson) — Fluid flow control with RL  
+- Valentin Guillet (PhD 2019-2022, C. Aguilar, E. Rachelson) — Neural network distillation for generalization and transfer in Reinforcement Learning
+- Sandrine Berger (Post-doc 2019-2021, M. Bauerheim, T. Jardin, E. Rachelson) — Fluid flow control with RL  
 - Erwan Lecarpentier (Post-doc 2021-2022, D. Wilson) — Image-based CGP for Atari  
 - Antoine Stevan (PhD track student 2020-2021, E. Rachelson) — Emergence of communication for RL coordination  
 - Mathis Clautrier (PhD track student 2019-2021, D. Wilson) — Eye-tracking and RL saliency maps  
-- Thibault Lahire (PhD track student 2020-2021, M. Geist, E. Rachelson) — Importance sampling in Reinforcement Learning.
+- Thibault Lahire (PhD track student 2020-2021, M. Geist, E. Rachelson) — Importance sampling in Reinforcement Learning
 - Ilyass Haloui (PhD 2019-2021, C. Chanel, A. Haït) — Predictive Maintenance via Sequential Decision Making
 - François Lamothe (PhD 2018-2021, A. Haït, E. Rachelson) — Unsplittable Multicommodity flows
 - Sana Ikli (PhD 2017-2021, C. Mancel, M. Mongeau, X. Olive, E. Rachelson) —  Coupling OR and ML methods for Aircraft Landing Scheduling
 - Erwan Lecarpentier (PhD 2016-2020, C. Lesire-Cabaniols, G. Infantes, E. Rachelson) — Reinforcement learning in non-stationary environments
-- Luca Mossina (PhD 2016-2020, D. Delahaye, E. Rachelson) — Applications of Machine Learning to the Resolution of Recurrent Combinatorial Optimization Problems.
-- Ankit Chiplunkar (PhD 2015-2017, J. Morlier, E. Rachelson) — Incorporating Prior Information from Engineering Design into Gaussian Process Regression, applications to Aeronautical Engineering.
-- 2020-2021 interns: C. Cuny, E. Chigot  (Evolutionary RL), H. Sanchez (RL saliency maps), R. Garsuault (Robustness to model uncertainties).
-- 2019-2020 interns: P. Carfantan (Prioritized Experience Replay in Soft Actor Critic algorithms), Andrea Arroyo-Ramos (Fluid control with RL), P.-L. Saint (Progressive Neural Networks), L. Hervier (co-evolution of agents and environments), T. Cormier (reward-modulated STDP), Paul Templier (Neuroevolution for RL), Pablo Miralles, Vincent Coyette (Domain Adaptation in DuckieTown).
-- 2018-2019 interns: Andres Quintela-Quintanilla (robustness and transfer in Deep RL), L. Bertomier, V. Guillet (Neural Consolidation in RL), I. Bouayad (Why is Rainbow sometimes underperforming?), G. Marugan-Rubio (iBoat stall avoidance), E. Dupont (off-policy critics for DDPG).
-- 2017-2018 interns: N. Megel, A. Bonet-Munoz, T. Karch (iBoat stall avoidance), F. Brulport, J.-M. Belley, P. Barde (iBoat navigation planning), Augustin Parjadis (Deep TD(lambda)), P. Planeix (Exoskeleton control with Deep RL), J.-J. Simeoni (robustness and transfer in Deep RL), V. Guillet (Deep RL agents).
-- 2016-2017 interns: L. Becq, A. Bufort, H. Akhmouch, T. Le Minh, E. Herlaut, N. El Jaafari, S. Ganapathi-Raju, R. Madelaine, E. Lecarpentier (Learning to fly), L. Mossina (Multi-label Naive Bayes Classification).
+- Luca Mossina (PhD 2016-2020, D. Delahaye, E. Rachelson) — Applications of Machine Learning to the Resolution of Recurrent Combinatorial Optimization Problems
+- Ankit Chiplunkar (PhD 2015-2017, J. Morlier, E. Rachelson) — Incorporating Prior Information from Engineering Design into Gaussian Process Regression, applications to Aeronautical Engineering
+- 2020-2021 interns: C. Cuny, E. Chigot  (Evolutionary RL), H. Sanchez (RL saliency maps), R. Garsuault (Robustness to model uncertainties)
+- 2019-2020 interns: P. Carfantan (Prioritized Experience Replay in Soft Actor Critic algorithms), Andrea Arroyo-Ramos (Fluid control with RL), P.-L. Saint (Progressive Neural Networks), L. Hervier (co-evolution of agents and environments), T. Cormier (reward-modulated STDP), Paul Templier (Neuroevolution for RL), Pablo Miralles, Vincent Coyette (Domain Adaptation in DuckieTown)
+- 2018-2019 interns: Andres Quintela-Quintanilla (robustness and transfer in Deep RL), L. Bertomier, V. Guillet (Neural Consolidation in RL), I. Bouayad (Why is Rainbow sometimes underperforming?), G. Marugan-Rubio (iBoat stall avoidance), E. Dupont (off-policy critics for DDPG)
+- 2017-2018 interns: N. Megel, A. Bonet-Munoz, T. Karch (iBoat stall avoidance), F. Brulport, J.-M. Belley, P. Barde (iBoat navigation planning), Augustin Parjadis (Deep TD(lambda)), P. Planeix (Exoskeleton control with Deep RL), J.-J. Simeoni (robustness and transfer in Deep RL), V. Guillet (Deep RL agents)
+- 2016-2017 interns: L. Becq, A. Bufort, H. Akhmouch, T. Le Minh, E. Herlaut, N. El Jaafari, S. Ganapathi-Raju, R. Madelaine, E. Lecarpentier (Learning to fly), L. Mossina (Multi-label Naive Bayes Classification)

index.md

@@ -39,10 +39,13 @@ Industrial Eng., Constraint Programming  <br />
 <a href="https://cv.archives-ouvertes.fr/catherinemancel">Catherine Mancel</a> — ENAC associate professor — Optimization, Air Traffic Management  <br />
 <a href="https://www.ut-capitole.fr/m-herve-luga--229143.kjsp">Hervé Luga</a> — Université Toulouse 1 Professor — Artificial life  <br />
 <a href="https://cerco.cnrs.fr/pagesp/tim/">Timothée Masquelier</a> — CNRS CerCo senior researcher — Computational neuroscience  <br />
+<a href="https://cedric.cnam.fr/~kedadsis/">Safia Kedad-Sidhoum</a> — CNAM professor — Operations Research <br />
+<a href="https://sites.google.com/site/zacharieales/">Zacharie Ales</a> — ENSTA associate professor — Operations Research <br />
 </details> 
 <br />
 Current Post-docs, PhD students and interns:  
-[Hedwin Bonnavaud](https://personnel.isae-supaero.fr/hedwin-bonnavaud/) (PhD 2021-, C. Chanel, C. Lesire, A. Albore, E. Rachelson) —  Planning and RL for robot tasks  
+[Paul Strang](https://www.linkedin.com/in/paul-strang-362754150/) (PhD 2022-, S. Kedad-Sidhoum, Z. Ales, E. Rachelson) — Solving repeated combinatorial optimization problems with machine learning  
+[Hedwin Bonnavaud](https://personnel.isae-supaero.fr/hedwin-bonnavaud/) (PhD 2021-, C. Chanel, C. Lesire, A. Albore, E. Rachelson) — Planning and RL for robot tasks  
 [Paul-Antoine Le Tolguenec](https://www.linkedin.com/in/paul-antoine-le-tolguenec-128b4018a) (PhD 2021-, D. Wilson, E. Rachelson) — Autopilot testing with RL  
 [Adil Zoutine](https://boring-guy.sh/) (PhD 2021-, E. Rachelson) — Robustness to model uncertainties in RL  
 [Mehdi Zouitine](https://mehdi-zouitine.netlify.app/) (PhD 2021-,  A. Lagnoux, C. Pellegrini, E. Rachelson), RL for heterogeneous space observation missions planning  
@@ -51,7 +54,6 @@ Current Post-docs, PhD students and interns:
 [Paul Templier](https://templierpaul.github.io/) (intern 2020, PhD 2020-, D. Wilson, E. Rachelson) — Bio-inspired Learning for Artificial Neural Networks  
 [Brice Martin](https://www.linkedin.com/in/brice-martin-b4b0a8155) (PhD 2020-, M. Bauerheim, T. Jardin, E. Rachelson) — Aircraft control with RL  
 [David Bertoin](https://davidbert.github.io/) (PhD 2019-, S. Gerchinovitz, E. Rachelson) — Generalization in RL  
-Valentin Guillet (PhD 2019-, C. Aguilar, E. Rachelson) — Transfer and Neural Consolidation in RL  
 
 The "former members" list has grown quite long over time and can be found [here](former-members.html).