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 and MINLP) and solvers, with a particular focus on preprocessing and cut generation techniques for MILP, MIQCP, and MISOCP, and nonconvex MIQCP. At the same time, I developed predictive machine learning models for both 2B and 2C scenarios, e.g., the sales prediction problem, the pricing problem and the detection of marketing models. 

I am also an applied scientist in supply chain management with 3 years of working experience in supporting e-commerce supply chain (e.g., inventory management, inbound logistics,  staffing). Linking the fundamental development and the 2B/2C business scenarios, we promote  the idea of the guiding 2C business with the combination of predictive and planning models.  

In addition to my work on MIP solvers and supply chain optimization, I have also worked on developing predictive 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.e., virtual machine placement problem). 

I am highly enthusiastic about the emerging LLMs 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 at, Digital Supply Chain (TaoTian) 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.