What is he best known for?
The fields of study he is best known for:
- Statistics
- Algorithm
- Artificial intelligence
His main research concerns Mathematical optimization, Algorithm, Convex optimization, Optimization problem and Beamforming.
Wing-Kin Ma has included themes like MIMO, Artificial noise, Channel state information and Robustness in his Mathematical optimization study.
In the subject of general Algorithm, his work in Recursion is often linked to Gaussian process, thereby combining diverse domains of study.
His work in the fields of Convex analysis overlaps with other areas such as Linear programming, Hyperspectral imaging, RGB color model and Contextual image classification.
The study incorporates disciplines such as Relay channel, Relay, Upper and lower bounds and Communication channel in addition to Optimization problem.
His Beamforming research is multidisciplinary, incorporating perspectives in Relaxation and Multicast.
His most cited work include:
- Semidefinite Relaxation of Quadratic Optimization Problems (1824 citations)
- The Gaussian Mixture Probability Hypothesis Density Filter (1328 citations)
- Least squares algorithms for time-of-arrival-based mobile location (409 citations)
What are the main themes of his work throughout his whole career to date?
Wing-Kin Ma mainly focuses on Algorithm, Mathematical optimization, Beamforming, MIMO and Hyperspectral imaging.
Many of his research projects under Algorithm are closely connected to Matrix decomposition with Matrix decomposition, tying the diverse disciplines of science together.
His Mathematical optimization research incorporates elements of Communication channel and Robustness.
His Beamforming study also includes fields such as
- Telecommunications link together with Precoding and Base station,
- Channel state information that intertwine with fields like Relay.
His work in MIMO tackles topics such as Orthogonal frequency-division multiplexing which are related to areas like Multipath propagation.
Wing-Kin Ma combines subjects such as Pixel and Algorithm design with his study of Hyperspectral imaging.
He most often published in these fields:
- Algorithm (51.98%)
- Mathematical optimization (36.90%)
- Beamforming (21.43%)
What were the highlights of his more recent work (between 2016-2021)?
- Algorithm (51.98%)
- MIMO (18.65%)
- Precoding (9.13%)
In recent papers he was focusing on the following fields of study:
Wing-Kin Ma mainly investigates Algorithm, MIMO, Precoding, Matrix decomposition and Beamforming.
His work deals with themes such as Probabilistic logic, Hyperspectral imaging, Identifiability and Robustness, which intersect with Algorithm.
His MIMO research is multidisciplinary, incorporating elements of Quantization, Artificial neural network, Modulation, Iterative method and Electronic engineering.
His Precoding study also includes fields such as
- Telecommunications link which is related to area like Base station, Constant envelope and Distortion,
- Quadrature amplitude modulation which intersects with area such as Phase-shift keying,
- QAM which is related to area like Signal-to-noise ratio,
- Spectral efficiency, which have a strong connection to Bit error rate.
His research in Beamforming intersects with topics in Quadratically constrained quadratic program, Channel state information, Communication channel, Relaxation and Optimization problem.
His Optimization problem research entails a greater understanding of Mathematical optimization.
Between 2016 and 2021, his most popular works were:
- Nonnegative Matrix Factorization for Signal and Data Analytics: Identifiability, Algorithms, and Applications (73 citations)
- Hyperspectral Super-Resolution: A Coupled Tensor Factorization Approach (62 citations)
- A Framework for One-Bit and Constant-Envelope Precoding Over Multiuser Massive MISO Channels (36 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Algorithm
- Artificial intelligence
Wing-Kin Ma spends much of his time researching Algorithm, Precoding, MIMO, Hyperspectral imaging and Matrix decomposition.
His work focuses on many connections between Algorithm and other disciplines, such as Identifiability, that overlap with his field of interest in Data analysis and Hidden Markov model.
His Precoding research is multidisciplinary, relying on both Beamforming, Spectral efficiency, Optimization problem, Telecommunications link and Quadrature amplitude modulation.
To a larger extent, Wing-Kin Ma studies Mathematical optimization with the aim of understanding Optimization problem.
His MIMO research integrates issues from Noise, Iterative method, Electronic engineering and Modulation.
His study in the field of Non-negative matrix factorization is also linked to topics like Inscribed figure, Convex optimization and Ellipsoid.
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