- Date & Time: Tuesday, March 11, 2025; 12:00 PM
Speaker: Dick den Hertog, University of Amsterdam
MERL Host: Arvind Raghunathan
Research Areas: Data Analytics, Optimization
Abstract 
Increasing ocean plastic pollution is irreversibly harming ecosystems and human economic activities. We partner with a nonprofit organization and use optimization to help clean up oceans from plastic faster. Specifically, we optimize the route of their plastic collection system in the ocean to maximize the quantity of plastic collected over time. We formulate the problem as a longest path problem in a well-structured graph. However, because collection directly impacts future plastic density, the corresponding edge lengths are nonlinear polynomials. After analyzing the structural properties of the edge lengths, we propose a search-and-bound method, which leverages a relaxation of the problem solvable via dynamic programming and clustering, to efficiently find high-quality solutions (within 6% optimal in practice) and develop a tailored branch-and-bound strategy to solve it to provable optimality. On one year of ocean data, our optimization-based routing approach increases the quantity of plastic collected by more than 60% compared with the current routing strategy, hence speeding up the progress toward plastic-free oceans.
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- Date & Time: Wednesday, November 20, 2024; 1:00 PM
Speaker: Di Shi, New Mexico State University
MERL Host: Hongbo Sun
Research Areas: Artificial Intelligence, Data Analytics, Optimization
Abstract 
This presentation delves into the challenges and advancements in optimizing power system operations through Grid Mind, an innovative, data-driven framework designed to enhance the integration of renewable energy sources. Utilizing advanced learning algorithms, Grid Mind excels in strategic resource allocation and control, significantly improving efficiency and reliability in power systems with high renewable energy penetration. The transformative potential of this AI-assisted technology is highlighted through real-world applications, demonstrating its effectiveness in addressing the complexities of modern power systems. In addition, critical safety considerations and practical deployment challenges are explored, emphasizing the need for robust, secure, and adaptable solutions. This talk also discusses the capabilities of Grid Mind as a distributed, learning-based system optimized for edge devices, marking a significant advancement toward sustainable, safe, and efficient power system operations in an era dominated by renewable energy.
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- Date & Time: Wednesday, September 18, 2024; 1:00 PM
Speaker: Tom Griffiths, Princeton University
Research Areas: Artificial Intelligence, Data Analytics, Machine Learning, Human-Computer Interaction
Abstract 
Large language models have been found to have surprising capabilities, even what have been called “sparks of artificial general intelligence.” However, understanding these models involves some significant challenges: their internal structure is extremely complicated, their training data is often opaque, and getting access to the underlying mechanisms is becoming increasingly difficult. As a consequence, researchers often have to resort to studying these systems based on their behavior. This situation is, of course, one that cognitive scientists are very familiar with — human brains are complicated systems trained on opaque data and typically difficult to study mechanistically. In this talk I will summarize some of the tools of cognitive science that are useful for understanding the behavior of large language models. Specifically, I will talk about how thinking about different levels of analysis (and Bayesian inference) can help us understand some behaviors that don’t seem particularly intelligent, how tasks like similarity judgment can be used to probe internal representations, how axiom violations can reveal interesting mechanisms, and how associations can reveal biases in systems that have been trained to be unbiased.
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- Date & Time: Wednesday, March 1, 2023; 1:00 PM
Speaker: Shaowu Pan, Rensselaer Polytechnic Institute
MERL Host: Saviz Mowlavi
Research Areas: Computational Sensing, Data Analytics, Machine Learning
Abstract 
High-dimensional spatio-temporal dynamics can often be encoded in a low-dimensional subspace. Engineering applications for modeling, characterization, design, and control of such large-scale systems often rely on dimensionality reduction to make solutions computationally tractable in real-time. Common existing paradigms for dimensionality reduction include linear methods, such as the singular value decomposition (SVD), and nonlinear methods, such as variants of convolutional autoencoders (CAE). However, these encoding techniques lack the ability to efficiently represent the complexity associated with spatio-temporal data, which often requires variable geometry, non-uniform grid resolution, adaptive meshing, and/or parametric dependencies. To resolve these practical engineering challenges, we propose a general framework called Neural Implicit Flow (NIF) that enables a mesh-agnostic, low-rank representation of large-scale, parametric, spatial-temporal data. NIF consists of two modified multilayer perceptrons (MLPs): (i) ShapeNet, which isolates and represents the spatial complexity, and (ii) ParameterNet, which accounts for any other input complexity, including parametric dependencies, time, and sensor measurements. We demonstrate the utility of NIF for parametric surrogate modeling, enabling the interpretable representation and compression of complex spatio-temporal dynamics, efficient many-spatial-query tasks, and improved generalization performance for sparse reconstruction.
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- Date & Time: Monday, December 12, 2022; 1:00pm-5:30pm ET
Location: Mitsubishi Electric Research Laboratories (MERL)/Virtual
Research Areas: Applied Physics, Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Electric Systems, Electronic and Photonic Devices, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & Audio, Digital Video
Brief - Join MERL's virtual open house on December 12th, 2022! Featuring a keynote, live sessions, research area booths, and opportunities to interact with our research team. Discover who we are and what we do, and learn about internship and employment opportunities.
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- Date & Time: Thursday, December 9, 2021; 1:00pm - 5:30pm EST
Location: Virtual Event
Speaker: Prof. Melanie Zeilinger, ETH
Research Areas: Applied Physics, Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Electric Systems, Electronic and Photonic Devices, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & Audio, Digital Video, Human-Computer Interaction, Information Security
Brief - MERL is excited to announce the second keynote speaker for our Virtual Open House 2021:
Prof. Melanie Zeilinger from ETH .
Our virtual open house will take place on December 9, 2021, 1:00pm - 5:30pm (EST).
Join us to learn more about who we are, what we do, and discuss our internship and employment opportunities. Prof. Zeilinger's talk is scheduled for 3:15pm - 3:45pm (EST).
Registration: https://mailchi.mp/merl/merlvoh2021
Keynote Title: Control Meets Learning - On Performance, Safety and User Interaction
Abstract: With increasing sensing and communication capabilities, physical systems today are becoming one of the largest generators of data, making learning a central component of autonomous control systems. While this paradigm shift offers tremendous opportunities to address new levels of system complexity, variability and user interaction, it also raises fundamental questions of learning in a closed-loop dynamical control system. In this talk, I will present some of our recent results showing how even safety-critical systems can leverage the potential of data. I will first briefly present concepts for using learning for automatic controller design and for a new safety framework that can equip any learning-based controller with safety guarantees. The second part will then discuss how expert and user information can be utilized to optimize system performance, where I will particularly highlight an approach developed together with MERL for personalizing the motion planning in autonomous driving to the individual driving style of a passenger.
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- Date & Time: Thursday, December 9, 2021; 1:00pm - 5:30pm EST
Location: Virtual Event
Speaker: Prof. Ashok Veeraraghavan, Rice University
Research Areas: Applied Physics, Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Electric Systems, Electronic and Photonic Devices, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & Audio, Digital Video, Human-Computer Interaction, Information Security
Brief - MERL is excited to announce the first keynote speaker for our Virtual Open House 2021:
Prof. Ashok Veeraraghavan from Rice University.
Our virtual open house will take place on December 9, 2021, 1:00pm - 5:30pm (EST).
Join us to learn more about who we are, what we do, and discuss our internship and employment opportunities. Prof. Veeraraghavan's talk is scheduled for 1:15pm - 1:45pm (EST).
Registration: https://mailchi.mp/merl/merlvoh2021
Keynote Title: Computational Imaging: Beyond the limits imposed by lenses.
Abstract: The lens has long been a central element of cameras, since its early use in the mid-nineteenth century by Niepce, Talbot, and Daguerre. The role of the lens, from the Daguerrotype to modern digital cameras, is to refract light to achieve a one-to-one mapping between a point in the scene and a point on the sensor. This effect enables the sensor to compute a particular two-dimensional (2D) integral of the incident 4D light-field. We propose a radical departure from this practice and the many limitations it imposes. In the talk we focus on two inter-related research projects that attempt to go beyond lens-based imaging.
First, we discuss our lab’s recent efforts to build flat, extremely thin imaging devices by replacing the lens in a conventional camera with an amplitude mask and computational reconstruction algorithms. These lensless cameras, called FlatCams can be less than a millimeter in thickness and enable applications where size, weight, thickness or cost are the driving factors. Second, we discuss high-resolution, long-distance imaging using Fourier Ptychography, where the need for a large aperture aberration corrected lens is replaced by a camera array and associated phase retrieval algorithms resulting again in order of magnitude reductions in size, weight and cost. Finally, I will spend a few minutes discussing how the wholistic computational imaging approach can be used to create ultra-high-resolution wavefront sensors.
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- Date & Time: Thursday, December 9, 2021; 100pm-5:30pm (EST)
Location: Virtual Event
Research Areas: Applied Physics, Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Electric Systems, Electronic and Photonic Devices, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & Audio, Digital Video, Human-Computer Interaction, Information Security
Brief - Mitsubishi Electric Research Laboratories cordially invites you to join our Virtual Open House, on December 9, 2021, 1:00pm - 5:30pm (EST).
The event will feature keynotes, live sessions, research area booths, and time for open interactions with our researchers. Join us to learn more about who we are, what we do, and discuss our internship and employment opportunities.
Registration: https://mailchi.mp/merl/merlvoh2021
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- Date & Time: Tuesday, September 14, 2021; 1:00 PM EST
Speaker: Prof. David Bergman, University of Connecticut
MERL Host: Arvind Raghunathan
Research Areas: Data Analytics, Machine Learning, Optimization
Abstract 
The integration of machine learning and optimization opens the door to new modeling paradigms that have already proven successful across a broad range of industries. Sports betting is a particularly exciting application area, where recent advances in both analytics and optimization can provide a lucrative edge. In this talk we will discuss three algorithmic sports betting games where combinations of machine learning and optimization have netted me significant winnings.
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- Date & Time: Wednesday, December 9, 2020; 1:00-5:00PM EST
Location: Virtual
MERL Contacts: Elizabeth Phillips; Anthony Vetro
Research Areas: Applied Physics, Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Electric Systems, Electronic and Photonic Devices, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & Audio
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- Date & Time: Thursday, November 29, 2018; 4-6pm
Location: 201 Broadway, 8th floor, Cambridge, MA
MERL Contacts: Elizabeth Phillips; Anthony Vetro
Research Areas: Applied Physics, Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Electric Systems, Electronic and Photonic Devices, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & Audio
Brief - Snacks, demos, science: On Thursday 11/29, Mitsubishi Electric Research Labs (MERL) will host an open house for graduate+ students interested in internships, post-docs, and research scientist positions. The event will be held from 4-6pm and will feature demos & short presentations in our main areas of research including artificial intelligence, robotics, computer vision, speech processing, optimization, machine learning, data analytics, signal processing, communications, sensing, control and dynamical systems, as well as multi-physyical modeling and electronic devices. MERL is a high impact publication-oriented research lab with very extensive internship and university collaboration programs. Most internships lead to publication; many of our interns and staff have gone on to notable careers at MERL and in academia. Come mix with our researchers, see our state of the art technologies, and learn about our research opportunities. Dress code: casual, with resumes.
Pre-registration for the event is strongly encouraged:
merlopenhouse.eventbrite.com
Current internship and employment openings:
www.merl.com/internship/openings
www.merl.com/employment/employment
Information about working at MERL:
www.merl.com/employment.
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- Date & Time: Friday, February 2, 2018; 12:00
Speaker: Dr. David Kaeli, Northeastern University
MERL Host: Abraham Goldsmith
Research Areas: Control, Optimization, Machine Learning, Speech & Audio
Abstract 
GPU computing is alive and well! The GPU has allowed researchers to overcome a number of computational barriers in important problem domains. But still, there remain challenges to use a GPU to target more general purpose applications. GPUs achieve impressive speedups when compared to CPUs, since GPUs have a large number of compute cores and high memory bandwidth. Recent GPU performance is approaching 10 teraflops of single precision performance on a single device. In this talk we will discuss current trends with GPUs, including some advanced features that allow them exploit multi-context grains of parallelism. Further, we consider how GPUs can be treated as cloud-based resources, enabling a GPU-enabled server to deliver HPC cloud services by leveraging virtualization and collaborative filtering. Finally, we argue for for new heterogeneous workloads and discuss the role of the Heterogeneous Systems Architecture (HSA), a standard that further supports integration of the CPU and GPU into a common framework. We present a new class of benchmarks specifically tailored to evaluate the benefits of features supported in the new HSA programming model.
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- Date & Time: Thursday, November 30, 2017; 4-6pm
Location: 201 Broadway, 8th floor, Cambridge, MA
MERL Contacts: Elizabeth Phillips; Anthony Vetro Brief - Snacks, demos, science: On Thursday 11/30, Mitsubishi Electric Research Labs (MERL) will host an open house for graduate+ students interested in internships, post-docs, and research scientist positions. The event will be held from 4-6pm and will feature demos & short presentations in our main areas of research: algorithms, multimedia, electronics, communications, computer vision, speech processing, optimization, machine learning, data analytics, mechatronics, dynamics, control, and robotics. MERL is a high impact publication-oriented research lab with very extensive internship and university collaboration programs. Most internships lead to publication; many of our interns and staff have gone on to notable careers at MERL and in academia. Come mix with our researchers, see our state of the art technologies, and learn about our research opportunities. Dress code: casual, with resumes.
Pre-registration for the event is strongly encouraged:
https://merlopenhouse2.eventbrite.com/
Current internship and employment openings:
http://www.merl.com/internship/openings
http://www.merl.com/employment/employment.
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- Date & Time: Monday, July 10, 2017; 6:15 PM - 7:15 PM
Location: David Lawrence Convention Center, Pittsburgh PA
Speaker: Andrew Knyazev and other panelists, MERL Brief - Andrew Knyazev accepted an invitation to represent MERL at the panel on Student Careers in Business, Industry and Government at the annual meeting of the Society for Industrial and Applied Mathematics (SIAM).
The format consists of a five minute introduction by each of the panelists covering their background and an overview of the mathematical and computational challenges at their organization. The introductions will be followed by questions from the students.
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- Date & Time: Tuesday, March 28, 2017; 1:30 - 5:30PM
Location: Google (355 Main St., 5th Floor, Cambridge MA)
MERL Contacts: Daniel N. Nikovski; Anthony Vetro; Richard C. (Dick) Waters; Jinyun Zhang Brief - How will AI and robotics reshape the economy and create new opportunities (and challenges) across industries? Who are the hottest companies that will compete with the likes of Google, Amazon, and Uber to create the future? And what are New England innovators doing to strengthen the local cluster and help lead the national discussion?
MERL will be participating in Xconomy's third annual conference on AI and robotics in Boston to address these questions. MERL President & CEO, Dick Waters, will be on a panel discussing the status and future of self-driving vehicles. Lab members will also be on hand demonstrate and discuss recent advances AI and robotics technology.
The agenda and registration for the event can be found online: https://xconomyforum85.eventbrite.com.
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- Date & Time: Thursday, December 8, 2016; 4:00-7:00pm
Location: 201 Broadway, 8th Floor, Cambridge, MA
MERL Contacts: Elizabeth Phillips; Anthony Vetro Brief - Snacks, demos, science: On Thursday 12/8, Mitsubishi Electric Research Labs (MERL) will host an open house for graduate+ students interested in internships, post-docs, and research scientist positions. The event will be held from 4-7pm and will feature demos & short presentations in our main areas of research: algorithms, multimedia, electronics, communications, computer vision, speech processing, optimization, machine learning, data analytics, mechatronics, dynamics, control, and robotics. MERL is a high impact publication-oriented research lab with very extensive internship and university collaboration programs. Most internships lead to publication; many of our interns and staff have gone on to notable careers at MERL and in academia. Come mix with our researchers, see our state of the art technologies, and learn about our research opportunities. Dress code: casual, with resumes.
Pre-registration for the event is strongly encouraged:
https://www.eventbrite.com/e/merl-open-house-tickets-29408503626
Current internship and employment openings:
http://www.merl.com/internship/openings
http://www.merl.com/employment/employment.
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- Date & Time: Wednesday, November 16, 2016; 3:30-6:30pm
Location: Sheraton Commander (16 Garden Street, Cambridge, MA)
MERL Contacts: Elizabeth Phillips; Anthony Vetro Brief - MERL will be participating in the Engineering Career Fair Collaborative, which is being held on November 16, 2016 at the Sheraton Commander in Cambridge from 3:30-6:30pm. Graduate students with an interest in learning about internship and other employment opportunities at MERL are invited to visit our booth. Staff members will be on hand to discuss current openings. We will also be showing some demonstrations of current research projects.
Current internship and employment openings:
http://www.merl.com/internship/openings
http://www.merl.com/employment/employment.
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- Date & Time: Friday, July 22, 2016; 12:00 Noon
Location: Cambridge Brewery
MERL Contacts: Elizabeth Phillips; Jinyun Zhang Brief - MERL hosted its 2nd Annual "Women In Science Celebration". MERL's current team of female interns discussed and celebrated the contributions they've made during their internships at MERL.
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- Date & Time: Wednesday, July 13, 2016; 2:30 PM - 3:30
Speaker: Richard Lehoucq, Sandia National Laboratories
Research Areas: Computer Vision, Digital Video, Machine Learning
Abstract 
My presentation considers the research question of whether existing algorithms and software for the large-scale sparse eigenvalue problem can be applied to problems in spectral graph theory. I first provide an introduction to several problems involving spectral graph theory. I then provide a review of several different algorithms for the large-scale eigenvalue problem and briefly introduce the Anasazi package of eigensolvers.
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- Date & Time: Monday, July 11, 2016; 10 AM - 9:15 PM
Location: Westin Boston Waterfront Pavilion, Boston, Massachusetts
MERL Contacts: Matthew Brand; Arvind Raghunathan Brief - MERL researchers participate in SIAM Job fair to showcase MERL's research and highlight employment and intern opportunities at MERL. The Career Fair emphasizes careers in business, industry, and government, and takes place during the SIAM Annual Meeting.
The SIAM Applied Mathematics and Computational Science Career Fair is an informational and interactive event at which employers and prospective employees can discuss careers. It is a great opportunity for prospective employees to meet government and industry representatives and discuss what they are looking for and what each employer has to offer.
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- Date & Time: Thursday, July 7, 2016; 2:00 PM
Speaker: Dr. Sonja Glavaski, Program Director, ARPA-E
MERL Host: Arvind Raghunathan
Research Area: Electric Systems
Abstract 
The evolution of the grid faces significant challenges if it is to integrate and accept more energy from renewable generation and other Distributed Energy Resources (DERs). To maintain grid's reliability and turn intermittent power sources into major contributors to the U.S. energy mix, we have to think about the grid differently and design it to be smarter and more flexible.
ARPA-E is interested in disruptive technologies that enable increased integration of DERs by real-time adaptation while maintaining grid reliability and reducing cost for customers with smart technologies. The potential impact is significant, with projected annual energy savings of more than 3 quadrillion BTU and annual CO2 emissions reductions of more than 250 million metric tons.
This talk will identify opportunities in developing next generation control technologies and grid operation paradigms that address these challenges and enable secure, stable, and reliable transmission and distribution of electrical power. Summary of newly announced ARPA-E NODES (Network Optimized Distributed Energy Systems) Program funding development of these technologies will be presented.
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- Date: Thursday, June 2, 2016
Location: Norton's Woods Conference Center at American Academy of Arts & Sciences, Cambridge, MA
MERL Contacts: Elizabeth Phillips; Anthony Vetro Brief - MERL celebrated 25 years of innovation on Thursday, June 2 at the Norton's Woods Conference Center at the American Academy of Arts & Sciences in Cambridge, MA. The event was a great success, with inspiring keynote talks, insightful panel sessions, and an exciting research showcase of MERL's latest breakthroughs.
Please visit the event page to view photos of each session, video presentations, as well as a commemorative booklet that highlights past and current research.
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- Date: Thursday, June 2, 2016
Location: Norton's Woods Conference Center at American Academy of Arts & Sciences, Cambridge, MA
MERL Contacts: Elizabeth Phillips; Anthony Vetro Brief - A celebration event to mark MERL's 25th anniversary will be held on Thursday, June 2 at the Norton's Woods Conference Center at the American Academy of Arts & Sciences in Cambridge, MA. This event will feature keynote talks, panel sessions, and a research showcase. The event itself is invitation-only, but videos and other highlights will be made available online. Further details about the program can be obtained at the link below.
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- Date: Friday, November 6, 2015
Location: Mitsubishi Electric Cooling & Heating
MERL Contact: Christopher R. Laughman
Research Area: Data Analytics
Brief - Chris Laughman of MERL and Kevin Miskewicz of MEUS-HVAC led a webinar on Friday, November 6 with over 20 leading HVAC industry trade publications on new products that are being released, as well as the role that MERL plays in advancing the forefront of technology within Mitsubishi Electric. Titled "Inventing the Future of VRF (and Other Neat Stuff)", they discussed the innovations embodied in the new L-generation City-Multi system, as well as trends in the HVAC industry and some recently published MERL research in the HVAC area.
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- Date & Time: Tuesday, August 4, 2015; 12:00
Location: Mitsubishi Electric Research Laboratories
MERL Contacts: Elizabeth Phillips; Jinyun Zhang Brief - To celebrate "Women in Science at MERL," a luncheon event was organized on August 4. Eleven female interns, three female researchers, and female members of HQ staff, interns, hosts/managers and MERL executives participated in that event. All female interns introduced their research projects and their positive experiences at MERL; female researchers shared their own career development stories; and at the end all discussed how to be successful in the field of science. Every participant was inspired to continue contributing to the future of science.
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