Liu Gang

Liu Gang (born January 30, 1961) is a Chinese scientist who studies mathematical model, computer science, and theoretical physics. He also was one of the most visible of the student leaders in the Tiananmen Square protests of 1989. Liu holds a M.A. in computer science from Columbia University and a M.A. in physics from Peking University. After his exile to the United States in 1996, Liu studied technology and physics at Bell Labs in New Jersey. Liu is currently employed at Morgan Stanley as a Wall Street IT analyst.^[1]

As a major leader of the Chinese democracy movement, Liu Gang is a friend of fellow activists Wang Dan and Wuer Kaixi.^[2]

Biography

Liu Gang was born in 1961, Liaoyuan, Jilin. He was a politically active student at the Peking University department of physics, organizing "Democracy Salons" at his school, where Wang Dan later held a successful position. Earlier, Liu was an undergraduate student from University of Science and Technology of China in Hefei, where he made influence on Fang Lizhi.^[3] During the 1989 demonstrations, he organized the Beijing Students' Autonomous Federation and joined the movement's organizing body as a graduate of Peking University. As a result, he immediately became the third most wanted individual on the list of 21 fugitives issued following the protests.^[4] Liu went into hiding but was arrested on June 15 the same year, and sentenced to six years imprisonment at Qincheng Prison in 1991 following a guilty verdict on charges of attempted subversion of the Communist Party of China.^{[5][6][7][8][9][10]} After being released in 1996, he continued to protest for human rights in China and organized an underground democrat movement.^[11][12] Upon his exodus to the United States, Liu Gang pursued his studies at Columbia University in New York City.^[13][14][15] He continued to support the Chinese democracy movement from abroad, and is the originator of 2011 Chinese pro-democracy protests.^[16]

Scientific research

In China

In 1982, after he earned a Bachelor degree in Modern Mechanics from the University of Science and Technology of China Liu started his research in aerodynamics and worked as a designer at the Aviation Industry Corporation of China in Shenyang. He worked in partnership with Luo Yang before being named Head Aircraft Designer of a new aircraft design bureau in Shenyang in 1982. Liu Gang was involved in the theoretical research of air resistance. His major contributions included the solutions to a series of fundamental and critical theoretical problems of double-sided entry and radar technology, which led to breakthroughs in the design of high-tech aircraft. During the period that Liu worked in the bureau, they produced a series of Shenyang J-8 fighter aircraft's. Before that, as one of the first-generation fighter jets in China, the J8-1 had a poor start; after Liu's contributions to radar and fuselage design, the J-8II's launch marked the start of a period of modern-design of aircraft in China. The J-8II could then fight in its intended high-level interceptor role.

In 1984, Liu entered the Department of Physics at Peking University in Beijing and obtained an M.Sc. in optics; he also served there as a teaching assistant in physics.^[17] After graduation, he took office at the China Soft Science Research Institute, and acted as the assistant director of the University of Science and Technology of China. In 1988, he became an assistant and associate researcher, who specialized in and tested resistant materials, at the Wear-resistant Materials Development Company of the National Ministry of Higher Education & Dalian Institute of Technology. Before Liu emigrated to the United States, the Chinese Government intentionally arranged him entry to the Department of Physics at the Chinese Academy of Sciences as a researcher.

In the United States

After came to the United States, Liu received the Master of Computer Columbia University in 1996 and participated to be a speaker in New York Academy of Sciences.^[18] Subsequently, Liu is a member of technical staff in the "Mathematics of Networks and Systems Research Department" at Bell Labs in Murray Hill, New Jersey, where he worked on optical network design and planning, routing algorithms, optimization techniques, and economic model and strategy analysis for telecommunications networks.^[19] Liu's specific carried out research on topics including the SPIDER, a design tool for fast-restoration in all-optical networks; VPNStar, a system for provisioning multi-service VPNs with QoS guarantees over IP; SoftWave design, a management system for LambdaRouter in all-optical networks, and the analyst of Internet pricing.^[20]

During the days in Bell Labs, Liu introduced the A*Prune (1999, ISSN :0743-166X) with K. G. Ramakrishnan, to describe a new class of Algorithm. This opens up a new research direction in theoretical science. He found that A*Prune is comparable to the current best known-approximate algorithms for most of randomly generated graphs. The algorithm constructs paths starting at the source and going towards the destination. But, at each iteration, the algorithm gets rid of all paths that are guaranteed to violate the constraints, thereby keeping only those partial paths that have the potential to be turned into feasible paths, from which the optimal paths are drawn.^[21] He also proposed a special class of Optical devices, SPIDER (2001, ISSN :1089-7089) : optical routers, dense wavelength division multiplexing (DWDM) systems, and cross connects of unprecedented capacities are on the verge of large-scale commercial deployment. With R.Drew Davis and Krishnan Kumaran, and Iraj Saniee, Liu presents a range of techniques for efficient and reliable optical network design, covering decentralized dedicated protection to shared path-based mesh restoration. In particular, SPIDER provides the key tradeoffs in optical network designs involving a variety of grades of protection and the balance between efficient use of wavelengths and restoration time.^[22]

Works

• Gang Liu (2014). T-Forward Method: A Closed-Form Solution and Strongly Polynomial Time Approach for Convex Nonlinear Programming.^[23] Algorithms Research, Elmhurst, New York. DOI: 10.5923/j.algorithms.20140301.01.
• Gang Liu (2014). A Mathematic Model for Supply-Demand Equilibrium and the Optimal Solution for Labor Assignment.^[24] Algorithms Research, Elmhurst, New York. DOI: 10.5923/j.economics.20140402.01
• Gang Liu, R. D. Davis, K. Kumaran, I. Saniee (2001). SPIDER: A Simple and Flexible Tool for Design and Provisioning of Protected Lightpaths in Optical Networks.^[25] Bell Laboratories Technical Memorandum, Murray Hill, New Jersey.
• Gang Liu, K. G. Ramakrishnan (2000). A*Prune: An Algorithm for Finding K Shortest Paths Subject to Multiple Constraints.^[26] Bell Laboratories Technical Memorandum, Murray Hill, New Jersey. 1999. 10009626-000302-04TM.
• Gang Liu, E. Bouillet, I. Saniee (2000). Algorithms for DWDM Mesh Network Design: Routing and Wavelength Assignment for Dedicated Protection, Ring Auto-Recovery and Optical Cross-Connect Restoration in Core Optical Networks.^[27] Bell Laboratories Technical Memorandum, Murray Hill, New Jersey. 1999. 10009626-000126-01TM.
• Gang Liu and T. E. Stern (1999). An Algorithm for Optimal Routing and Wavelength Assignment on a Bi-directional Ring.^[28] Bell Laboratories Technical Memorandum, Murray Hill, New Jersey. BL0112120-990610-10TM.

References

External links

• Quatratic.com — A website solver for Convex Nonlinear Programming

Optimization: Algorithms, methods, and heuristics   Unconstrained nonlinear: Methods calling … … functions Golden section search Interpolation methods Line search Nelder–Mead method Successive parabolic interpolation … and gradients Convergence Trust region Wolfe conditions Quasi–Newton BFGS and L-BFGS DFP Symmetric rank-one (SR1) Other methods Gauss–Newton Gradient Levenberg–Marquardt Conjugate gradient … and Hessians Newton's method   Constrained nonlinear General Barrier methods Penalty methods Differentiable Augmented Lagrangian methods Sequential quadratic programming Successive linear programming   Convex optimization Convex minimization Cutting-plane method Reduced gradient (Frank–Wolfe) Subgradient method Linear and quadratic Interior point Ellipsoid algorithm of Khachiyan Projective algorithm of Karmarkar Basis-Exchange Simplex algorithm of Dantzig Revised simplex algorithm Criss-cross algorithm Principal pivoting algorithm of Lemke   Combinatorial Paradigms Approximation algorithm Dynamic programming Greedy algorithm Integer programming Branch & bound or cut Graph algorithms Minimum spanning tree Bellman–Ford Borůvka Dijkstra Floyd–Warshall Johnson Kruskal Network flows Dinic Edmonds–Karp Ford–Fulkerson Push-relabel maximum flow   Metaheuristics Evolutionary algorithm Hill climbing Local search Simulated annealing Tabu search Categories Algorithms and methods Heuristics Software