News & Events

89 were found.




  •  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.
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  •  TALK   Universal Differential Equations for Scientific Machine Learning
    Date & Time: Thursday, May 7, 2020; 12:00 PM
    Speaker: Christopher Rackauckas, MIT
    MERL Host: Christopher Laughman
    Research Areas: Machine Learning, Multi-Physical Modeling, Optimization
    Brief
    • In the context of science, the well-known adage "a picture is worth a thousand words" might well be "a model is worth a thousand datasets." Scientific models, such as Newtonian physics or biological gene regulatory networks, are human-driven simplifications of complex phenomena that serve as surrogates for the countless experiments that validated the models. Recently, machine learning has been able to overcome the inaccuracies of approximate modeling by directly learning the entire set of nonlinear interactions from data. However, without any predetermined structure from the scientific basis behind the problem, machine learning approaches are flexible but data-expensive, requiring large databases of homogeneous labeled training data. A central challenge is reco nciling data that is at odds with simplified models without requiring "big data". In this talk we discuss a new methodology, universal differential equations (UDEs), which augment scientific models with machine-learnable structures for scientifically-based learning. We show how UDEs can be utilized to discover previously unknown governing equations, accurately extrapolate beyond the original data, and accelerate model simulation, all in a time and data-efficient manner. This advance is coupled with open-source software that allows for training UDEs which incorporate physical constraints, delayed interactions, implicitly-defined events, and intrinsic stochasticity in the model. Our examples show how a diverse set of computationally-difficult modeling issues across scientific disciplines, from automatically discovering biological mechanisms to accelerating climate simulations by 15,000x, can be handled by training UDEs.
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  •  NEWS   Stefano Di Cairano Appointed IPC Vice-Chair for the 7th IFAC Symposium on NMPC (2021)
    Date: July 7, 2021 - July 14, 2021
    Where: Bratislava, Slovakia
    MERL Contact: Stefano Di Cairano
    Research Areas: Control, Machine Learning, Optimization
    Brief
    • MERL researcher Stefano Di Cairano has been appointed as Vice-Chair for Industry of the International Program Committee of the 7th IFAC Symposium on Nonlinear Model Predictive Control, which will be held in Bratislava, Slovakia, in July 2021.
      IFAC NMPC is the main symposium focused on model predictive control, theory, methods and applications, includes contributions on control, optimization, and machine learning research, and is held every 3 years.
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  •  NEWS   MERL presenting 13 papers and an industry talk at ICASSP 2020
    Date: May 4, 2020 - May 8, 2020
    Where: Virtual Barcelona
    MERL Contacts: Karl Berntorp; Petros Boufounos; Chiori Hori; Takaaki Hori; Toshiaki Koike-Akino; Jonathan Le Roux; Dehong Liu; Yanting Ma; Hassan Mansour; Niko Moritz; Philip Orlik; Anthony Vetro; Pu (Perry) Wang; Gordon Wichern; Siheng Chen
    Research Areas: Computational Sensing, Computer Vision, Machine Learning, Signal Processing, Speech & Audio
    Brief
    • MERL researchers are presenting 13 papers at the IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP), which is being held virtually from May 4-8, 2020. Petros Boufounos is also presenting a talk on the Computational Sensing Revolution in Array Processing (video) in ICASSP’s Industry Track, and Siheng Chen is co-organizing and chairing a special session on a Signal-Processing View of Graph Neural Networks.

      Topics to be presented include recent advances in speech recognition, audio processing, scene understanding, computational sensing, array processing, and parameter estimation. Videos for all talks are available on MERL's YouTube channel, with corresponding links in the references below.

      This year again, MERL is a sponsor of the conference and will be participating in the Student Job Fair; please join us to learn about our internship program and career opportunities.

      ICASSP is the flagship conference of the IEEE Signal Processing Society, and the world's largest and most comprehensive technical conference focused on the research advances and latest technological development in signal and information processing. The event attracts more than 2000 participants each year. Originally planned to be held in Barcelona, Spain, ICASSP has moved to a fully virtual setting due to the COVID-19 crisis, with free registration for participants not covering a paper.
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  •  NEWS   MERL Scientists Presented 5 Papers Including 2 Invited Talks at Optical Fiber Communications Conference (OFC) 2020
    Date: March 8, 2020 - March 13, 2020
    MERL Contacts: Devesh Jha; Toshiaki Koike-Akino; Keisuke Kojima; David Millar; Kieran Parsons; Ye Wang
    Research Areas: Communications, Electronic and Photonic Devices, Machine Learning, Signal Processing
    Brief
    • Due to COVID-19, MERL Optical Team scientists remotely presented 5 papers including 2 invited talks at the Optical Fiber Communications Conference (OFC) 2020, that was held in San Diego from March 8-13, 2020. Topics presented include recent advances in quantum signal processing, channel coding design, nano-optic power splitter, and deep learning-based integrated photonics. In addition, Dr. Kojima gave an invited workshop talk on deep learning-based nano-photonic device optimization.

      OFC is the largest global conference and exhibition for optical communications and networking professionals. The program is comprehensive from research to marketplace, from components to systems and networks and from technical sessions to the exhibition. For over 40 years, OFC has drawn attendees from all corners of the globe to meet and greet, teach and learn, make connections and move the industry forward. The five-day technical conference features peer reviewed presentations and more than 180 invited speakers, the thought leaders in the industry presenting the highlights of emerging technologies. Additional technical programming throughout the week includes special symposia, special sessions, in-depth tutorials, workshops, panels and the thought-provoking rump session.
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  •  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.
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  •  NEWS   MERL researchers presented 8 papers at Conference on Decision and Control (CDC)
    Date: December 11, 2019 - December 13, 2019
    Where: Nice, France
    MERL Contacts: Mouhacine Benosman; Karl Berntorp; Scott Bortoff; Ankush Chakrabarty; Claus Danielson; Stefano Di Cairano; Uroš Kalabić; Jing Zhang
    Research Areas: Control, Machine Learning, Optimization
    Brief
    • At the Conference on Decision and Control, MERL presented 8 papers on subjects including estimation for thermal-fluid models and transportation networks, analysis of HVAC systems, extremum seeking for multi-agent systems, reinforcement learning for vehicle platoons, and learning with applications to autonomous vehicles.
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  •  NEWS   MERL Scientists Presenting 11 Papers at IEEE Global Communications Conference (GLOBECOM) 2019
    Date: December 9, 2019 - December 13, 2019
    Where: Waikoloa, Hawaii, USA
    MERL Contacts: Jianlin Guo; Kyeong Jin (K.J.) Kim; Toshiaki Koike-Akino; Rui Ma; Philip Orlik; Pu (Perry) Wang
    Research Areas: Communications, Computer Vision, Machine Learning, Signal Processing, Information Security
    Brief
    • MERL Signal Processing scientists and collaborators will be presenting 11 papers at the IEEE Global Communications Conference (GLOBECOM) 2019, which is being held in Waikoloa, Hawaii from December 9-13, 2019. Topics to be presented include recent advances in power amplifier, MIMO algorithms, WiFi sensing, video casting, visible light communications, user authentication, vehicular communications, secrecy, and relay systems, including sophisticated machine learning applications. A number of these papers are a result of successful collaboration between MERL and world-leading Universities including: Osaka University, University of New South Wales, Oxford University, Princeton University, South China University of Technology, Massachusetts Institute of Technology and Aalborg University.

      GLOBECOM is one of the IEEE Communications Society’s two flagship conferences dedicated to driving innovation in nearly every aspect of communications. Each year, more than 3000 scientific researchers and their management submit proposals for program sessions to be held at the annual conference. Themed “Revolutionizing Communications,” GLOBECOM2019 will feature a comprehensive high-quality technical program including 13 symposia and a variety of tutorials and workshops to share visions and ideas, obtain updates on latest technologies and expand professional and social networking.
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  •  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.
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  •  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.
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  •  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.
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  •  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.
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  •  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.
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  •  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.
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  •  NEWS   MERL researchers presented 8 papers at American Control Conference
    Date: July 10, 2019 - July 12, 2019
    Where: Philadelphia
    MERL Contacts: Mouhacine Benosman; Karl Berntorp; Ankush Chakrabarty; Claus Danielson; Stefano Di Cairano; Devesh Jha; Rien Quirynen; Yebin Wang; Avishai Weiss
    Research Areas: Control, Machine Learning, Optimization
    Brief
    • At the American Control Conference, MERL presented 8 papers on subjects including model predictive control applications, estimation and motion planning for vehicles, modular control architectures, and adaptation and learning.
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  •  TALK   Perspectives on Integer Programming in Sparse Optimization
    Date & Time: Tuesday, July 16, 2019; 12:00 PM
    Speaker: Prof. Jeff Linderoth, University of Wisconsin-Madison
    MERL Host: Arvind Raghunathan
    Research Areas: Machine Learning, Optimization
    Brief
    • Algorithms to solve mixed integer linear programs have made incredible progress in the past 20 years. Key to these advances has been a mathematical analysis of the structure of the set of feasible solutions. We argue that a similar analysis is required in the case of mixed integer quadratic programs, like those that arise in sparse optimization in machine learning. One such analysis leads to the so-called perspective relaxation, which significantly improves solution performance on separable instances. Extensions of the perspective reformulation can lead to algorithms that are equivalent to some of the most popular, modern, sparsity-inducing non-convex regularizations in variable selection. Based on joint work with Hongbo Dong (Washington State Univ. ), Oktay Gunluk (IBM), and Kun Chen (Univ. Connecticut)
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  •  NEWS   MERL researchers presented more than 8 papers in European Control Conference, ECC 2019
    Date: June 25, 2019 - June 28, 2019
    Where: Naples, Italy
    MERL Contacts: Karl Berntorp; Scott Bortoff; Ankush Chakrabarty; Claus Danielson; Stefano Di Cairano; Devesh Jha; Christopher Laughman; Daniel Nikovski; Rien Quirynen; Diego Romeres; William Yerazunis
    Research Areas: Control, Machine Learning, Optimization
    Brief
    • The European Control Conference is the premier control conference in Europe. This year MERL was well represented with papers on control for HVAC, machine learning for estimation and control, robot assembly, and optimization methods for control.
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  •  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)
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  •  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.
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  •  NEWS   MERL presenting 16 papers at ICASSP 2019
    Date: May 12, 2019 - May 17, 2019
    Where: Brighton, UK
    MERL Contacts: Petros Boufounos; Anoop Cherian; Chiori Hori; Takaaki Hori; Toshiaki Koike-Akino; Jonathan Le Roux; Dehong Liu; Hassan Mansour; Tim Marks; Niko Moritz; Philip Orlik; Anthony Vetro; Pu (Perry) Wang; Gordon Wichern
    Research Areas: Computational Sensing, Computer Vision, Machine Learning, Signal Processing, Speech & Audio
    Brief
    • MERL researchers will be presenting 16 papers at the IEEE International Conference on Acoustics, Speech & Signal Processing (ICASSP), which is being held in Brighton, UK from May 12-17, 2019. Topics to be presented include recent advances in speech recognition, audio processing, scene understanding, computational sensing, and parameter estimation. MERL is also a sponsor of the conference and will be participating in the student career luncheon; please join us at the lunch to learn about our internship program and career opportunities.

      ICASSP is the flagship conference of the IEEE Signal Processing Society, and the world's largest and most comprehensive technical conference focused on the research advances and latest technological development in signal and information processing. The event attracts more than 2000 participants each year.
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  •  NEWS   Deep Learning-Based Photonic Circuit Design in Scientific Reports
    Date: February 4, 2019
    Where: Scientific Reports, open-access journal from Nature Research
    MERL Contacts: Devesh Jha; Toshiaki Koike-Akino; Keisuke Kojima; Chungwei Lin; Kieran Parsons; Bingnan Wang
    Research Areas: Artificial Intelligence, Electronic and Photonic Devices, Machine Learning
    Brief
    • MERL researchers developed a novel design method enhanced by modern deep learning techniques for optimizing photonic integrated circuits (PIC). The developed technique employs residual deep neural networks (DNNs) to understand physics underlaying complicated lightwave propagations through nano-structured photonic devices. It was demonstrated that the trained DNN achieves excellent prediction to design power splitting nanostructures having various target power ratios. The work was published in Scientific Reports, which is an online open access journal from Nature Research, having high-impact articles in the research community.
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  •  NEWS   MERL presenting 4 papers at OFC, including an invited talk
    Date: March 3, 2019 - March 7, 2019
    Where: San Diego, CA
    MERL Contacts: Devesh Jha; Toshiaki Koike-Akino; Keisuke Kojima; Chungwei Lin; David Millar; Kieran Parsons; Bingnan Wang; Ye Wang
    Research Areas: Communications, Machine Learning, Optimization, Signal Processing
    Brief
    • MERL researchers are presenting 4 papers at the OSA Optical Fiber Conference (OFC), which is being held in San Diego from March 3-7, 2019. Topics to be presented include recent advances in nonbinary polar codes, joint polar-coded shaping, and deep learning-based photonics circuit design. Additionally, recent work on multiset-partition distribution matching is presented as an invited talk.

      OFC is the flagship conference of the OSA, and the world's most comprehensive technical conference focused on the research advances and latest technological development in optics and photonics. The event attracts more than 10000 participants each year.
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  •  NEWS   Mitsubishi Electric Corporation and MERL Press Release Describes Future Digitally Controlled Power Amplifier
    Date: January 10, 2019
    Where: Tokyo, Japan
    MERL Contacts: Mouhacine Benosman; Rui Ma; Philip Orlik; Koon Hoo Teo
    Research Areas: Communications, Electronic and Photonic Devices, Machine Learning, Signal Processing
    Brief
    • Mitsubishi Electric Corporation announced today its development of the world's first ultra-wideband digitally controlled gallium nitride (GaN) amplifier, which is compatible with a world-leading range of sub-6GHz bands focused on fifth-generation (5G) mobile communication systems. With a power efficiency rating of above 40%, the amplifier is expected to contribute to large-capacity communication and reduce the power consumption of mobile base stations.

      MERL and Mitsubishi Electric researchers collaborated to develop digital control methods for amplifiers achieving high-efficiency of 40% and above, with 110% of the fractional bandwidth over frequency range 1.4-4.8 GHz. The digital control signals are designed using a learning-function based on Maisart®.

      Please see the link below for the full Mitsubishi Electric press release text.
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  •  AWARD   R&D100 award for Deep Learning-based Water Detector
    Date: November 16, 2018
    Awarded to: Ziming Zhang, Alan Sullivan, Hideaki Maehara, Kenji Taira, Kazuo Sugimoto
    MERL Contact: Alan Sullivan
    Research Areas: Artificial Intelligence, Computer Vision, Machine Learning
    Brief
    • Researchers and developers from MERL, Mitsubishi Electric and Mitsubishi Electric Engineering (MEE) have been recognized with an R&D100 award for the development of a deep learning-based water detector. Automatic detection of water levels in rivers and streams is critical for early warning of flash flooding. Existing systems require a height gauge be placed in the river or stream, something that is costly and sometimes impossible. The new deep learning-based water detector uses only images from a video camera along with 3D measurements of the river valley to determine water levels and warn of potential flooding. The system is robust to lighting and weather conditions working well during the night as well as during fog or rain. Deep learning is a relatively new technique that uses neural networks and AI that are trained from real data to perform human-level recognition tasks. This work is powered by Mitsubishi Electric's Maisart AI technology.
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  •  EVENT   MERL is a Proud Sponsor of the Grace Hopper Celebration 2018!
    Date: Wednesday, September 26, 2018 - Friday, September 28, 2018
    MERL Contacts: Chiori Hori; Elizabeth Phillips
    Location: Houston, Texas
    Research Areas: Artificial Intelligence, Computer Vision, Machine Learning
    Brief
    • "MERL, in partnership with Mitsubishi Electric was a Gold Sponsor of the Grace Hopper Celebration 2018 (GHC18) held in Houston, TX on September 26-28th. Presented by AnitaB.org and the Association for Computing Machinery, this is world's largest gathering of women technologists. Chiori Hori and Elizabeth Phillips from MERL, and Yoshiyuki Umei, Jared Baker and Lien Randle from MEUS, proudly represented Mitsubishi Electric at the recruiting expo, that drew over 20,000 female technologists this year.
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