Matthew Brand

Matthew Brand
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  • Biography

    Matt develops and analyzes optimization algorithms for problems in logistics, control, perception, data-mining, and learning. Notable results include methods for parallel solution of quadratic programs, recomposing photos by re-arranging pixels, nonlinear dimensionality reduction, online singular value decomposition, 3D shape-from-video, and learning concise models of data. In addition to academic "best paper" awards, this work has garnered several industrial awards for commercialized technologies.

  • Recent News & Events

    •  NEWS    MERL Researchers to Present 2 Conference and 11 Workshop Papers at NeurIPS 2024
      Date: December 10, 2024 - December 15, 2024
      Where: Advances in Neural Processing Systems (NeurIPS)
      MERL Contacts: Petros T. Boufounos; Matthew Brand; Ankush Chakrabarty; Anoop Cherian; François Germain; Toshiaki Koike-Akino; Christopher R. Laughman; Jonathan Le Roux; Jing Liu; Suhas Lohit; Tim K. Marks; Yoshiki Masuyama; Kieran Parsons; Kuan-Chuan Peng; Diego Romeres; Pu (Perry) Wang; Ye Wang; Gordon Wichern
      Research Areas: Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & Audio, Human-Computer Interaction, Information Security
      Brief
      • MERL researchers will attend and present the following papers at the 2024 Advances in Neural Processing Systems (NeurIPS) Conference and Workshops.

        1. "RETR: Multi-View Radar Detection Transformer for Indoor Perception" by Ryoma Yataka (Mitsubishi Electric), Adriano Cardace (Bologna University), Perry Wang (Mitsubishi Electric Research Laboratories), Petros Boufounos (Mitsubishi Electric Research Laboratories), Ryuhei Takahashi (Mitsubishi Electric). Main Conference. https://neurips.cc/virtual/2024/poster/95530

        2. "Evaluating Large Vision-and-Language Models on Children's Mathematical Olympiads" by Anoop Cherian (Mitsubishi Electric Research Laboratories), Kuan-Chuan Peng (Mitsubishi Electric Research Laboratories), Suhas Lohit (Mitsubishi Electric Research Laboratories), Joanna Matthiesen (Math Kangaroo USA), Kevin Smith (Massachusetts Institute of Technology), Josh Tenenbaum (Massachusetts Institute of Technology). Main Conference, Datasets and Benchmarks track. https://neurips.cc/virtual/2024/poster/97639

        3. "Probabilistic Forecasting for Building Energy Systems: Are Time-Series Foundation Models The Answer?" by Young-Jin Park (Massachusetts Institute of Technology), Jing Liu (Mitsubishi Electric Research Laboratories), François G Germain (Mitsubishi Electric Research Laboratories), Ye Wang (Mitsubishi Electric Research Laboratories), Toshiaki Koike-Akino (Mitsubishi Electric Research Laboratories), Gordon Wichern (Mitsubishi Electric Research Laboratories), Navid Azizan (Massachusetts Institute of Technology), Christopher R. Laughman (Mitsubishi Electric Research Laboratories), Ankush Chakrabarty (Mitsubishi Electric Research Laboratories). Time Series in the Age of Large Models Workshop.

        4. "Forget to Flourish: Leveraging Model-Unlearning on Pretrained Language Models for Privacy Leakage" by Md Rafi Ur Rashid (Penn State University), Jing Liu (Mitsubishi Electric Research Laboratories), Toshiaki Koike-Akino (Mitsubishi Electric Research Laboratories), Shagufta Mehnaz (Penn State University), Ye Wang (Mitsubishi Electric Research Laboratories). Workshop on Red Teaming GenAI: What Can We Learn from Adversaries?

        5. "Spatially-Aware Losses for Enhanced Neural Acoustic Fields" by Christopher Ick (New York University), Gordon Wichern (Mitsubishi Electric Research Laboratories), Yoshiki Masuyama (Mitsubishi Electric Research Laboratories), François G Germain (Mitsubishi Electric Research Laboratories), Jonathan Le Roux (Mitsubishi Electric Research Laboratories). Audio Imagination Workshop.

        6. "FV-NeRV: Neural Compression for Free Viewpoint Videos" by Sorachi Kato (Osaka University), Takuya Fujihashi (Osaka University), Toshiaki Koike-Akino (Mitsubishi Electric Research Laboratories), Takashi Watanabe (Osaka University). Machine Learning and Compression Workshop.

        7. "GPT Sonography: Hand Gesture Decoding from Forearm Ultrasound Images via VLM" by Keshav Bimbraw (Worcester Polytechnic Institute), Ye Wang (Mitsubishi Electric Research Laboratories), Jing Liu (Mitsubishi Electric Research Laboratories), Toshiaki Koike-Akino (Mitsubishi Electric Research Laboratories). AIM-FM: Advancements In Medical Foundation Models: Explainability, Robustness, Security, and Beyond Workshop.

        8. "Smoothed Embeddings for Robust Language Models" by Hase Ryo (Mitsubishi Electric), Md Rafi Ur Rashid (Penn State University), Ashley Lewis (Ohio State University), Jing Liu (Mitsubishi Electric Research Laboratories), Toshiaki Koike-Akino (Mitsubishi Electric Research Laboratories), Kieran Parsons (Mitsubishi Electric Research Laboratories), Ye Wang (Mitsubishi Electric Research Laboratories). Safe Generative AI Workshop.

        9. "Slaying the HyDRA: Parameter-Efficient Hyper Networks with Low-Displacement Rank Adaptation" by Xiangyu Chen (University of Kansas), Ye Wang (Mitsubishi Electric Research Laboratories), Matthew Brand (Mitsubishi Electric Research Laboratories), Pu Wang (Mitsubishi Electric Research Laboratories), Jing Liu (Mitsubishi Electric Research Laboratories), Toshiaki Koike-Akino (Mitsubishi Electric Research Laboratories). Workshop on Adaptive Foundation Models.

        10. "Preference-based Multi-Objective Bayesian Optimization with Gradients" by Joshua Hang Sai Ip (University of California Berkeley), Ankush Chakrabarty (Mitsubishi Electric Research Laboratories), Ali Mesbah (University of California Berkeley), Diego Romeres (Mitsubishi Electric Research Laboratories). Workshop on Bayesian Decision-Making and Uncertainty. Lightning talk spotlight.

        11. "TR-BEACON: Shedding Light on Efficient Behavior Discovery in High-Dimensions with Trust-Region-based Bayesian Novelty Search" by Wei-Ting Tang (Ohio State University), Ankush Chakrabarty (Mitsubishi Electric Research Laboratories), Joel A. Paulson (Ohio State University). Workshop on Bayesian Decision-Making and Uncertainty.

        12. "MEL-PETs Joint-Context Attack for the NeurIPS 2024 LLM Privacy Challenge Red Team Track" by Ye Wang (Mitsubishi Electric Research Laboratories), Tsunato Nakai (Mitsubishi Electric), Jing Liu (Mitsubishi Electric Research Laboratories), Toshiaki Koike-Akino (Mitsubishi Electric Research Laboratories), Kento Oonishi (Mitsubishi Electric), Takuya Higashi (Mitsubishi Electric). LLM Privacy Challenge. Special Award for Practical Attack.

        13. "MEL-PETs Defense for the NeurIPS 2024 LLM Privacy Challenge Blue Team Track" by Jing Liu (Mitsubishi Electric Research Laboratories), Ye Wang (Mitsubishi Electric Research Laboratories), Toshiaki Koike-Akino (Mitsubishi Electric Research Laboratories), Tsunato Nakai (Mitsubishi Electric), Kento Oonishi (Mitsubishi Electric), Takuya Higashi (Mitsubishi Electric). LLM Privacy Challenge. Won 3rd Place Award.

        MERL members also contributed to the organization of the Multimodal Algorithmic Reasoning (MAR) Workshop (https://marworkshop.github.io/neurips24/). Organizers: Anoop Cherian (Mitsubishi Electric Research Laboratories), Kuan-Chuan Peng (Mitsubishi Electric Research Laboratories), Suhas Lohit (Mitsubishi Electric Research Laboratories), Honglu Zhou (Salesforce Research), Kevin Smith (Massachusetts Institute of Technology), Tim K. Marks (Mitsubishi Electric Research Laboratories), Juan Carlos Niebles (Salesforce AI Research), Petar Veličković (Google DeepMind).
    •  
    •  NEWS    MERL Papers and Workshops at CVPR 2024
      Date: June 17, 2024 - June 21, 2024
      Where: Seattle, WA
      MERL Contacts: Petros T. Boufounos; Moitreya Chatterjee; Anoop Cherian; Michael J. Jones; Toshiaki Koike-Akino; Jonathan Le Roux; Suhas Lohit; Tim K. Marks; Pedro Miraldo; Jing Liu; Kuan-Chuan Peng; Pu (Perry) Wang; Ye Wang; Matthew Brand
      Research Areas: Artificial Intelligence, Computational Sensing, Computer Vision, Machine Learning, Speech & Audio
      Brief
      • MERL researchers are presenting 5 conference papers, 3 workshop papers, and are co-organizing two workshops at the CVPR 2024 conference, which will be held in Seattle, June 17-21. CVPR is one of the most prestigious and competitive international conferences in computer vision. Details of MERL contributions are provided below.

        CVPR Conference Papers:

        1. "TI2V-Zero: Zero-Shot Image Conditioning for Text-to-Video Diffusion Models" by H. Ni, B. Egger, S. Lohit, A. Cherian, Y. Wang, T. Koike-Akino, S. X. Huang, and T. K. Marks

        This work enables a pretrained text-to-video (T2V) diffusion model to be additionally conditioned on an input image (first video frame), yielding a text+image to video (TI2V) model. Other than using the pretrained T2V model, our method requires no ("zero") training or fine-tuning. The paper uses a "repeat-and-slide" method and diffusion resampling to synthesize videos from a given starting image and text describing the video content.

        Paper: https://www.merl.com/publications/TR2024-059
        Project page: https://merl.com/research/highlights/TI2V-Zero

        2. "Long-Tailed Anomaly Detection with Learnable Class Names" by C.-H. Ho, K.-C. Peng, and N. Vasconcelos

        This work aims to identify defects across various classes without relying on hard-coded class names. We introduce the concept of long-tailed anomaly detection, addressing challenges like class imbalance and dataset variability. Our proposed method combines reconstruction and semantic modules, learning pseudo-class names and utilizing a variational autoencoder for feature synthesis to improve performance in long-tailed datasets, outperforming existing methods in experiments.

        Paper: https://www.merl.com/publications/TR2024-040

        3. "Gear-NeRF: Free-Viewpoint Rendering and Tracking with Motion-aware Spatio-Temporal Sampling" by X. Liu, Y-W. Tai, C-T. Tang, P. Miraldo, S. Lohit, and M. Chatterjee

        This work presents a new strategy for rendering dynamic scenes from novel viewpoints. Our approach is based on stratifying the scene into regions based on the extent of motion of the region, which is automatically determined. Regions with higher motion are permitted a denser spatio-temporal sampling strategy for more faithful rendering of the scene. Additionally, to the best of our knowledge, ours is the first work to enable tracking of objects in the scene from novel views - based on the preferences of a user, provided by a click.

        Paper: https://www.merl.com/publications/TR2024-042

        4. "SIRA: Scalable Inter-frame Relation and Association for Radar Perception" by R. Yataka, P. Wang, P. T. Boufounos, and R. Takahashi

        Overcoming the limitations on radar feature extraction such as low spatial resolution, multipath reflection, and motion blurs, this paper proposes SIRA (Scalable Inter-frame Relation and Association) for scalable radar perception with two designs: 1) extended temporal relation, generalizing the existing temporal relation layer from two frames to multiple inter-frames with temporally regrouped window attention for scalability; and 2) motion consistency track with a pseudo-tracklet generated from observational data for better object association.

        Paper: https://www.merl.com/publications/TR2024-041

        5. "RILA: Reflective and Imaginative Language Agent for Zero-Shot Semantic Audio-Visual Navigation" by Z. Yang, J. Liu, P. Chen, A. Cherian, T. K. Marks, J. L. Roux, and C. Gan

        We leverage Large Language Models (LLM) for zero-shot semantic audio visual navigation. Specifically, by employing multi-modal models to process sensory data, we instruct an LLM-based planner to actively explore the environment by adaptively evaluating and dismissing inaccurate perceptual descriptions.

        Paper: https://www.merl.com/publications/TR2024-043

        CVPR Workshop Papers:

        1. "CoLa-SDF: Controllable Latent StyleSDF for Disentangled 3D Face Generation" by R. Dey, B. Egger, V. Boddeti, Y. Wang, and T. K. Marks

        This paper proposes a new method for generating 3D faces and rendering them to images by combining the controllability of nonlinear 3DMMs with the high fidelity of implicit 3D GANs. Inspired by StyleSDF, our model uses a similar architecture but enforces the latent space to match the interpretable and physical parameters of the nonlinear 3D morphable model MOST-GAN.

        Paper: https://www.merl.com/publications/TR2024-045

        2. “Tracklet-based Explainable Video Anomaly Localization” by A. Singh, M. J. Jones, and E. Learned-Miller

        This paper describes a new method for localizing anomalous activity in video of a scene given sample videos of normal activity from the same scene. The method is based on detecting and tracking objects in the scene and estimating high-level attributes of the objects such as their location, size, short-term trajectory and object class. These high-level attributes can then be used to detect unusual activity as well as to provide a human-understandable explanation for what is unusual about the activity.

        Paper: https://www.merl.com/publications/TR2024-057

        MERL co-organized workshops:

        1. "Multimodal Algorithmic Reasoning Workshop" by A. Cherian, K-C. Peng, S. Lohit, M. Chatterjee, H. Zhou, K. Smith, T. K. Marks, J. Mathissen, and J. Tenenbaum

        Workshop link: https://marworkshop.github.io/cvpr24/index.html

        2. "The 5th Workshop on Fair, Data-Efficient, and Trusted Computer Vision" by K-C. Peng, et al.

        Workshop link: https://fadetrcv.github.io/2024/

        3. "SuperLoRA: Parameter-Efficient Unified Adaptation for Large Vision Models" by X. Chen, J. Liu, Y. Wang, P. Wang, M. Brand, G. Wang, and T. Koike-Akino

        This paper proposes a generalized framework called SuperLoRA that unifies and extends different variants of low-rank adaptation (LoRA). Introducing new options with grouping, folding, shuffling, projection, and tensor decomposition, SuperLoRA offers high flexibility and demonstrates superior performance up to 10-fold gain in parameter efficiency for transfer learning tasks.

        Paper: https://www.merl.com/publications/TR2024-062
    •  

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  • Research Highlights

  • MERL Publications

    •  Chen, X., Wang, Y., Brand, M., Wang, P., Liu, J., Koike-Akino, T., "Slaying the HyDRA: Parameter-Efficient Hyper Networks with Low-Displacement Rank Adaptation", Advances in Neural Information Processing Systems (NeurIPS), December 2024.
      BibTeX TR2024-157 PDF Presentation
      • @inproceedings{Chen2024dec,
      • author = {{Chen, Xiangyu and Wang, Ye and Brand, Matthew and Wang, Pu and Liu, Jing and Koike-Akino, Toshiaki}},
      • title = {Slaying the HyDRA: Parameter-Efficient Hyper Networks with Low-Displacement Rank Adaptation},
      • booktitle = {Workshop on Adaptive Foundation Models: Evolving AI for Personalized and Efficient Learning at Neural Information Processing Systems (NeurIPS)},
      • year = 2024,
      • month = dec,
      • url = {https://www.merl.com/publications/TR2024-157}
      • }
    •  Chen, X., Liu, J., Wang, Y., Wang, P., Brand, M., Wang, G., Koike-Akino, T., "SuperLoRA: Parameter-Efficient Unified Adaptation of Large Foundation Models", British Machine Vision Conference (BMVC), November 2024.
      BibTeX TR2024-156 PDF Presentation
      • @inproceedings{Chen2024nov,
      • author = {{Chen, Xiangyu and Liu, Jing and Wang, Ye and Wang, Pu and Brand, Matthew and Wang, Guanghui and Koike-Akino, Toshiaki}},
      • title = {SuperLoRA: Parameter-Efficient Unified Adaptation of Large Foundation Models},
      • booktitle = {British Machine Vision Conference (BMVC)},
      • year = 2024,
      • month = nov,
      • url = {https://www.merl.com/publications/TR2024-156}
      • }
    •  Chen, X., Liu, J., Wang, Y., Wang, P., Brand, M., Wang, G., Koike-Akino, T., "SuperLoRA: Parameter-Efficient Unified Adaptation for Large Vision Models", IEEE Conference on Computer Vision and Pattern Recognition (CVPR), DOI: 10.1109/​CVPRW63382.2024.00804, June 2024, pp. 8050-8055.
      BibTeX TR2024-062 PDF Presentation
      • @inproceedings{Chen2024jun,
      • author = {{Chen, Xiangyu and Liu, Jing and Wang, Ye and Wang, Pu and Brand, Matthew and Wang, Guanghui and Koike-Akino, Toshiaki}},
      • title = {SuperLoRA: Parameter-Efficient Unified Adaptation for Large Vision Models},
      • booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
      • year = 2024,
      • pages = {8050--8055},
      • month = jun,
      • publisher = {IEEE},
      • doi = {10.1109/CVPRW63382.2024.00804},
      • url = {https://www.merl.com/publications/TR2024-062}
      • }
    •  Chen, X., Liu, J., Wang, Y., Wang, P., Brand, M., Wang, G., Koike-Akino, T., "SuperLoRA: Parameter-Efficient Unified Adaptation of Multi-Layer Attention Modules", arXiv, March 2024.
      BibTeX arXiv
      • @article{Chen2024mar,
      • author = {Chen, Xiangyu and Liu, Jing and Wang, Ye and Wang, Pu and Brand, Matthew and Wang, Guanghui and Koike-Akino, Toshiaki},
      • title = {SuperLoRA: Parameter-Efficient Unified Adaptation of Multi-Layer Attention Modules},
      • journal = {arXiv},
      • year = 2024,
      • month = mar,
      • url = {https://arxiv.org/abs/2403.11887}
      • }
    •  Basu, S., Lohit, S., Brand, M., "G-RepsNet: A Fast and General Construction of Equivariant Networks for Arbitrary Matrix Groups", arXiv, February 2024.
      BibTeX arXiv
      • @article{Basu2024feb,
      • author = {Basu, Sourya and Lohit, Suhas and Brand, Matthew},
      • title = {G-RepsNet: A Fast and General Construction of Equivariant Networks for Arbitrary Matrix Groups},
      • journal = {arXiv},
      • year = 2024,
      • month = feb,
      • url = {https://arxiv.org/abs/2402.15413}
      • }
    See All MERL Publications for Matt

  • Software & Data Downloads

  • Videos

  • MERL Issued Patents

    • Title: "System and Method for Generating Optimal Lattice Tool Paths"
      Inventors: Brand, Matthew E.
      Patent No.: 11,392,105
      Issue Date: Jul 19, 2022
    • Title: "Machine Learning via Double Layer Optimization"
      Inventors: Zhang, Ziming; Brand, Matthew E.
      Patent No.: 11,170,301
      Issue Date: Nov 9, 2021
    • Title: "Uniform-irradiance extended-source freeforms"
      Inventors: Brand, Matthew E.; Birch, Daniel
      Patent No.: 10,995,932
      Issue Date: May 4, 2021
    • Title: "Methods and Systems for Freeform Irradiance Tailoring for Light Fields"
      Inventors: Brand, Matthew E.; Birch, Daniel
      Patent No.: 10,837,621
      Issue Date: Nov 17, 2020
    • Title: "Compound Optics with Freeform Optical Surface"
      Inventors: Brand, Matthew E.
      Patent No.: 10,234,689
      Issue Date: Mar 19, 2019
    • Title: "Freeform Optical Surface for Producing Sharp-Edged Irradiance Patterns"
      Inventors: Brand, Matthew E.
      Patent No.: 10,119,679
      Issue Date: Nov 6, 2018
    • Title: "Tailored Freeform Optical Surface"
      Inventors: Brand, Matthew E.; Aksoylar, Aydan
      Patent No.: 9,869,866
      Issue Date: Jan 16, 2018
    • Title: "Method for Determining a Sequence for Drilling Holes According to a Pattern using Global and Local Optimization"
      Inventors: Garaas, Tyler W; Brand, Matthew E.
      Patent No.: 9,703,915
      Issue Date: Jul 11, 2017
    • Title: "MPC controller using parallel quadratic programming"
      Inventors: Di Cairano, Stefano; Brand, Matthew E.
      Patent No.: 9,618,912
      Issue Date: Apr 11, 2017
    • Title: "Method for Generating Representations Polylines Using Piecewise Fitted Geometric Primitives"
      Inventors: Brand, Matthew E.; Marks, Tim; MV, Rohith
      Patent No.: 9,613,443
      Issue Date: Apr 4, 2017
    • Title: "Method for Generating Trajectory for Numerical Control Process"
      Inventors: Brand, Matthew E.; Agrawal, Amit K.; Erdim, Huseyin
      Patent No.: 9,513,623
      Issue Date: Dec 6, 2016
    • Title: "System and Method for Planning a Radiation Therapy Treatment"
      Inventors: Brand, Matthew E.
      Patent No.: 9,251,302
      Issue Date: Feb 2, 2016
    • Title: "Method and System for Cutting Features From Sheet Materials With a Laser Cutter According to a Pattern"
      Inventors: Garaas, Tyler W.; Brand, Matthew E.; Josef, Cibulka
      Patent No.: 9,248,525
      Issue Date: Feb 2, 2016
    • Title: "Method for Reconstructing 3D Lines from 2D Lines in an Image"
      Inventors: Ramalingam, Srikumar; Brand, Matthew E.
      Patent No.: 9,183,635
      Issue Date: Nov 10, 2015
    • Title: "Determining Trajectories of Redundant Actuators Jointly Tracking Reference Trajectory"
      Inventors: Shilpiekandula, Vijay; Brand, Matthew E.; Srikanth, Manohar; Bortoff, Scott A.
      Patent No.: 9,170,580
      Issue Date: Oct 27, 2015
    • Title: "System and Method for Controlling Machines According to Pattern of Contours"
      Inventors: Brand, Matthew E.
      Patent No.: 9,104,192
      Issue Date: Aug 11, 2015
    • Title: "Method and System for Detouring Around Features Cut From Sheet Materials with a Laser Cutter According to a Pattern"
      Inventors: Garaas, Tyler W.; Brand, Matthew E.
      Patent No.: 9,046,888
      Issue Date: Jun 2, 2015
    • Title: "Method for Scheduling Cars in Elevator Systems to Minimizes Round-Trip Times"
      Inventors: Brand, Matthew E.
      Patent No.: 8,950,555
      Issue Date: Feb 10, 2015
    • Title: "Method for Performing Image Processing Applications Using Quadratic Programming"
      Inventors: Brand, Matthew E.; Chen, Dongui
      Patent No.: 8,761,533
      Issue Date: Jun 24, 2014
    • Title: "Method for Solving Control Problems"
      Inventors: Brand, Matthew E.; Yao, Chen; Shilpiekandula, Vijay
      Patent No.: 8,554,343
      Issue Date: Oct 8, 2013
    • Title: "Method for Optimization Radiotherapy Particle Beams"
      Inventors: Brand, Matthew E.
      Patent No.: 8,492,735
      Issue Date: Jul 23, 2013
    • Title: "Motion Planning for Elevator Cars Moving Independently in One Elevator Shaft"
      Inventors: Brand, Matthew E.
      Patent No.: 8,424,651
      Issue Date: Apr 23, 2013
    • Title: "Motion Planning for Elevator Cars Moving Independently in One Elevator Shaft"
      Inventors: Brand, Matthew E.
      Patent No.: 8,424,650
      Issue Date: Apr 23, 2013
    • Title: "Content Aware Resizing of Images and Videos"
      Inventors: Brand, Matthew E.; Shamir, Ariel; Rubinstein, Michael; Avidan, Shmuel
      Patent No.: 8,380,010
      Issue Date: Feb 19, 2013
    • Title: "Method and System for Localizing in Urban Environments From Omni-Direction Skyline Images"
      Inventors: Ramalingam, Srikumar; Brand, Matthew E.
      Patent No.: 8,311,285
      Issue Date: Nov 13, 2012
    • Title: "Method for Temporally Editing Video"
      Inventors: Brand, Matthew E.
      Patent No.: 8,290,298
      Issue Date: Oct 16, 2012
    • Title: "Method for Editing Images and Videos"
      Inventors: Brand, Matthew E.
      Patent No.: 8,290,297
      Issue Date: Oct 16, 2012
    • Title: "Method for Determining a Location From Images Acquired of an Environment with an Omni-Directional Camera"
      Inventors: Ramalingam, Srikumar; Brand, Matthew E.; Bouaziz, Sofien
      Patent No.: 8,249,302
      Issue Date: Aug 21, 2012
    • Title: "Method and Apparatus for Touching-Up Images"
      Inventors: Brand, Matthew E.; Pletscher, Patrick A.
      Patent No.: 8,160,396
      Issue Date: Apr 17, 2012
    • Title: "Resource Allocation for Rateless Transmissions"
      Inventors: Brand, Matthew E.
      Patent No.: 8,155,048
      Issue Date: Apr 10, 2012
    • Title: "Method for Routing Packets in Wireless Ad-Hoc Networks withProbabilistic Delay Guarantees"
      Inventors: Molisch, Andreas F.; Brand, Matthew E.; Maymounkov, Petar B.
      Patent No.: 8,040,810
      Issue Date: Oct 18, 2011
    • Title: "Method for Routing Packets in Ad-Hoc Networks with Partial Channel State Information"
      Inventors: Molisch, Andreas F.; Brand, Matthew E.
      Patent No.: 7,822,029
      Issue Date: Oct 26, 2010
    • Title: "Method for Finding Minimal Cost Paths under Uncertainty"
      Inventors: Nikolova, Evdokia V.; Brand, Matthew E.
      Patent No.: 7,756,021
      Issue Date: Jul 13, 2010
    • Title: "Method and System for Determining Instantaneous Peak Power Consumption in Elevator Banks"
      Inventors: Brand, Matthew E.; Nikovski, Daniel N.
      Patent No.: 7,743,890
      Issue Date: Jun 29, 2010
    • Title: "Method for Finding Optimal Paths Using a Stochastic NetworkModel"
      Inventors: Mitzenmacher, Michael D.; Brand, Matthew E.; Nikolova, Evdokia V.
      Patent No.: 7,573,866
      Issue Date: Aug 11, 2009
    • Title: "System and Method for Scheduling Elevator Cars Using Pairwise Delay Minimization"
      Inventors: Nikovski, Daniel N.; Brand, Matthew E.; Ebner, Dietmar
      Patent No.: 7,546,905
      Issue Date: Jun 16, 2009
    • Title: "System and Method for Scheduling Elevator Cars Using Branch-and-Bound"
      Inventors: Brand, Matthew E.; Nikovski, Daniel N.; Ebner, Dietmar
      Patent No.: 7,484,597
      Issue Date: Feb 3, 2009
    • Title: "On-Line Recommender System"
      Inventors: Brand, Matthew E.
      Patent No.: 7,475,027
      Issue Date: Jan 6, 2009
    • Title: "Method for Generating a Low-Dimensional Representation of High-Dimensional Data"
      Inventors: Brand, Matthew E.
      Patent No.: 7,412,098
      Issue Date: Aug 12, 2008
    • Title: "Incremental Singular Value Decomposition of Incomplete Data"
      Inventors: Brand, Matthew E.
      Patent No.: 7,359,550
      Issue Date: Apr 15, 2008
    • Title: "Variable Multilinear Models for Facial Synthesis"
      Inventors: Brand, Matthew E.
      Patent No.: 7,133,048
      Issue Date: Nov 7, 2006
    • Title: "Method and System for Scheduling Cars in Elevator Systems Considering Existing and Future Passengers"
      Inventors: Brand, Matthew E.; Nikovski, Daniel N.
      Patent No.: 7,014,015
      Issue Date: Mar 21, 2006
    • Title: "Method for Determining Poses of Sensors"
      Inventors: Brand, Matthew E.
      Patent No.: 7,006,944
      Issue Date: Feb 28, 2006
    • Title: "Modeling Shapes, Motions, Flexions and Textures of Non-Rigid 3D Objects Directly from Video"
      Inventors: Brand, Matthew E.
      Patent No.: 7,006,683
      Issue Date: Feb 28, 2006
    • Title: "Method for Mapping High-Dimensional Samples to Reduced-Dimensional Manifolds"
      Inventors: Brand, Matthew E.
      Patent No.: 6,947,042
      Issue Date: Sep 20, 2005
    • Title: "Rendering Deformable 3D Models Recovered from Videos"
      Inventors: Brand, Matthew E.
      Patent No.: 6,873,724
      Issue Date: Mar 29, 2005
    • Title: "Analysis, Synthesis and Control of Data Signals with Temporal Textures Using a Linear Dynamic System"
      Inventors: Brand, Matthew E.
      Patent No.: 6,864,897
      Issue Date: Mar 8, 2005
    • Title: "Optimal Parking of Free Cars in Elevator Group Control"
      Inventors: Brand, Matthew E.; Nikovski, Daniel N.
      Patent No.: 6,808,049
      Issue Date: Oct 26, 2004
    • Title: "Method for Generating Realistic Facial Animation Directly from Speech Utilizing Hidden Markov Models"
      Inventors: Brand, Matthew E.
      Patent No.: 6,735,566
      Issue Date: May 11, 2004
    • Title: "Method and System for Dynamic Programming of Elevators for Optimal Group Elevator Control"
      Inventors: Brand, Matthew E.; Nikovski, Daniel N.
      Patent No.: 6,672,431
      Issue Date: Jan 6, 2004
    • Title: "Method for Acquiring Static and Dynamic Super-Resolution Texture Maps from Video"
      Inventors: Brand, Matthew E.
      Patent No.: 6,650,335
      Issue Date: Nov 18, 2003
    • Title: "Method for Designing Optimal Single Pointer Predictive Keyboards and Apparatus Therefore"
      Inventors: Brand, Matthew E.
      Patent No.: 6,646,572
      Issue Date: Nov 11, 2003
    • Title: "Method for Predicting Keystroke Characters on Single Pointer Keyboards and Apparatus Therefore"
      Inventors: Brand, Matthew E.
      Patent No.: 6,621,424
      Issue Date: Sep 16, 2003
    • Title: "Method for Inferring Target Paths from Related Cue Paths"
      Inventors: Brand, Matthew E.
      Patent No.: 6,459,808
      Issue Date: Oct 1, 2002
    • Title: "System for Having Concise Models from a Signal Utilizing a Hidden Markov Model"
      Inventors: Brand, Matthew E.
      Patent No.: 6,212,510
      Issue Date: Apr 3, 2001
    • Title: "Markov Model Discriminator Using Negative Examples"
      Inventors: Brand, Matthew E.
      Patent No.: 6,112,021
      Issue Date: Aug 29, 2000
    See All Patents for MERL