The Doctoral Program (DP) of the CP conference is open to all research students (including past participants) conducting research on constraint programming and related topics. The aim is to gather student researchers, discuss ongoing work in a relaxed atmosphere, and provide an opportunity for students to interact with experienced researchers.
The program is a full-day event. It includes short presentations of student papers, discussion with senior researchers and networking activities for researchers in similar areas. The day closes with a dinner.
Two researchers will reflect on their time in academia and industry.
Nina Narodytska is a senior researcher at VMware Research. Prior to VMware, she was a researcher at Samsung Research America. She completed postdoctoral studies in the Carnegie Mellon University School of Computer Science and the University of Toronto. She received her PhD from the University of New South Wales. Nina works on developing efficient search algorithms for decision and optimization problems. She was named one of "AI's 10 to Watch" researchers in the field of AI in 2013. She has presented invited talks and tutorials at FMCAD'18, CP'19, AAAI'20 and IJCAI'20.
Title: Industrial Research Career Path as a Sequence of Constraint Satisfaction Problems
Industrial career path is a multi-step journey where you make a constrained decision at each step. Each choice point leads you to the next environment, influences your research agenda and your next choice. Along this path, there will be additional circumstances that affect your choices, e.g., personal circumstances, leading to certain trade-offs. All these considerations turn each decision point into a fun constraint optimization problem! Your decisions might move across the globe a few times, lead to meeting new people, explore new research areas, publish papers or do tech transfers!
In the first part of the talk, I will share my personal path, my choices and considerations at that time. In the second part, we will discuss opportunities and challenges working in industrial research labs compared to the academic environment.
Simon de Givry
Simon de Givry is a full-time researcher in Toulouse, France, at INRAE since 2002. INRAE is the main public research institute in Agriculture, Food, and Environment in France. Before that, he was a research scientist at Thales Research & Technology. He got his Ph.D. in constraint programming and real-time artificial intelligent systems in 1998. His area of expertise is related to discrete constraint optimization (cost function networks), probabilistic graphical models (bayesian networks), and their applications in bioinformatics. He co-supervised four interdisciplinary Ph.D. students in genetics (linkage analysis), systems biology (gene regulatory network reconstruction), and agronomy (crop planning). He is the main maintainer of toulbar2, a state-of-the-art solver for graphical model optimization. The solver is currently used at INRAE in computational protein design.
Title: Interdisciplinary Research -- Cost Function Network for Life Sciences
Simon de Givry is a researcher at INRAE, a French national institute on agriculture, food, and the environment. He obtained his PhD on combinatorial optimization in 1998. He co-supervised five PhD students and will present parts of their work on interdisciplinary research. Two subjects are in bioinformatics, developing methodology on cost function networks and applying it to genetics and computational protein design problems. The last subject concerns crop planning problems in agronomy. Lessons from these studies will be presented to guide future PhD students doing a successful dissertation in interdisciplinary research.
The full program can also be found on EasyChair
Session 1 (90 min) 9:00-10:30
- 9:00 - Opening
- 9:05 - Invited Talk: Industrial Research Career Path as a Sequence of Constraint Satisfaction Problems, by Nina Narodytska
- 10:00 - Solving the Non-Crossing MAPF for non point-sized robots, by Xiao Peng, Olivier Simonin and Christine Solnon
- 10:20 - Scheduling the Equipment Maintenance of an Electric Power Transmission Network using Constraint Programming (extended abstract), by Louis Popovic, Alain Côté, Mohamed Gaha, Franklin Nguewouo and Quentin Cappart
- 10:23 - Sequence Variables for Routing Problems (extended abstract), by Augustin Delecluse, Pierre Schaus and Pascal Van Hentenryck
- 10:26 - Combining Reinforcement Learning and Constraint Programming for Sequence-Generation Tasks with Hard Constraints (extended abstract), by Daphné Lafleur, Sarath Chandar and Gilles Pesant
Coffee break and poster session 10:30-11:00
Session 2 (90 min) 11:00-12:30
- 11:00 - Invited Talk: Interdisciplinary Research -- Cost Function Network for Life Sciences, by Simon de Givry
- 11:55 - Automated SAT Problem Feature Extraction using 1 Convolutional Autoencoders, by Marco Dalla, Andrea Visentin and Barry O'Sullivan
- 12:15 - Selecting SAT Encodings for Pseudo-Boolean and Linear Integer Constraints (extended abstract), by Felix Ulrich-Oltean, Peter Nightingale and James Walker
- 12:18 - Peel-and-Bound: Generating Stronger Relaxed Bounds with Multivalued Decision Diagrams (extended abstract), by Isaac Rudich, Quentin Cappart and Louis-Martin Rousseau
- 12:21 - Solving the Constrained Single-Row Facility Layout Problem with Decision Diagrams (extended abstract), by Vianney Coppé, Xavier Gillard and Pierre Schaus
- 12:24 - CNF Encodings of Binary Constraint Trees (extended abstract), by Ruiwei Wang and Roland Yap
Session 3 (90 min) 14:00-15:30
- 14:00 - Aggressive Bound Descent for Constraint Optimization, by Thibault Falque, Christophe Lecoutre, Bertrand Mazure and Hugues Wattez
- 14:20 - Exploiting Model Entropy to Make Branching Decisions in Constraint Programming, by Auguste Burlats and Gilles Pesant
- 14:40 - Finding Counterfactual Explanations through Constraint Relaxations, by Sharmi Dev Gupta, Begum Genc and Barry O'Sullivan
- 15:00 - Symmetry breaking and Knowledge Compilation, by Andrea Balogh and Barry O'Sullivan
- 15:20 - Improved Sample Complexity Bounds for Branch-and-Cut (extended abstract), by Siddharth Prasad, Maria-Florina Balcan, Tuomas Sandholm and Ellen Vitercik
- 15:23 - Exploiting Functional Constraints in Automatic Dominance Breaking for Constraint Optimization (extended abstract), by Jimmy H. M. Lee and Allen Z. Zhong
- 15:26 - Large Neighborhood Search for Robust Solutions for Constraint Satisfaction Problems with Ordered Domains (extended abstract), by Jheisson López, Laura Climent and Alejandro Arbelaez
Coffee break and poster session 15:30-16:00
Session 4 (90 min) 16:00-17:30
- 16:00 - Optimized Code Generation against Power Side Channels, by Rodothea Myrsini Tsoupidi, Roberto Castaneda Lozano and Elena Troubitsyna
- 16:20 - Boolean Functional Synthesis and its Applications, by Priyanka Golia, Subhajit Roy and Kuldeep S. Meel
- 16:40 - On Pseudo-Boolean Encodings for PB Problems, by Thibault Falque and Romain Wallon
- 17:00 - A Boolean Formula Seeker in the Context of Acquiring Maps of Interrelated Conjectures on Sharp Bounds, by Ramiz Gindullin, Nicolas Beldiceanu and Jovial Cheukam Ngouonou
- 17:20 - Explaining Propagation for Gini and Spread with Variable Mean (extended abstract), by Alexander Ek, Andreas Schutt, Peter J. Stuckey and Guido Tack
- 17:23 - Constraint Acquisition Based on Solution Counting (extended abstract), by Christopher Coulombe and Claude-Guy Quimper
- 17:26 - Acquiring Maps of Interrelated Conjectures on Sharp Bounds (extended abstract), by Nicolas Beldiceanu, Jovial Cheukam Ngouonou, Rémi Douence, Ramiz Gindullin and Claude-Guy Quimper
The proceedings of the DP are available for download as a zip archive.
We would like to thanks the AI Journal, the ACP and the AFPC for their support. They allow us to support 14 students.
Questions about the doctoral program may be addressed to the Doctoral Program Chair Hélène Verhaeghe (firstname.lastname@example.org).