- 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, Computer Vision
- 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.
- 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
- 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.
- Date: July 9, 2019
MERL Contacts: Toshiaki Koike-Akino; Keisuke Kojima; David Millar; Kieran Parsons; Ye Wang
Research Areas: Communications, Signal Processing
- MERL researchers presented an invited talk at OptElectronics and Communications Conference (OECC), held at Fukuoka, Japan. The speech focused on recent advancement of error correction coding based on polar codes and suited for hardware implementation in high-speed optical communications.
- Date: July 10, 2019 - July 12, 2019
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, Robotics, Applied Physics, Dynamical Systems, Computational Sensing
- 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.
- 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
- 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)
- 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, Artificial Intelligence, Data Analytics, Robotics, Multi-Physical Modeling
- 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.
- Date: July 4, 2019
Where: University of Edinburgh
MERL Contact: Arvind Raghunathan
Research Area: Optimization
- Arvind Raghunathan, of MERL's Data Analytics group, will deliver a keynote titled "Embedding Perfect Structures in Process Systems" in the School of Engineering at University of Edinburgh. Abstract of the talk can be found in the link below.
- Date: July 2, 2019
Where: Imperial College London
MERL Contact: Arvind Raghunathan
Research Area: Optimization
- Arvind Raghunathan, of MERL's Data Analytics group, will deliver a seminar titled "Chordal Completions – Semidefinite Programming and Minimum Completions" in the Computational Optimisation Group at Imperial College London. Abstract of the talk can be found in the link below.
- Date & Time: Tuesday, June 18, 2019; 12:00PM
Speaker: Beverly Shultz
MERL Contacts: Marissa Deegan; Elizabeth Phillips
Location: 201 Broadway, Cambridge, MA
- MERL hosted its annual "Women In Science Luncheon" to celebrate and inspire the Lab's team of female researchers, PhD student interns and members of the HQ staff. Beverly Shultz, author of "Skip the Typing Test, I’ll Manage the Software-A Woman’s Pioneering Journey in High Tech” joined the event to share her insights as a successful female engineer, who brought passion and technology business acumen to the male-dominated computer revolution.
Beverly was a former Vice President of Engineering at Mitsubishi Electric of America and responsible to produce several versions of an early volume rendering product. She was the first female recipient of the MELCO’s President’s Award for Technology, for this work.
- Date: June 10, 2019 - June 14, 2019
MERL Contact: Stefano Di Cairano
Research Areas: Control, Dynamical Systems, Optimization, Signal Processing
- MERL researcher Stefano Di Cairano and Prof. Ilya Kolmanovsky, Dept. Aerospace Engineering, the University of Michigan, were invited to teach a class on "Predictive and Optimization Based Control for Automotive and Aerospace Application" at the 2019 International Graduate School in Control, of the European Embedded Control Institute (EECI). Every year EECI invites world renown experts to teach 21-hours class modules, mostly for PhD students but also for professionals, on selected control subjects. Stefano and Ilya's class was attended by 30 "students" from both academia and industry, from all around the world, interested in automotive and aerospace control. The module described the fundamentals of modeling and control design in automotive and aerospace through lectures, real world examples and exercises, and placed particular emphasis on techniques such as MPC, reference governors, and optimal control.
- Date: June 12, 2019
Where: Physical Chemistry Chemical Physics – Published 22 Feb 2019
MERL Contact: Chungwei Lin
Research Areas: Applied Physics, Multi-Physical Modeling
- The journal "Physical Chemistry Chemical Physics (PCCP)" selects a few well-received articles highlighted as HOT by the handling editor or referees. The following paper "Band Alignment in Quantum Wells from Automatically Tuned DFT+U" with MERL authors Grigory Kolesov, Chungwei Lin, Andrew Knyazev, Keisuke Kojima, Joseph Katz has been selected as a 2019 HOT Physical Chemistry Chemical Physics article, and is made free to access until the end of July 2019. This paper provides a semi-empirical methodology to compute the lattice and electronic structures of systems composed of 400+ atoms. The efficiency of this method allows for realistic simulations of interfaces between semiconductors, which is nearly impossible using the existing methods due to the extremely large degrees of freedom involved. The formalism is tested against a few established band alignments and then applied to determine the band gaps of quantum wells; the agreement is within the experimental uncertainty.
- Date & Time: July 29, 2019; 10 AM
Where: US National Congress on Computational Mechanics 2019, in Austin Texas
MERL Contact: Mouhacine Benosman
Research Areas: Control, Data Analytics, Dynamical Systems
- MERL researcher Mouhacine Benosman will present his work on 'Learning-based Robust Stabilization for Reduced-Order Models of 3D Boussinesq Equations' as a keynote speaker at the mini-symposium 'Data assimilation in Model Order Techniques for Computational Mechanics', during the next US National Congress on Computational Mechanics 2019, in Austin Texas.
- 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
- 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)
- Date: April 15, 2019
MERL Contact: Stefano Di Cairano
Research Areas: Control, Dynamical Systems, Optimization
- Stefano Di Cairano, senior team leader and distinguished research scientist in the Control and Dynamical Systems group, was interviewed in the April 2019 issue of IEEE Control Systems Magazine. Stefano described himself, promising opportunities in the control field, and how his passion for control research fits well into the industrial research laboratory setting at MERL. It is very good reading for any young researcher considering possible career trajectories.
- Date: January 2, 2019
Awarded to: Siheng Chen
MERL Contact: Siheng Chen
Research Area: Signal Processing
- MERL researcher, Siheng Chen, has won an IEEE Young Author Best Paper award for his paper entitled "Discrete Signal Processing on Graphs: Sampling Theory". This paper, published in the December 2015 issue of IEEE Transactions on Signal Processing, proposes a sampling theory for signals that are supported on either directed or undirected graphs. The theory follows the same paradigm as classical sampling theory and shows that perfect recovery is possible for graph signals bandlimited under the graph Fourier transform. The award honors the authors of an especially meritorious paper dealing with a subject related to IEEE's technical scope and appearing in one if its journals within a three year window of eligibility.
- Date: April 23, 2019
Awarded to: Teng-yok Lee
MERL Contact: Teng-Yok Lee
Research Areas: Artificial Intelligence, Computer Vision, Data Analytics, Machine Learning
- 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.
- Date: April 28, 2019
Where: 3rd IAVSD Workshop on Dynamics of Road Vehicles: Connected and Automated Vehicles
MERL Contact: Stefano Di Cairano
Research Areas: Control, Optimization, Robotics, Signal Processing, Dynamical Systems
- Stefano Di Cairano, Distinguished Scientist and Senior Team Leader in the Control and Dynamical Systems Group, will give an invited talk entitled: "Modularity, integration and synergy in architectures for autonomous driving" that covers recent work in the lab concerning building a modular, robust control framework for autonomous driving.
- Date: April 4, 2019
Where: Nashua Public Library, Nashua, NH
MERL Contact: Petros Boufounos
Research Areas: Computational Sensing, Signal Processing, Computer Vision
- MERL's Petros Boufounos gave a lecture for the IEEE-NH ComSig chapter at the Nashua Public Library as part of the IEEE Signal Processing Society Distinguished Lecturer series.
Title: "An Inverse Problem Framework for Array Processing Systems."
Abstract: Array-based sensing systems, such as ultrasonic, radar and optical (LIDAR) are becoming increasingly important in a variety of applications, including robotics, autonomous driving, medical imaging, and virtual reality, among others. This has led to continuous improvements in sensing hardware, but also to increasing demand for theory and methods to inform the system design and improve the processing. In this talk we will discuss how recent advances in formulating and solving inverse problems, such as compressed sensing, blind deconvolution, and sparse signal modeling can be applied to significantly reduce the cost and improve the capabilities of array-based and multichannel sensing systems. We show that these systems share a common mathematical framework, which allows us to describe both the acquisition hardware and the scene being acquired. Under this framework we can exploit prior knowledge on the scene, the system, and a variety of errors that might occur, allowing for significant improvements in the reconstruction accuracy. Furthermore, we can consider the design of the system itself in the context of the inverse problem, leading to designs that are more efficient, more accurate, or less expensive, depending on the application. In the talk we will explore applications of this model to LIDAR and depth sensing, radar and distributed radar, and ultrasonic sensing. In the context of these applications, we will describe how different models can lead to improved specifications in ultrasonic systems, robustness to position and timing errors in distributed array systems, and cost reduction and new capabilities in LIDAR systems.
- 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; Milutin Pajovic; Anthony Vetro; Pu (Perry) Wang; Gordon Wichern
Research Areas: Computational Sensing, Computer Vision, Machine Learning, Signal Processing, Speech & Audio, Artificial Intelligence, Communications
- 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.
- 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, Communications
- 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.