Guanglei Wang

My name is Guanglei Wang and I am currently a research scientist at Alibaba Group. My research interests lie in mathematical programming-based optimization methods, robust optimization, combinatorial optimization, and their various applications in supply chain management, telecommunications and power systems. Recently, I have been working on developing open-source solvers and modeling platforms with some excellent colleagues. You can find a brief summary of my research experience here. I am also an applied scientist in constrained optimization, heuristics and deep learning. 

My main area of expertise is in developing Mixed-Integer Programming (MIP) solvers, with a particular focus on preprocessing and cut generation techniques for MILP, MIQCP, and MISOCP. I have extensive experience in developing MIQP, MIQCP and MISOCP solvers that have consistently outperformed open-source solvers (without relying on problem-specific fine-tuning tricks), and have even surpassed some commercial ones (COPT, CPLEX) by a significant margin.  If you would like further details on my work, please don't hesitate to contact me.

In addition to my work on MIP solvers, I have also worked on developing (Deep) Reinforcement Learning-based methods to enhance the efficiency of autonomous outbound calling systems, as well as creating heuristics to solve inventory and supply chain optimization problems such as transshipment and truck hauling. I am the author of AUTO-RO, a robust optimization software that is widely used in the Alibaba economy. Furthermore, I have collaborated on the development of Gravity, an award-winning mathematical programming language, alongside Dr. Hassan Hijazi. Prior to my work on optimization softwares, I worked at Orange Labs Research (Paris), where I tackled virtual network optimization problems.

I am highly enthusiastic about the emerging LLMs (e.g., ChatGPT, GPT4) and their potential to accelerate the development of traditional MIP solver development. This could lead to the creation of a new generation of computing paradigms.

I am actively exploring technical positions in data science (ideally combining optimization, coding and deep learning) worldwide. 

Career 

• Research Scientist  and Staff Research Scientist in Damo Academy, Alibaba Group, Hangzhou, China (Nov 2020-now)

• Applied Scientist in Digital Supply Chain Team, Alibaba Group, Hangzhou, China (Sep 2018-Oct 2020)

• Research Fellow in the Australian National University, Canberra, Australia (Feb 2017-June 2018)

• Research Engineer in Orange Labs Research (France Telecom),  Paris (June 2013- June 2016)

•  PhD in Computer Science from Telecom SudParis and Paris 6 University (Nov 2016)

• Intern in Orange Labs Research (France Telecom), Paris (July 2012- Dec 2012)

•  MSc degree in Operations research in the University of Edinburgh (Dec 2012) 

•  B.Eng in Management Science and Engineering in Zhengzhou University (Aeronautics) (June 2011)

Journal Publications

• Exploiting sparsity for the min-k partition problem, Mathematical Programming Computation,  joint work with Hassan Hijazi (2019).

• A Lagrange decomposition based branch and bound algorithm for the optimal mapping of cloud virtual machines, European journal of operations research,  joint work with Walid Ben-Ameur and Adam Ouorou (2019). 

• Gravity: A Mathematical Modeling Language for Optimization and Machine Learning, NIPS 2018 Workshop MLOSS, joint work with Hassan Hijazi and Carleton Coffrin (2018). 

• Mathematical programming methods for microgrid design and operations,  Computational Optimization and Applications, joint work with Hassan Hijazi (2018).

• Exploiting sparsity for the min-k partition problem, Mathematical Programming Computation,  joint work with Hassan Hijazi (2017).

• Multipolar robust optimization,  joint work with Walid Ben-Ameur and Adam Ouorou. European journal on computational optimization (2016).

• Convex and concave envelopes: revisited and new perspectives, joint work with Walid Ben-Ameur and Adam Ouorou, Operations Research letters (2016).

• Optimal mapping of cloud virtual machines, joint work with Walid Ben-Ameur and Adam Ouorou, Electronic Notes in Discrete Math (2015). 

• My phd thesis on "Relaxations in mixed integer quadratically constrained programming and robust programming". 

On-going work

• A convergent hierarchy for solving disjoint bilinear problems. 

• Reduction methods in MIQP and MIQCP: a computational study. 

Selected Presentations

• Mathematical programming, the Alibaba Group, Hangzhou, China(July 2018)

• Mathematical programming in power systems, the Australian National University, Canberra, Australia (July 2017).

• Multipolar robust optimization, NICTA, Canberra, Australia (March 2017).

• Multipolar robust optimization, Brno,  APMOD 2016 (8-10 June, Brno, APMOD 2016).

• New perspectives in bilinear optimization, Institute Henri Poincaré, Paris (Nov 2015).

• Optimal mapping of cloud virtual machines, HuaWei, Boulogne-Billancourt, France (July 2015).

Awards

• 2021 COIN-OR Cup with Dr. Hassan Hijazi and other fabulous colleagues.

Tutorials

Introduction to mathematical optimisation (The Australian National University, Nov. 2017) 

Profession service 

• Reviewer of journal articles: Mathematical Programming, Mathematical Programming Computation, European Journal of Operational Research,  European Journal on Computational Optimization, Operations Research Letters, Computational optimization and applications, Computers & Operations Research.

I like camping with my family.  A number of interesting camping areas can be found here.