News & Events

120 were found.




  •  NEWS   Computer vision and robotics researcher Siddarth Jain appointed as an Associate Editor for the IEEE Robotics and Automation Letters (RA-L)
    Date: October 13, 2020
    MERL Contact: Siddarth Jain
    Research Areas: Artificial Intelligence, Computer Vision, Machine Learning, Robotics
    Brief
    • Computer vision and robotics researcher, Siddarth Jain, has been appointed to the editorial board of the IEEE Robotics and Automation Letters (RA-L) as an Associate Editor. Siddarth joined MERL in September 2019 after obtaining his Ph.D. in robotics from Northwestern University, where he developed novel robotics systems to help people with motor-impairments in performing activities of daily living tasks.

      RA-L publishes peer-reviewed articles in areas of robotics and automation. RA-L also provides a unique feature to the authors with the opportunity to publish a paper in a peer-reviewed journal and present the same paper at the annual flagship robotics conferences of IEEE RAS, including ICRA, IROS, and CASE.
  •  
  •  AWARD   Best Poster Award and Best Video Award at the International Society for Music Information Retrieval Conference (ISMIR) 2020
    Date: October 15, 2020
    Awarded to: Ethan Manilow, Gordon Wichern, Jonathan Le Roux
    MERL Contacts: Jonathan Le Roux; Gordon Wichern
    Research Areas: Artificial Intelligence, Machine Learning, Speech & Audio
    Brief
    • Former MERL intern Ethan Manilow and MERL researchers Gordon Wichern and Jonathan Le Roux won Best Poster Award and Best Video Award at the 2020 International Society for Music Information Retrieval Conference (ISMIR 2020) for the paper "Hierarchical Musical Source Separation". The conference was held October 11-14 in a virtual format. The Best Poster Awards and Best Video Awards were awarded by popular vote among the conference attendees.

      The paper proposes a new method for isolating individual sounds in an audio mixture that accounts for the hierarchical relationship between sound sources. Many sounds we are interested in analyzing are hierarchical in nature, e.g., during a music performance, a hi-hat note is one of many such hi-hat notes, which is one of several parts of a drumkit, itself one of many instruments in a band, which might be playing in a bar with other sounds occurring. Inspired by this, the paper re-frames the audio source separation problem as hierarchical, combining similar sounds together at certain levels while separating them at other levels, and shows on a musical instrument separation task that a hierarchical approach outperforms non-hierarchical models while also requiring less training data. The paper, poster, and video can be seen on the paper page on the ISMIR website.
  •  
  •  NEWS   Diego Romeres serves on the Programme Committee for the Conference on Innovative Applications of Artificial Intelligence, 2021.
    Date: February 4, 2021
    Where: N/A
    MERL Contact: Diego Romeres
    Research Areas: Artificial Intelligence, Data Analytics, Machine Learning
    Brief
    • Dr. Diego Romeres, Principal Research Scientist in the Data Analytics group, will serve on the Programme Committee for the Thirty-Third Annual Conference on Innovative Applications of Artificial Intelligence (IAAI), 2021.
  •  
  •  NEWS   Anoop Cherian gave an invited talk at the Multi-modal Video Analysis Workshop, ECCV 2020
    Date: August 23, 2020
    Where: European Conference on Computer Vision (ECCV), online, 2020
    MERL Contact: Anoop Cherian
    Research Areas: Artificial Intelligence, Computer Vision, Machine Learning, Speech & Audio
    Brief
    • MERL Principal Research Scientist Anoop Cherian gave an invited talk titled "Sound2Sight: Audio-Conditioned Visual Imagination" at the Multi-modal Video Analysis workshop held in conjunction with the European Conference on Computer Vision (ECCV), 2020. The talk was based on a recent ECCV paper that describes a new multimodal reasoning task called Sound2Sight and a generative adversarial machine learning algorithm for producing plausible video sequences conditioned on sound and visual context.
  •  
  •  NEWS   MERL Researcher Ankush Chakrabarty organized a special session on data-driven control at IEEE CCTA 2020
    Date: August 25, 2020
    MERL Contact: Ankush Chakrabarty
    Research Areas: Artificial Intelligence, Control, Data Analytics, Dynamical Systems, Machine Learning, Optimization, Robotics
    Brief
    • Ankush Chakrabarty co-organized an invited session on “Data-Driven Control For Industrial Applications” at the IEEE Conference on Control Technology and Applications with Shahin Shahrampour (Asst. Prof., Texas A&M). Talks covered topics including reinforcement learning for aerospace systems, constrained reinforcement learning for motors, deep Q learning for traffic systems and participants included speakers from Stanford University, North Carolina State University, Texas A&M, Oklahoma State University, University of Science and Technology at Beijing, and TU Delft.

      MERL presented research (Chakrabarty, Danielson, Wang) on constraint-enforcing output-tracking with approximate dynamic programming for servomotor systems.
  •  
  •  NEWS   Dr. Abraham P. Vinod joins the Research Staff of Mitsubishi Electric Research Laboratories
    Date: August 3, 2020
    Where: Cambridge, MA
    MERL Contact: Abraham P. Vinod
    Research Areas: Artificial Intelligence, Control, Optimization, Robotics
    Brief
    • Mitsubishi Electric Research Laboratories is excited to welcome Abraham P. Vinod as the newest member of its research staff, in the Control for Autonomy Team. Abraham joins MERL from the University of Texas, Austin, where he was a Postdoctoral Research Fellow. He obtained his Ph.D. from the University of New Mexico. His PhD research produced scalable algorithms for providing safety guarantees for stochastic, control-constrained, dynamical systems, with applications to motion planning. In his postdoctoral research, Abraham studied theory and algorithms for on-the-fly, data-driven control of unknown systems under severely limited data. His current research interests lie in the intersection of optimization, control, and learning. Abraham won the Best Student Paper Award at the 2017 ACM Hybrid Systems: Computation and Control Conference, was a finalist for the Best Paper Award in the 2018 ACM Hybrid Systems: Computation and Control Conference, and won the best undergraduate student research project award at the Indian Institute of Technology, Madras.
  •  
  •  NEWS   MERL's Scene-Aware Interaction Technology Featured in Mitsubishi Electric Corporation Press Release
    Date: July 22, 2020
    Where: Tokyo, Japan
    MERL Contacts: Siheng Chen; Anoop Cherian; Bret Harsham; Chiori Hori; Takaaki Hori; Jonathan Le Roux; Tim Marks; Alan Sullivan; Anthony Vetro
    Research Areas: Artificial Intelligence, Computer Vision, Machine Learning, Speech & Audio
    Brief
    • Mitsubishi Electric Corporation announced that the company has developed what it believes to be the world’s first technology capable of highly natural and intuitive interaction with humans based on a scene-aware capability to translate multimodal sensing information into natural language.

      The novel technology, Scene-Aware Interaction, incorporates Mitsubishi Electric’s proprietary Maisart® compact AI technology to analyze multimodal sensing information for highly natural and intuitive interaction with humans through context-dependent generation of natural language. The technology recognizes contextual objects and events based on multimodal sensing information, such as images and video captured with cameras, audio information recorded with microphones, and localization information measured with LiDAR.

      Scene-Aware Interaction for car navigation, one target application, will provide drivers with intuitive route guidance. The technology is also expected to have applicability to human-machine interfaces for in-vehicle infotainment, interaction with service robots in building and factory automation systems, systems that monitor the health and well-being of people, surveillance systems that interpret complex scenes for humans and encourage social distancing, support for touchless operation of equipment in public areas, and much more. The technology is based on recent research by MERL's Speech & Audio and Computer Vision groups.


      Demonstration Video:



      Link:

      Mitsubishi Electric Corporation Press Release
  •  
  •  NEWS   Jonathan Le Roux gives Plenary Lecture at the JSALT 2020 Summer Workshop
    Date: July 10, 2020
    Where: Virtual Baltimore, MD
    MERL Contact: Jonathan Le Roux
    Research Areas: Artificial Intelligence, Machine Learning, Speech & Audio
    Brief
    • MERL Senior Principal Research Scientist and Speech and Audio Senior Team Leader Jonathan Le Roux was invited by the Center for Language and Speech Processing at Johns Hopkins University to give a plenary lecture at the 2020 Frederick Jelinek Memorial Summer Workshop on Speech and Language Technology (JSALT). The talk, entitled "Deep Learning for Multifarious Speech Processing: Tackling Multiple Speakers, Microphones, and Languages", presented an overview of deep learning techniques developed at MERL towards the goal of cracking the Tower of Babel version of the cocktail party problem, that is, separating and/or recognizing the speech of multiple unknown speakers speaking simultaneously in multiple languages, in both single-channel and multi-channel scenarios: from deep clustering to chimera networks, phasebook and friends, and from seamless ASR to MIMO-Speech and Transformer-based multi-speaker ASR.

      JSALT 2020 is the seventh in a series of six-week-long research workshops on Machine Learning for Speech Language and Computer Vision Technology. A continuation of the well known Johns Hopkins University summer workshops, these workshops bring together diverse "dream teams" of leading professionals, graduate students, and undergraduates, in a truly cooperative, intensive, and substantive effort to advance the state of the science. MERL researchers led such teams in the JSALT 2015 workshop, on "Far-Field Speech Enhancement and Recognition in Mismatched Settings", and the JSALT 2018 workshop, on "Multi-lingual End-to-End Speech Recognition for Incomplete Data".
  •  
  •  NEWS   MERL researchers presenting three papers at ICML 2020
    Date: July 12, 2020 - July 18, 2020
    Where: Vienna, Austria (virtual this year)
    MERL Contacts: Mouhacine Benosman; Anoop Cherian; Devesh Jha; Daniel Nikovski
    Research Areas: Artificial Intelligence, Computer Vision, Data Analytics, Dynamical Systems, Machine Learning, Optimization, Robotics
    Brief
    • MERL researchers are presenting three papers at the International Conference on Machine Learning (ICML 2020), which is virtually held this year from 12-18th July. ICML is one of the top-tier conferences in machine learning with an acceptance rate of 22%. The MERL papers are:

      1) "Finite-time convergence in Continuous-Time Optimization" by Orlando Romero and Mouhacine Benosman.

      2) "Can Increasing Input Dimensionality Improve Deep Reinforcement Learning?" by Kei Ota, Tomoaki Oiki, Devesh Jha, Toshisada Mariyama, and Daniel Nikovski.

      3) "Representation Learning Using Adversarially-Contrastive Optimal Transport" by Anoop Cherian and Shuchin Aeron.
  •  
  •  NEWS   Zhong-Qiu Wang joins MERL's Speech and Audio Team
    Date: June 22, 2020
    MERL Contact: Zhong-Qiu Wang
    Research Areas: Artificial Intelligence, Machine Learning, Speech & Audio
    Brief
    • We are excited to announce that Dr. Zhong-Qiu Wang, who recently obtained his Ph.D. from The Ohio State University, has joined MERL's Speech and Audio Team as a Visiting Research Scientist. Zhong-Qiu brings strong expertise in microphone array processing, speech enhancement, blind source/speaker separation, and robust automatic speech recognition, for which he has developed some of the most advanced machine learning and deep learning methods.

      Prior to joining MERL, Zhong-Qiu received the B.Eng. degree in 2013 from Harbin Institute of Technology, Harbin, China, and the M.Sc. and Ph.D. degree in 2017 and 2020 from The Ohio State University, Columbus, USA, all in Computer Science. He was a summer research intern at Microsoft Research, Mitsubishi Electric Research Laboratories, and Google AI. He received a Best Student Paper Award at ICASSP 2018 for his work as an intern at MERL, and a Graduate Research Award from OSU Department of Computer Science and Engineering in 2020.
  •  
  •  NEWS   MERL researchers presenting four papers and organizing two workshops at CVPR 2020 conference
    Date: June 14, 2020 - June 19, 2020
    MERL Contacts: Siheng Chen; Anoop Cherian; Michael Jones; Toshiaki Koike-Akino; Tim Marks; Kuan-Chuan Peng; Ye Wang
    Research Areas: Artificial Intelligence, Computer Vision, Machine Learning
    Brief
    • MERL researchers are presenting four papers (two oral papers and two posters) and organizing two workshops at the IEEE/CVF Computer Vision and Pattern Recognition (CVPR 2020) conference.

      CVPR 2020 Orals with MERL authors:
      1. "Dynamic Multiscale Graph Neural Networks for 3D Skeleton Based Human Motion Prediction," by Maosen Li, Siheng Chen, Yangheng Zhao, Ya Zhang, Yanfeng Wang, Qi Tian
      2. "Collaborative Motion Prediction via Neural Motion Message Passing," by Yue Hu, Siheng Chen, Ya Zhang, Xiao Gu

      CVPR 2020 Posters with MERL authors:
      3. "LUVLi Face Alignment: Estimating Landmarks’ Location, Uncertainty, and Visibility Likelihood," by Abhinav Kumar, Tim K. Marks, Wenxuan Mou, Ye Wang, Michael Jones, Anoop Cherian, Toshiaki Koike-Akino, Xiaoming Liu, Chen Feng
      4. "MotionNet: Joint Perception and Motion Prediction for Autonomous Driving Based on Bird’s Eye View Maps," by Pengxiang Wu, Siheng Chen, Dimitris N. Metaxas

      CVPR 2020 Workshops co-organized by MERL researchers:
      1. Fair, Data-Efficient and Trusted Computer Vision
      2. Deep Declarative Networks.
  •  
  •  NEWS   Diego Romeres gave an invited talk on modeling and control of physical systems at the MIT workshop "ICRAxMIT"
    Date: June 9, 2020
    Where: ICRAxMIT
    MERL Contact: Diego Romeres
    Research Areas: Artificial Intelligence, Data Analytics, Dynamical Systems, Machine Learning, Robotics
    Brief
    • Diego Romeres, a Principal Research Scientist in MERL's Data Analytics group, gave an invited talk at the workshop ICRAxMIT organized at MIT. The talk briefly described a derivative-free framework that doesn't take in consideration velocities and accelerations to model and control robotic systems. The proposed approach is validated in two real robotic systems.
  •  
  •  NEWS   MERL Researcher Pu (Perry) Wang organized a special session on automotive radar sensing at IEEE SAM Workshop 2020
    Date: June 8, 2020 - June 12, 2020
    Where: Virtual Hangzhou
    MERL Contact: Pu (Perry) Wang
    Research Areas: Artificial Intelligence, Computational Sensing, Dynamical Systems, Machine Learning, Signal Processing
    Brief
    • MERL researcher Pu (Perry) Wang organized a special session on June 10, 2020 titled Automotive Radar Sensing. Presentations included topics from deep waveform design, object tracking, mutual interference mitigation with their applications to high-resolution automotive imaging. The session's contributors come from both academia and industry.

      In this special session, our previous intern Yuxuan Xia (Chalmers Institute of Technology, Sweden) presented our work on extended object tracking using low-cost automotive radar sensors with a realistic measurement model. Yuxuan was also selected to be one of the six best student paper finalists at IEEE SAM 2020.
  •  
  •  TALK   A Prospect in Wireless Connectivity Beyond 5G: Heterogeneity, Learning, Caution, and New Opportunities
    Date & Time: Thursday, May 7, 2020; 11:00 AM
    Speaker: Prof. Petar Popovski, Aalborg University, Denmark
    MERL Host: Toshiaki Koike-Akino
    Research Areas: Artificial Intelligence, Communications, Machine Learning, Signal Processing, Information Security
    Brief
    • The wireless landscape evolves towards supporting a large population of connections for humans and machines with very diverse features and requirements. Perhaps the main motivation of 5G wireless systems is its flexibility to support heterogeneous connectivity requirements: enhanced mobile broadband (eMBB), massive machine-type communications (mMTC), and ultra-reliable low-latency communications (URLLC). However, this classification is rather limited and is currently undergoing a revision within the research community. The first part of this talk will discuss how this heterogeneity can be revised and which opportunities it opens with respect to spectrum usage. The second part of the talk will deal with performance guarantees of wireless services and, specifically, ultra-reliable communication and outline the importance of machine learning in that context. The final part of the talk will provide a broader view on the evolution of wireless connectivity, including aspects that are implied by the resistance to the deployment of 5G, but also the new opportunities that can transform the way we build and utilize connected systems.
  •  
  •  NEWS   Diego Romeres appointed as an Associate Editor for IROS 2020
    Date: February 14, 2020
    Where: 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems
    MERL Contact: Diego Romeres
    Research Areas: Artificial Intelligence, Data Analytics, Robotics
    Brief
    • Diego Romeres, a Research Scientist in MERL's Data Analytics group, will be serving as an Associate Editor (AE) for the 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2020).
  •  
  •  AWARD   Best Paper Award at the IEEE Automatic Speech Recognition and Understanding Workshop (ASRU) 2019
    Date: December 18, 2019
    Awarded to: Xuankai Chang, Wangyou Zhang, Yanmin Qian, Jonathan Le Roux, Shinji Watanabe
    MERL Contact: Jonathan Le Roux
    Research Areas: Artificial Intelligence, Machine Learning, Speech & Audio
    Brief
    • MERL researcher Jonathan Le Roux and co-authors Xuankai Chang, Shinji Watanabe (Johns Hopkins University), Wangyou Zhang, and Yanmin Qian (Shanghai Jiao Tong University) won the Best Paper Award at the 2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU 2019), for the paper "MIMO-Speech: End-to-End Multi-Channel Multi-Speaker Speech Recognition". MIMO-Speech is a fully neural end-to-end framework that can transcribe the text of multiple speakers speaking simultaneously from multi-channel input. The system is comprised of a monaural masking network, a multi-source neural beamformer, and a multi-output speech recognition model, which are jointly optimized only via an automatic speech recognition (ASR) criterion. The award was received by lead author Xuankai Chang during the conference, which was held in Sentosa, Singapore from December 14-18, 2019.
  •  
  •  NEWS   MERL researcher Diego Romeres gave an invited talk at University of Connecticut on Reinforcement Learning for Robotics
    Date: November 20, 2019
    MERL Contact: Diego Romeres
    Research Areas: Artificial Intelligence, Data Analytics, Machine Learning, Robotics
    Brief
    • Diego Romeres, a Research Scientist in MERL's Data Analytics group, gave a seminar lecture at the Electrical and Computer Engineering Colloquium of the University of Connecticut. The talk described novel reinforcement algorithms based on combining physical models with non-parametric models of robotic systems derived from data.
  •  
  •  NEWS   Takaaki Hori elected to IEEE Technical Committee on Speech and Language Processing
    Date: November 9, 2019
    MERL Contact: Takaaki Hori
    Research Areas: Artificial Intelligence, Machine Learning, Speech & Audio
    Brief
    • Takaaki Hori has been elected to serve on the Speech and Language Processing Technical Committee (SLTC) of the IEEE Signal Processing Society for a 3-year term.

      The SLTC promotes and influences all the technical areas of speech and language processing such as speech recognition, speech synthesis, spoken language understanding, speech to speech translation, spoken dialog management, speech indexing, information extraction from audio, and speaker and language recognition.
  •  
  •  AWARD   MERL Researchers win Best Paper Award at ICCV 2019 Workshop on Statistical Deep Learning in Computer Vision
    Date: October 27, 2019
    Awarded to: Abhinav Kumar, Tim K. Marks, Wenxuan Mou, Chen Feng, Xiaoming Liu
    MERL Contact: Tim Marks
    Research Areas: Artificial Intelligence, Computer Vision, Machine Learning
    Brief
    • MERL researcher Tim Marks, former MERL interns Abhinav Kumar and Wenxuan Mou, and MERL consultants Professor Chen Feng (NYU) and Professor Xiaoming Liu (MSU) received the Best Oral Paper Award at the IEEE/CVF International Conference on Computer Vision (ICCV) 2019 Workshop on Statistical Deep Learning in Computer Vision (SDL-CV) held in Seoul, Korea. Their paper, entitled "UGLLI Face Alignment: Estimating Uncertainty with Gaussian Log-Likelihood Loss," describes a method which, given an image of a face, estimates not only the locations of facial landmarks but also the uncertainty of each landmark location estimate.
  •  
  •  AWARD   MERL Researcher Devesh Jha Wins the Rudolf Kalman Best Paper Award 2019
    Date: October 10, 2019
    Awarded to: Devesh Jha, Nurali Virani, Zhenyuan Yuan, Ishana Shekhawat and Asok Ray
    MERL Contact: Devesh Jha
    Research Areas: Artificial Intelligence, Control, Data Analytics, Machine Learning, Robotics
    Brief
    • MERL researcher Devesh Jha has won the Rudolf Kalman Best Paper Award 2019 for the paper entitled "Imitation of Demonstrations Using Bayesian Filtering With Nonparametric Data-Driven Models". This paper, published in a Special Commemorative Issue for Rudolf E. Kalman in the ASME JDSMC in March 2018, uses Bayesian filtering for imitation learning in Hidden Mode Hybrid Systems. This award is given annually by the Dynamic Systems and Control Division of ASME to the authors of the best paper published in the ASME Journal of Dynamic Systems Measurement and Control during the preceding year.
  •  
  •  NEWS   MERL Scientists Presenting 5 Papers including 2 Invited Talks at European Conference on Optical Communication (ECOC) 2019
    Date: September 22, 2019 - September 26, 2019
    MERL Contacts: Devesh Jha; Toshiaki Koike-Akino; Keisuke Kojima; David Millar; Kieran Parsons; Ye Wang
    Research Areas: Artificial Intelligence, Communications, Electronic and Photonic Devices, Optimization, Signal Processing
    Brief
    • MERL Optical Team scientists will be presenting 5 papers including 2 invited talks at the 45th European Conference on Optical Communication (ECOC) 2019, which is being held in Dublin from September 22-26, 2019. Topics to be presented include recent advances in sophisticated constellation shaping schemes, lattice coding, and deep learning-based turbo equalization to mitigate fiber nonlinearity. Dr. Kojima is giving an invited workshop talk on deep learning-based nano-photonic device optimization. Dr. Tobias Fehenberger, a former Visiting Scientist is giving an invited talk related to our joint paper "Mapping Strategies for Short-Length Probabilistic Shaping"

      ECOC is the largest optical communications event in Europe and a key meeting place for more than 1,500 scientists and researchers from institutions and companies across the world. The conference features more than 400 oral and poster presentations from various major telecoms industries and universities. As well as being one of the largest scientific conferences globally, ECOC also features Europe’s largest optical communications exhibition.
  •  
  •  NEWS   MERL Speech & Audio Researchers Presenting 7 Papers and a Tutorial at Interspeech 2019
    Date: September 15, 2019 - September 19, 2019
    Where: Graz, Austria
    MERL Contacts: Chiori Hori; Takaaki Hori; Jonathan Le Roux; Niko Moritz; Gordon Wichern
    Research Areas: Artificial Intelligence, Machine Learning, Speech & Audio
    Brief
    • MERL Speech & Audio Team researchers will be presenting 7 papers at the 20th Annual Conference of the International Speech Communication Association INTERSPEECH 2019, which is being held in Graz, Austria from September 15-19, 2019. Topics to be presented include recent advances in end-to-end speech recognition, speech separation, and audio-visual scene-aware dialog. Takaaki Hori is also co-presenting a tutorial on end-to-end speech processing.

      Interspeech is the world's largest and most comprehensive conference on the science and technology of spoken language processing. It gathers around 2000 participants from all over the world.
  •  
  •  NEWS   Ankush Chakrabarty gave an invited talk on machine learning for constrained control at AI for Engineering in Toronto
    Date: August 19, 2019 - August 23, 2019
    Where: AI for Engineering Summer School 2019
    MERL Contact: Ankush Chakrabarty
    Research Areas: Artificial Intelligence, Control, Dynamical Systems, Machine Learning
    Brief
    • Ankush Chakrabarty, a Visiting Research Scientist in MERL's Control and Dynamical Systems group, gave an invited talk at the AI for Engineering Summer School 2019 hosted by Autodesk. The talk briefly described MERL's research areas, and focused on Dr. Chakrabarty's work at MERL (with collaborators from the CD and DA group) on the use of supervised learning for verification of control systems with simulators/neural nets in the loop, and on constraint-enforcing reinforcement learning. Other speakers at the event included researchers from various academic and industrial research facilities including U Toronto, UW-Seattle, Carnegie Mellon U, the Vector Institute, and the Montreal Institute for Learning Algorithms.
  •  
  •  AWARD   MERL Researchers Won IEEE ICC Best Paper Award
    Date: May 22, 2019
    Awarded to: Siriramya Bhamidipati, Kyeong Jin Kim, Hongbo Sun, Philip Orlik
    MERL Contacts: Kyeong Jin (K.J.) Kim; Hongbo Sun
    Research Areas: Artificial Intelligence, Communications, Machine Learning, Signal Processing, Information Security
    Brief
    • MERL researchers, Kyeong Jin Kim, Hongbo Sun, Philip Orlik, along with lead author and former MERL intern Siriramya Bhamidipati were awarded the Smart Grid Symposium Best Paper Award at this year's International Conference on Communications (ICC) held in Shanghai, China. There paper titled "GPS Spoofing Detection and Mitigation in PMUs Using Distributed Multiple Directional Antennas," described a technique to rapidly detect and mitigate GPS timing attacks/errors via hardware (antennas) and signal processing (Kalman Filtering).
  •  
  •  AWARD   MERL researcher wins Best Visualization Note Award at PacificVis2019 Conference
    Date: April 23, 2019
    Awarded to: Teng-yok Lee
    Research Areas: Artificial Intelligence, Computer Vision, Data Analytics, Machine Learning
    Brief
    • MERL researcher Teng-yok Lee has won the Best Visualization Note Award at the PacificVis 2019 conference held in Bangkok Thailand, from April 23-26, 2019. The paper entitled "Space-Time Slicing: Visualizing Object Detector Performance in Driving Video Sequences" presents a visualization method called Space-Time Slicing to assist a human developer in the development of object detectors for driving applications without requiring labeled data. Space-Time Slicing reveals patterns in the detection data that can suggest the presence of false positives and false negatives.
  •