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NEWS MERL Presents Five Papers at IEEE Quantum Week 2026 Date: September 13, 2026 - September 18, 2026
Where: Toronto, Canada
MERL Contact: Toshiaki Koike-Akino
Research Areas: Applied Physics, Artificial Intelligence, Machine Learning, Optimization, Signal ProcessingBrief- MERL is pleased to announce that five papers have been accepted to the 2026 IEEE International Conference on Quantum Computing and Engineering (QCE), also known as IEEE Quantum Week 2026, held September 13–18, 2026, in Toronto, Canada.
The papers highlight MERL’s recent advances in quantum computing, spanning hardware-efficient quantum state preparation, quantum low-density parity-check (QLDPC) code design, graph-cover-based code construction, machine-learning-assisted code search, and reinforcement-learning-guided quantum error correction. Together, these works address important challenges toward more efficient and reliable quantum computing systems.
The five papers are:
- “Near-Lower-Bound Approximate Quantum State Preparation with Hardware-Efficient Circuits” — Toshiaki Koike-Akino (TR2026-131)
- “Reinforcement-Learning-Guided Multi-Branch Decoding of Quantum LDPC Codes” — Vahid Nourozi, Toshiaki Koike-Akino, and David Mitchell (TR2026-130)
- “Q-Learning Base Search Voltage-Labeled Covers for Weight-Six Bivariate-Bicycle Quantum LDPC Codes” — Vahid Nourozi, David Mitchell, and Toshiaki Koike-Akino (TR2026-132)
- “Collision-Voltage Design of Directional Covers for Bivariate Bicycle Quantum LDPC Codes” — Vahid Nourozi, David Mitchell, and Toshiaki Koike-Akino (TR2026-133)
- “Base-Preserving APM/Voltage Lifts of Bivariate Bicycle Quantum LDPC Codes” — Vahid Nourozi, David Mitchell, and Toshiaki Koike-Akino (TR2026-129)
- MERL is pleased to announce that five papers have been accepted to the 2026 IEEE International Conference on Quantum Computing and Engineering (QCE), also known as IEEE Quantum Week 2026, held September 13–18, 2026, in Toronto, Canada.
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NEWS MERL collaborator Yuri Shimane receives IFAC Young Author Applications Paper Prize Date: August 28, 2026
MERL Contacts: Stefano Di Cairano; Avishai Weiss
Research Areas: Control, Dynamical Systems, OptimizationBrief- MERL collaborator and former intern Prof. Yuri Shimane received the IFAC Young Author Applications Paper Prize at the 23rd IFAC World Congress 2026, held August 23–28 in Busan, South Korea for a paper co-authored with MERL researchers.
The award recognized Prof. Shimane paper, “Scenario-Based Model Predictive Control for Station Keeping on Near-Rectilinear Halo Orbit,” co-authored with Masafumi Isaji and MERL researchers Avishai Weiss and Stefano Di Cairano.
MERL congratulates Yuri and his co-authors on this recognition.
- MERL collaborator and former intern Prof. Yuri Shimane received the IFAC Young Author Applications Paper Prize at the 23rd IFAC World Congress 2026, held August 23–28 in Busan, South Korea for a paper co-authored with MERL researchers.
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NEWS MERL researchers contribute six papers to IFAC World Congress 2026 Date: August 23, 2026 - August 28, 2026
Where: Busan, South Korea
MERL Contacts: Stefano Di Cairano; Alexander Schperberg; Abraham P. Vinod; Yebin Wang; Avishai Weiss
Research Areas: Control, Dynamical Systems, OptimizationBrief- MERL researchers contributed six papers to the 23rd IFAC World Congress 2026, held August 23–28 in Busan, South Korea. The IFAC World Congress, held every three years, brings together the international control community to share advances in control theory and applications.
The papers covered a range of topics in spacecraft control, autonomous robotics, and precision motion control:
- Coordinated aerial inspection of infrastructure with heterogeneous drones, using drones with complementary sensing capabilities. MERL also released an open-source ROS 2 implementation accompanying the work.
- Geostationary satellite control using averaged dynamics, with the goal of extending the time between east–west station-keeping maneuvers.
- Scenario-based model predictive control for spacecraft station keeping on a near-rectilinear halo orbit.
- Parameter estimation for induction machines, enabling torque-bound construction for trajectory planning and control in precision positioning systems.
- Feedforward control with dual neural networks, improving motion tracking when load-side position measurements are only partially available.
- Constrained sampling-based model predictive control for contact-rich robotics, combining sampling-based exploration with gradient-based refinement for safe and precise robot motion.
In addition to the paper presentations, MERL researcher Abraham Vinod delivered an invited talk at the workshop “Trustworthy Data-Driven Control: From Finite Samples to Robust Guarantees.” His talk discussed data-driven environmental monitoring and decision-making under uncertainty.
- MERL researchers contributed six papers to the 23rd IFAC World Congress 2026, held August 23–28 in Busan, South Korea. The IFAC World Congress, held every three years, brings together the international control community to share advances in control theory and applications.
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AWARD MERL Team Wins Real-TSE Challenge Track 2 on Offline Target Speaker Extraction Date: July 6, 2026
Awarded to: Dominik Klement, Yoshiki Masuyama, Christoph Boeddeker, Kohei Saijo, Julius Richter, Gordon Wichern, and Jonathan Le Roux
MERL Contacts: Christoph Boeddeker; Jonathan Le Roux; Yoshiki Masuyama; Julius Richter; Gordon Wichern
Research Areas: Artificial Intelligence, Machine Learning, Speech & AudioBriefMERL's Speech & Audio team, led by MERL intern Dominik Klement, ranked 1st out of 11 teams in Track 2, "Offline Target Speaker Extraction," of the Real-TSE Challenge. The challenge focuses on target speaker extraction (TSE) from real-world conversational recordings in either English or Chinese, where the goal is to extract the speech of a target speaker in the presence of interfering speakers, background noise, and reverberation.
While modern TSE systems have achieved strong performance on simulated speech mixtures, their performance can degrade considerably on real-world recordings due to the mismatch between simulated training data and actual conversational environments. The Real-TSE Challenge was designed to advance TSE under these realistic conditions, using real far-field conversational recordings for evaluation.
The MERL team won Track 2 by focusing on training data and curriculum learning rather than introducing a new model architecture. Starting from a strong speech separation model, the team progressively trained the system on fully overlapping synthetic speech, simulated conversations, realistic far-field mixtures, and finally real conversational recordings. This approach reduced the token error rate (TER), measured at either the word (English) or character (Chinese) level, from 70% to 37% on the development set and achieved a final TER of 61.3% on the evaluation set, best among the 11 participating teams. The team also topped the leaderboard in terms of the aggregate ranking across the four measures evaluating intelligibility, target speaker presence rate, speaker similarity, and perceptual quality.
The team also investigated the reliability of the challenge metrics and demonstrated that neural network-based speaker similarity and predicted speech-quality scores could be substantially improved without a corresponding improvement in perceptual quality. Because learned metrics can be susceptible to adversarial attacks or optimization that exploits weaknesses in the metric itself, these findings highlight both the importance of realistic training data for real-world TSE and the need for robust evaluation metrics when developing speech extraction systems.
A paper summarizing the team's findings will be presented at the IEEE Spoken Language Technology (SLT) 2026 workshop, to be held in Palermo, Italy from December 13-16, 2026.
REAL-TSE Challenge: Track 2 rankings — Offline Target Speaker Extraction Rank Team TER ↓ F1 ↑ SIM ↑ P808 ↑ Score ↓ 1 MERL 0.613 (1) 0.861 (2) 0.538 (3) 3.371 (2) 2.00 2 YiJiaHe 0.639 (2) 0.871 (1) 0.565 (1) 3.128 (9) 3.25 3 CARTSE 0.651 (3) 0.857 (4) 0.544 (2) 3.138 (8) 4.25 4 WasedaM 0.675 (5) 0.858 (3) 0.480 (6) 3.232 (6) 5.00 5 SonicAGI 0.680 (6) 0.851 (6) 0.471 (7) 3.258 (5) 6.00 6 WAKA 0.670 (4) 0.847 (8) 0.471 (7) 3.150 (7) 6.50 6 SHNU-TSE 0.731 (9) 0.840 (9) 0.507 (5) 3.362 (3) 6.50 7 ChuEst 0.710 (7) 0.831 (11) 0.532 (4) 3.064 (10) 8.00 8 pyannoteAI 0.728 (8) 0.855 (5) 0.464 (9) 2.904 (12) 8.50 9 AGH-JHU 0.743 (10) 0.837 (10) 0.434 (11) 3.335 (4) 8.75 10 WHU_IASP 0.757 (11) 0.850 (7) 0.465 (8) 2.961 (11) 9.25 11 CUDA_OUT_OF_MEMORY 0.827 (12) 0.819 (13) 0.364 (13) 3.435 (1) 9.75 12 BSRNN_EMB Baseline 0.829 (13) 0.829 (12) 0.417 (12) 2.875 (13) 12.50 12 BSRNN_TFMAP Baseline 0.838 (14) 0.829 (12) 0.443 (10) 2.756 (14) 12.50 ↓ Lower is better; ↑ higher is better. Parentheses show metric ranks. The score is the average of the four dense metric ranks; tied scores share a position. Best metric values are bold. P808 denotes DNSMOS-P808.
Source: Official REAL-TSE Challenge rankings. BSRNN entries are organizer baselines.
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AWARD MERL Team Wins DCASE 2026 Challenge on Anomalous Sound Detection for Machine Condition Monitoring Date: June 30, 2026
Awarded to: Takuya Fujimura, Gordon Wichern, Yoshiki Masuyama, Christoph Boeddeker, Kohei Saijo, Julius Richter, Takahiro Edo, and Jonathan Le Roux
MERL Contacts: Christoph Boeddeker; Jonathan Le Roux; Yoshiki Masuyama; Julius Richter; Gordon Wichern
Research Areas: Artificial Intelligence, Machine Learning, Signal Processing, Speech & AudioBrief- MERL's Speech & Audio team ranked 1st out of 51 teams in the DCASE 2026 Challenge’s Task 2, “Noise-aware Unsupervised Anomalous Sound Detection for Machine Condition Monitoring.” The team was led by MERL intern Takuya Fujimura, and also included Gordon Wichern, Yoshiki Masuyama, Christoph Boeddeker, Kohei Saijo, Julius Richter, Takahiro Edo, and Jonathan Le Roux.
The IEEE AASP Challenge on Detection and Classification of Acoustic Scenes and Events (DCASE Challenge), started in 2013, has been organized yearly since 2016, and gathers challenges on multiple tasks related to the detection, analysis, and generation of sound events. This year, the DCASE 2026 Challenge received 421 submissions from 135 teams across seven tasks.
The MERL team won Task 2, Noise-aware Unsupervised Anomalous Sound Detection for Machine Condition Monitoring, which aims at building noise-robust systems for automatically detecting machine failure via microphones when only normal machine operating data is available for system development. Task 2 was by far the most popular out of the 7 DCASE 2026 tasks, with 51 teams submitting 168 entries. The MERL team's system was built around MERL’s recently proposed paradigm of noise-aware self-supervised learning, which extracts noise robust features leveraging two-channel recordings, in which one microphone is used to capture noise. Anomaly detection is then performed in the extracted denoised feature space using advanced score normalization. The team's best submission obtained a composite score of 70.24% on five evaluation machines, largely outperforming the 2nd best team's 65.45%.
MERL also participated in Task 4, Spatial Semantic Segmentation of Sound Scenes (S5) and placed 3rd out of 10 teams in separation performance. Our cascaded system consists of universal sound separation with source counting, source classification, and class-aware refinement, where the separation and refinement modules are built upon MERL's TF-Locoformer separation technology. Notably, the team's best submission obtained a label prediction accuracy of 76.92% on the evaluation set, largely outperforming the 2nd best team's 65.54%.
- MERL's Speech & Audio team ranked 1st out of 51 teams in the DCASE 2026 Challenge’s Task 2, “Noise-aware Unsupervised Anomalous Sound Detection for Machine Condition Monitoring.” The team was led by MERL intern Takuya Fujimura, and also included Gordon Wichern, Yoshiki Masuyama, Christoph Boeddeker, Kohei Saijo, Julius Richter, Takahiro Edo, and Jonathan Le Roux.
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NEWS MERL Presents 4 Main Conference Papers and 6 Workshop Papers at ICML 2026 Date: July 6, 2026 - July 11, 2026
Where: COEX, Seoul, South Korea
MERL Contacts: Moitreya Chatterjee; Anoop Cherian; Stefano Di Cairano; Toshiaki Koike-Akino; Christopher R. Laughman; Jing Liu; Suhas Lohit; Kuan-Chuan Peng; Alexander Schperberg; Ye Wang; Gordon Wichern
Research Areas: Artificial Intelligence, Computer Vision, Machine Learning, Signal ProcessingBrief- MERL researchers are proud to present 4 main conference papers and 6 workshop papers at ICML 2026. ICML, taking place from July 6-11 in Seoul, South Korea, is a premier international conference in machine learning.
Main Conference Papers with MERL Authors:
1. Understanding Dynamic Compute Allocation in Recurrent Transformers by Ibraheem Muhammad Moosa, Suhas Lohit, Ye Wang, Moitreya Chatterjee, and Wenpeng Yin.
2. LLawCo: Learning Laws of Cooperation for Modeling Embodied Multi-Agent Behavior by Qinhong Zhou, Chuang Gan, and Anoop Cherian.
3. Memory-Distilled Selection for Noise-Robust Anomaly Detection by Sirojbek Safarov, Jaewoo Park, Yoon G. Jung, Kuan-Chuan Peng, Wonchul Kim, Seongdeok Bang, and Octavia Camps.
4. Partial Ring Scan: Revisiting Scan Order in Vision State Space Models by Yi-Kuan Hsieh, Kuan-Chuan Peng, Xin Li, Ming-Ching Chang, Yu-Chee Tseng, and Jun-Wei Hsieh.
Workshop Papers with MERL Authors:
1. WISE: Weighted Iterative Society-of-Experts for Multimodal Multi-Agent Debate with Probabilistic Consensus by Anoop Cherian, Suhas Lohit, and Kuan-Chuan Peng. (Workshop on Scalable Learning and Optimization for Efficient Multimodal AI Agents (SCALE))
2. MIRROR: Multisensory Implicit Rejection-sampled RObotic policy by Amisha Bhaskar, Pratap Tokekar, Stefano Di Cairano, and Alexander Schperberg. (Workshop on Structured Probabilistic Inference & Generative Modeling)
3. Reinforced Neural Processes: Memory-Efficient Time-Series Forecasting with a World-Feedback-Trained Memory Policy by Nibraas Khan, Gordon Wichern, and Christopher R. Laughman. (Workshop on Reinforcement Learning from World Feedback (RLxF))
4. Connecting Low-Rank Adapters and Policy Stability in GRPO Fine-Tuning by Antonin Rottman, Francesco Tonin, Yongtao Wu, Toshiaki Koike-Akino, and Volkan Cevher. (Workshop on Connecting Low-rank Representations in AI (CoLorAI))
5. EinSort: Sorting is All We Need for Tensorizing LLM by Toshiaki Koike-Akino, Jing Liu, and Ye Wang. (Workshop on Connecting Low-rank Representations in AI (CoLorAI))
6. Temper and Tilt Lead to SLOP: Reward Hacking Mitigation with Inference-Time Alignment by Ye Wang, and Jing Liu, and Toshiaki Koike-Akino. (Workshop on Agents in the Wild: Safety, Security, and Beyond)
- MERL researchers are proud to present 4 main conference papers and 6 workshop papers at ICML 2026. ICML, taking place from July 6-11 in Seoul, South Korea, is a premier international conference in machine learning.
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NEWS MERL researchers present 9 papers at IEEE ICRA 2026 Date: June 1, 2026 - June 5, 2026
Where: Vienna, Austria
MERL Contacts: Radu Corcodel; Stefano Di Cairano; Purnanand Elango; Siddarth Jain; Alexander Schperberg; Kento Tomita
Research Areas: Artificial Intelligence, Computer Vision, Control, Dynamical Systems, Machine Learning, Optimization, RoboticsBrief- MERL researchers presented nine papers at the recently concluded IEEE International Conference on Robotics and Automation (ICRA) 2026 in Vienna, Austria. The papers covered a broad set of topics in robotics, including robot perception, visuo-tactile sensing, contact and pose estimation, manipulation, reinforcement learning, diffusion policies, loco-manipulation, contact-implicit trajectory optimization, legged locomotion, localization, and perception-aware planning.
IEEE ICRA is the flagship conference of the IEEE Robotics and Automation Society and the world’s largest and most comprehensive technical conference focused on research advances and the latest technological developments in robotics. The event attracts nearly 8,000 participants and receives more than 5,000 paper submissions.
- MERL researchers presented nine papers at the recently concluded IEEE International Conference on Robotics and Automation (ICRA) 2026 in Vienna, Austria. The papers covered a broad set of topics in robotics, including robot perception, visuo-tactile sensing, contact and pose estimation, manipulation, reinforcement learning, diffusion policies, loco-manipulation, contact-implicit trajectory optimization, legged locomotion, localization, and perception-aware planning.
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NEWS Petros Boufounos elected Vice President–Conferences of the IEEE Signal Processing Society Date: June 24, 2026
MERL Contact: Petros T. Boufounos
Research Areas: Computational Sensing, Signal ProcessingBrief- MERL's Distinguished Research Scientist and IEEE Fellow Dr. Petros Boufounos has been elected Vice President–Conferences of the IEEE Signal Processing Society (SPS) for the 2027–2029 term. In this role, he will serve on the SPS Board of Governors and chair the SPS Conferences Board, overseeing the Society’s conferences, workshops, and other technical meeting activities.
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NEWS MERL researchers present 8 papers at ACC 2026 Date: May 26, 2026 - May 29, 2026
Where: New Orleans, USA
MERL Contacts: Scott A. Bortoff; Vedang M. Deshpande; Stefano Di Cairano; Christopher R. Laughman; Jordan Leung; Hongtao Qiao; Zhaolin Ren; Abraham P. Vinod; Yebin Wang
Research Areas: Control, Dynamical Systems, Optimization, RoboticsBrief- MERL researchers presented 8 papers at the recently concluded American Control Conference (ACC) 2026 in New Orleans, USA. The papers covered a wide range of topics including robust controllable set computation, vapor compression cycle calibration, task-reasoning LLM agents, Minkowski-cost stable MPC, polynomial chaos approximation, invariant-set motion planning, heat-pump MPC architectures, and relaxed barrier-function MPC. Additionally, Zhaolin Ren was an invited speaker at Multi-Agent Dynamic Games workshop, and Abraham Vinod served as a panelist at the Professional Development and Career Advice for Young Professionals session.
As a sponsor of the conference, MERL maintained a booth for open discussions with researchers and students, and hosted a special session to discuss highlights of MERL research and work philosophy.
- MERL researchers presented 8 papers at the recently concluded American Control Conference (ACC) 2026 in New Orleans, USA. The papers covered a wide range of topics including robust controllable set computation, vapor compression cycle calibration, task-reasoning LLM agents, Minkowski-cost stable MPC, polynomial chaos approximation, invariant-set motion planning, heat-pump MPC architectures, and relaxed barrier-function MPC. Additionally, Zhaolin Ren was an invited speaker at Multi-Agent Dynamic Games workshop, and Abraham Vinod served as a panelist at the Professional Development and Career Advice for Young Professionals session.
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NEWS MERL Presents Set-Based Reachability Research for Spacecraft Guidance at NASA Johnson Space Center Date: April 15, 2026 - April 16, 2026
Where: NASA Johnson Space Center, Houston
MERL Contacts: Abraham P. Vinod; Avishai Weiss
Research Areas: Control, Dynamical Systems, Optimization, RoboticsBrief- MERL researchers Avishai Weiss and Abraham Vinod visited NASA Johnson Space Center to present recent advances in set-based reachability analysis for spacecraft guidance, navigation, and control, with an emphasis on powered descent guidance for lunar landing. They delivered an invited talk titled “Safe and Optimal Control for Spacecraft GN&C using Set-Based Reachability Analysis.”
The presentation introduced MERL’s recently developed set-based computational techniques for safe, optimal, and robust spacecraft control, including methods that specialize the approach for computing maximum divert envelopes and enabling real-time landing footprint prediction for landers. The talk was attended by researchers from NASA and the University of Washington, and generated extensive technical discussion.
- MERL researchers Avishai Weiss and Abraham Vinod visited NASA Johnson Space Center to present recent advances in set-based reachability analysis for spacecraft guidance, navigation, and control, with an emphasis on powered descent guidance for lunar landing. They delivered an invited talk titled “Safe and Optimal Control for Spacecraft GN&C using Set-Based Reachability Analysis.”
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NEWS MERL Presents 7 Papers and 2 Workshops at CVPR 2026 Date: June 3, 2026 - June 7, 2026
Where: Colorado Convention Center, Denver, Colorado
MERL Contacts: Moitreya Chatterjee; Anoop Cherian; Suhas Lohit; Lalit Manam; Tim K. Marks; Pedro Miraldo; Kuan-Chuan Peng
Research Areas: Artificial Intelligence, Computer Vision, Machine LearningBrief- MERL researchers are proud to present 7 papers, including two highlight papers (top 3.6% of submissions), and 2 workshops at CVPR 2026. CVPR, taking place from June 3-7 in Denver, CO, USA, is a premier international conference in computer vision.
Papers with MERL Authors:
1. Point4Cast: Streaming Dynamic Scene Reconstruction and Forecasting by Xinhang Liu, Pedro Miraldo, Suhas Lohit, Huaizu Jiang, Naoko Sawada, Yu-Wing Tai, Chi-Keung Tang, and Moitreya Chatterjee (Highlight Paper)
2. Parallel Rigidity Matters for Bundle Adjustment by Lalit Manam and Venu Govindu (Highlight Paper)
3. Revisiting Monocular SLAM with Spatio-Temporal Scene Modeling by Valter Piedade, Lalit Manam, Masashi Yamazaki, and Pedro Miraldo
4. AssemblyBench: Physics-Aware Assembly of Complex Industrial Objects by Danrui Li, Jiahao Zhang, Bernhard Egger, Moitreya Chatterjee, Suhas Lohit, Tim K. Marks, and Anoop Cherian
5. LASER: Layer-wise Scale Alignment for Training-Free Streaming 4D Reconstruction by Tianye Ding, Yiming Xie, Yiqing Liang, Moitreya Chatterjee, Pedro Miraldo, and Huaizu Jiang
6. SoREL: Soft-Label Refurbishment with Ensemble Learning for Noisy Long-Tailed Classification by Jun-Wei Hsieh, Ying-Hsuan Wu, Yi-Kuan Hsieh, Xin Li, Kuan-Chuan Peng, Ming-Ching Chang (CVPR Findings paper)
7. MMHOI: Complex 3D Multi-Human-Object Interaction Understanding by Kaen Kogashi and Anoop Cherian (PhysHuman Workshop paper)
Workshops Co-Organized by MERL:
1. Multimodal Algorithmic Reasoning Workshop by Anoop Cherian, Suhas Lohit, Kuan-Chuan Peng, Honglu Zhou, Kevin Smith, and Josh Tenenbaum
2. The Third Workshop on Anomaly Detection with Foundation Models by Kuan-Chuan Peng, Ying Zhao, and Abhishek Aich
- MERL researchers are proud to present 7 papers, including two highlight papers (top 3.6% of submissions), and 2 workshops at CVPR 2026. CVPR, taking place from June 3-7 in Denver, CO, USA, is a premier international conference in computer vision.
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NEWS MERL hosts Boston AI Music Meetup Date: March 19, 2026
Where: Cambridge, MA
MERL Contact: Gordon Wichern
Research Areas: Artificial Intelligence, Machine Learning, Speech & AudioBrief- MERL hosted the Boston AI Music Meetup on March 19, 2026, bringing together researchers, musicians, and technologists from the local community to explore the intersection of artificial intelligence and music. The event featured talks on emerging approaches in AI-driven audio and creative tools, including a presentation by Elena Georgieva (NYU MARL) on improving audio quality for singing and speech using CLAP-based methods, as well as a talk by Ashvala Vinay (NoneType) on creative workflows using infinite canvas systems. Following the presentations, attendees participated in a networking session, fostering discussion and collaboration across academia and industry.
The Boston AI Music Meetup has been held monthly since 2024 (including a presentation on MERL’s music source separation work in May 2025), and has grown to include over 1,200 subscribers, attracting attendees from across the Northeast. It provides a forum for knowledge exchange and collaboration within the rapidly evolving AI music ecosystem, with discussions spanning music information retrieval, generative AI, and machine learning for creative practice.
- MERL hosted the Boston AI Music Meetup on March 19, 2026, bringing together researchers, musicians, and technologists from the local community to explore the intersection of artificial intelligence and music. The event featured talks on emerging approaches in AI-driven audio and creative tools, including a presentation by Elena Georgieva (NYU MARL) on improving audio quality for singing and speech using CLAP-based methods, as well as a talk by Ashvala Vinay (NoneType) on creative workflows using infinite canvas systems. Following the presentations, attendees participated in a networking session, fostering discussion and collaboration across academia and industry.
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NEWS Toshiaki Koike-Akino delivers an invited talk as a panelist at OFC 2026 Date: March 17, 2026
MERL Contact: Toshiaki Koike-Akino
Research Areas: Artificial Intelligence, Communications, Machine Learning, Signal ProcessingBrief- MERL researcher Toshiaki Koike-Akino will serve as a panelist at OFC 2026, the premier global event for optical communications and networking, to be held in Los Angeles, March 15–19.
Dr. Koike-Akino will participate in the special panel session titled “Machine Learning is Taking Over Optical Communications—But Which Algorithms Should We Use?” He will deliver a panel talk titled “Scaling AI with Light: AI Is Taking Over Optics — But Optics May Take Over AI.” His talk will discuss the growing synergy between AI and optical technologies, highlighting the emerging vision of leveraging optical physics not only as an application domain for AI, but also as a platform for scaling future AI systems.
- MERL researcher Toshiaki Koike-Akino will serve as a panelist at OFC 2026, the premier global event for optical communications and networking, to be held in Los Angeles, March 15–19.
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NEWS MERL researcher Purnanand Elango receives Best Paper Award at the AIAA SciTech Forum 2026. Date: January 12, 2026
Where: Orlando, FL
MERL Contact: Purnanand Elango
Research Areas: Control, OptimizationBrief- MERL research scientist Purnanand Elango received the Atmospheric Flight Mechanics (AFM) Best Paper Award at the AIAA SciTech Forum 2026 in January for the paper, “Auto-tuned Primal-dual Successive Convexification for Hypersonic Reentry Guidance.”, that he co-authored during his PhD research at the University of Washington, before joining MERL.
The paper presents a trajectory optimization method that reduces parameter-tuning effort for nonconvex optimization algorithms, such as sequential convex programming, in solving a challenging real-world optimal control problems.
The AIAA SciTech Forum is the flagship conference (more than 6000 attendees from 48 countries) of the American Institute of Aeronautics and Astronautics, the world's largest professional technical society dedicated to aerospace.
- MERL research scientist Purnanand Elango received the Atmospheric Flight Mechanics (AFM) Best Paper Award at the AIAA SciTech Forum 2026 in January for the paper, “Auto-tuned Primal-dual Successive Convexification for Hypersonic Reentry Guidance.”, that he co-authored during his PhD research at the University of Washington, before joining MERL.
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NEWS MERL researcher Abraham Vinod delivers an invited talk at CVXPY workshop 2026 Date: February 20, 2026
MERL Contact: Abraham P. Vinod
Research Areas: Control, Dynamical Systems, Optimization, RoboticsBrief- MERL researcher Abraham Vinod was an invited speaker at the inaugural CVXPY Workshop 2026, held at Stanford University, USA. CVXPY is an open-source, Python-embedded modeling language for convex optimization, and the workshop brought together researchers and practitioners to share ideas and real-world Python-based applications of convex optimization. Abraham’s talk, titled “pycvxset: Convex Sets in Python,” introduced MERL’s recently released open-source toolbox for convex set manipulation to the CVXPY community. The talk highlighted the toolbox’s capabilities and showcased recent applications in autonomous precision landing and robotics. The workshop details are available at https://www.cvxpy.org/workshop/2026/.
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NEWS Stefano Di Cairano elected to the Board of Governors of the IEEE Control System Society Date: February 11, 2026
MERL Contact: Stefano Di Cairano
Research Areas: Control, Dynamical SystemsBrief- Dr. Stefano Di Cairano, Distinguished Research Scientist at MERL and Fellow, IEEE has been recently elected as a member of the board of governor of the IEEE Control Systems Society, for the term 2026-2028.
The Control Systems Society (CSS) is the IEEE society dedicated to advancing the theory and practice of automatic control, engineering systems, and decision-making.
The Board of Governors has the responsibility for governing the IEEE Control Systems Society, by operating according to a set of bylaws to set strategic direction, provide necessary resources, and make key decisions to implement that will meet member needs.
- Dr. Stefano Di Cairano, Distinguished Research Scientist at MERL and Fellow, IEEE has been recently elected as a member of the board of governor of the IEEE Control Systems Society, for the term 2026-2028.
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NEWS MERL researchers present 3 papers at AIAA SciTech Forum 2026 Date: January 12, 2026 - January 16, 2026
Where: Orlando, Florida
MERL Contacts: Stefano Di Cairano; Purnanand Elango; Kento Tomita; Abraham P. Vinod; Avishai Weiss
Research Areas: Control, Dynamical Systems, OptimizationBrief- MERL researchers presented 3 papers at the recently concluded AIAA SciTech Forum 2026 in Orlando, Florida. The AIAA SciTech Forum is the flagship conference (more than 6,000 from 48 countries) of the American Institute of Aeronautics and Astronautics, the world's largest professional technical society dedicated to aerospace.
The papers presented by MERL researchers covered 1) a powered descent decision making approach to maximize the probability of safe landing, 2) a set-based robust, optimal, and resilient control architecture for autonomous precision landing, and 3) a continuous-time safe control policy for passively-safe spacecraft rendezvous on a Near Rectilinear Halo Orbit using successive convexification.
- MERL researchers presented 3 papers at the recently concluded AIAA SciTech Forum 2026 in Orlando, Florida. The AIAA SciTech Forum is the flagship conference (more than 6,000 from 48 countries) of the American Institute of Aeronautics and Astronautics, the world's largest professional technical society dedicated to aerospace.
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NEWS MERL Researcher Diego Romeres Collaborates with Mitsubishi Electric and University of Padua to Advance Physics-Embedded AI for Predictive Equipment Maintenance Date: December 10, 2025
Research Areas: Artificial Intelligence, Machine Learning, RoboticsBrief- Mitsubishi Electric Research Laboratories (MERL) researchers, together with collaborators at Mitsubishi Electric’s Information Technology R&D Center in Kamakura, Kanagawa Prefecture, Japan, and the Department of Information Engineering at the University of Padua, have developed a cutting-edge physics-embedded AI technology that substantially improves the accuracy of equipment degradation estimation using minimal training data. This collaborative effort has culminated in a press release by Mitsubishi Electric Corporation announcing the new AI technology as part of its Neuro-Physical AI initiative under the Maisart program.
The interdisciplinary team, including MERL Senior Principal Research Scientist and Team Leader Diego Romeres and University of Padua researchers Alberto Dalla Libera and Giulio Giacomuzzo, combined expertise in machine learning, physical modeling, and real-world industrial systems to embed physics-based models directly into AI frameworks. By training AI with theoretical physical laws and real operational data, the resulting system delivers reliable degradation estimates on the torque of robotic arms even with limited datasets. This result addresses key challenges in preventive maintenance for complex manufacturing environments and supports reduced downtime, maintained quality, and lower lifecycle costs.
The successful integration of these foundational research efforts into Mitsubishi Electric’s business-scale AI solutions exemplifies MERL’s commitment to translating fundamental innovation into real-world impact.
- Mitsubishi Electric Research Laboratories (MERL) researchers, together with collaborators at Mitsubishi Electric’s Information Technology R&D Center in Kamakura, Kanagawa Prefecture, Japan, and the Department of Information Engineering at the University of Padua, have developed a cutting-edge physics-embedded AI technology that substantially improves the accuracy of equipment degradation estimation using minimal training data. This collaborative effort has culminated in a press release by Mitsubishi Electric Corporation announcing the new AI technology as part of its Neuro-Physical AI initiative under the Maisart program.
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NEWS MERL Researchers at NeurIPS 2025 presented 2 conference papers, 5 workshop papers, and organized a workshop. Date: December 2, 2025 - December 7, 2025
Where: San Diego
MERL Contacts: Petros T. Boufounos; Anoop Cherian; Radu Corcodel; Stefano Di Cairano; Chiori Hori; Christopher R. Laughman; Suhas Lohit; Pedro Miraldo; Saviz Mowlavi; Kuan-Chuan Peng; Arvind Raghunathan; Abraham P. Vinod; Pu (Perry) Wang
Research Areas: Artificial Intelligence, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & AudioBrief- MERL researchers presented 2 main-conference papers and 5 workshop papers, as well as organized a workshop, at NeurIPS 2025.
Main Conference Papers:
1) Sorachi Kato, Ryoma Yataka, Pu Wang, Pedro Miraldo, Takuya Fujihashi, and Petros Boufounos, "RAPTR: Radar-based 3D Pose Estimation using Transformer", Code available at: https://github.com/merlresearch/radar-pose-transformer
2) Runyu Zhang, Arvind Raghunathan, Jeff Shamma, and Na Li, "Constrained Optimization From a Control Perspective via Feedback Linearization"
Workshop Papers:
1) Yuyou Zhang, Radu Corcodel, Chiori Hori, Anoop Cherian, and Ding Zhao, "SpinBench: Perspective and Rotation as a Lens on Spatial Reasoning in VLMs", NeuriIPS 2025 Workshop on SPACE in Vision, Language, and Embodied AI (SpaVLE) (Best Paper Runner-up)
2) Xiaoyu Xie, Saviz Mowlavi, and Mouhacine Benosman, "Smooth and Sparse Latent Dynamics in Operator Learning with Jerk Regularization", Workshop on Machine Learning and the Physical Sciences (ML4PS)
3) Spencer Hutchinson, Abraham Vinod, François Germain, Stefano Di Cairano, Christopher Laughman, and Ankush Chakrabarty, "Quantile-SMPC for Grid-Interactive Buildings with Multivariate Temporal Fusion Transformers", Workshop on UrbanAI: Harnessing Artificial Intelligence for Smart Cities (UrbanAI)
4) Yuki Shirai, Kei Ota, Devesh Jha, and Diego Romeres, "Sim-to-Real Contact-Rich Pivoting via Optimization-Guided RL with Vision and Touch", Worskhop on Embodied World Models for Decision Making
5) Mark Van der Merwe and Devesh Jha, "In-Context Policy Iteration for Dynamic Manipulation", Workshop on Embodied World Models for Decision Making
Workshop Organized:
MERL members co-organized the Multimodal Algorithmic Reasoning (MAR) Workshop (https://marworkshop.github.io/neurips25/). Organizers: Anoop Cherian (Mitsubishi Electric Research Laboratories), Kuan-Chuan Peng (Mitsubishi Electric Research Laboratories), Suhas Lohit (Mitsubishi Electric Research Laboratories), Honglu Zhou (Salesforce AI Research), Kevin Smith (Massachusetts Institute of Technology), and Joshua B. Tenenbaum (Massachusetts Institute of Technology).
- MERL researchers presented 2 main-conference papers and 5 workshop papers, as well as organized a workshop, at NeurIPS 2025.
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NEWS Abraham Vinod Delivers Invited Talks at The University of Texas at Austin and The University of Texas at Dallas Date: November 11, 2025 - November 13, 2025
MERL Contact: Abraham P. Vinod
Research Areas: Artificial Intelligence, Control, Dynamical Systems, Machine Learning, Optimization, RoboticsBrief- MERL researcher Abraham Vinod was invited to present MERL's latest research at the University of Texas at Austin and The University of Texas at Dallas this November. His talk discussed a tractable set-based method for a broad class of robust control problems with nonlinear dynamics and bounded uncertainty, with applications to powered descent guidance and drone motion planning problems. Additionally, he also presented MERL's recent research on environmental monitoring using hetereogenous robots, with applications in disaster management and search-and-rescue.
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NEWS Jonathan Le Roux Elected Vice Chair and Gordon Wichern Reelected as Member of the IEEE AASP Technical Committee Date: November 14, 2025
MERL Contacts: Jonathan Le Roux; Gordon Wichern
Research Areas: Artificial Intelligence, Machine Learning, Speech & AudioBrief- Two members of MERL’s Speech and Audio Team have been elected to important positions within the IEEE Audio and Acoustic Signal Processing Technical Committee (AASP TC), a leading body of the IEEE Signal Processing Society that brings together experts from academia and industry working on speech, music, environmental audio, spatial acoustics, enhancement, separation, and machine learning for audio. The committee plays a central role in guiding the scientific direction of the field by promoting emerging research areas, shaping major conferences such as ICASSP and WASPAA, organizing special sessions and tutorials, and fostering a vibrant and collaborative global community.
Jonathan Le Roux, Senior Team Leader and Distinguished Research Scientist, has been elected as the next Vice Chair of the AASP TC. His election reflects his longstanding contributions to the audio and acoustic signal processing community, his leadership in workshop and conference organization, and his significant impact across a wide range of research areas within the TC’s scope. Jonathan will serve a one-year term as Vice Chair, after which he will succeed Prof. Minje Kim (UIUC) as Chair of the AASP TC for a two-year term in 2027–28, helping steer the committee’s strategic initiatives and continued growth.
During the same election, Senior Principal Research Scientist Gordon Wichern, who currently serves as Chair of the Review Subcommittee, was reelected for a second three-year term as a member of the AASP TC, serving from 2026 to 2028. His continued presence on the committee reflects his impactful research and active service to the audio and acoustic signal processing community.
- Two members of MERL’s Speech and Audio Team have been elected to important positions within the IEEE Audio and Acoustic Signal Processing Technical Committee (AASP TC), a leading body of the IEEE Signal Processing Society that brings together experts from academia and industry working on speech, music, environmental audio, spatial acoustics, enhancement, separation, and machine learning for audio. The committee plays a central role in guiding the scientific direction of the field by promoting emerging research areas, shaping major conferences such as ICASSP and WASPAA, organizing special sessions and tutorials, and fostering a vibrant and collaborative global community.
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AWARD MERL team wins the Generative Data Augmentation of Room Acoustics (GenDARA) 2025 Challenge Date: April 7, 2025
Awarded to: Christopher Ick, Gordon Wichern, Yoshiki Masuyama, François G. Germain, and Jonathan Le Roux
MERL Contacts: Jonathan Le Roux; Yoshiki Masuyama; Gordon Wichern
Research Areas: Artificial Intelligence, Machine Learning, Speech & AudioBrief- MERL's Speech & Audio team ranked 1st out of 3 teams in the Generative Data Augmentation of Room Acoustics (GenDARA) 2025 Challenge, which focused on “generating room impulse responses (RIRs) to supplement a small set of measured examples and using the augmented data to train speaker distance estimation (SDE) models". The team was led by MERL intern Christopher Ick, and also included Gordon Wichern, Yoshiki Masuyama, François G. Germain, and Jonathan Le Roux.
The GenDARA Challenge was organized as part of the Generative Data Augmentation (GenDA) workshop at the 2025 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2025), and held on April 7, 2025 in Hyderabad, India. Yoshiki Masuyama presented the team's method, "Data Augmentation Using Neural Acoustic Fields With Retrieval-Augmented Pre-training".
The GenDARA challenge aims to promote the use of generative AI to synthesize RIRs from limited room data, as collecting or simulating RIR datasets at scale remains a significant challenge due to high costs and trade-offs between accuracy and computational efficiency. The challenge asked participants to first develop RIR generation systems capable of expanding a sparse set of labeled room impulse responses by generating RIRs at new source–receiver positions. They were then tasked with using this augmented dataset to train speaker distance estimation systems. Ranking was determined by the overall performance on the downstream SDE task. MERL’s approach to the GenDARA challenge centered on a geometry-aware neural acoustic field model that was first pre-trained on a large external RIR dataset to learn generalizable mappings from 3D room geometry to room impulse responses. For each challenge room, the model was then adapted or fine-tuned using the small number of provided RIRs, enabling high-fidelity generation of RIRs at unseen source–receiver locations. These augmented RIR sets were subsequently used to train the SDE system, improving speaker distance estimation by providing richer and more diverse acoustic training data.
- MERL's Speech & Audio team ranked 1st out of 3 teams in the Generative Data Augmentation of Room Acoustics (GenDARA) 2025 Challenge, which focused on “generating room impulse responses (RIRs) to supplement a small set of measured examples and using the augmented data to train speaker distance estimation (SDE) models". The team was led by MERL intern Christopher Ick, and also included Gordon Wichern, Yoshiki Masuyama, François G. Germain, and Jonathan Le Roux.
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NEWS MERL Papers, Workshops, and Talks at ICCV 2025 Date: October 19, 2025 - October 23, 2025
Where: Honolulu, HI, USA
MERL Contacts: Petros T. Boufounos; Anoop Cherian; Toshiaki Koike-Akino; Hassan Mansour; Tim K. Marks; Pedro Miraldo; Kuan-Chuan Peng; Pu (Perry) Wang
Research Areas: Artificial Intelligence, Computer Vision, Machine Learning, Signal ProcessingBrief- MERL researchers presented 3 conference papers and 3 workshop papers, co-organized 2 workshops, and delivered 2 invited talks at the IEEE International Conference on Computer Vision (ICCV) 2025, which was held in Honolulu, HI, USA from October 19-23, 2025. ICCV is one of the most prestigious and competitive international conferences in the area of computer vision. Details of MERL contributions are provided below:
Main Conference Papers:
1. "SAC-GNC: SAmple Consensus for adaptive Graduated Non-Convexity" by V. Piedade, C. Sidhartha, J. Gaspar, V. M. Govindu, and P. Miraldo. (Highlight Paper)
Paper: https://www.merl.com/publications/TR2025-146
2. "Toward Long-Tailed Online Anomaly Detection through Class-Agnostic Concepts" by C.-A. Yang, K.-C. Peng, and R. A. Yeh.
Paper: https://www.merl.com/publications/TR2025-124
3. "Manual-PA: Learning 3D Part Assembly from Instruction Diagrams" by J. Zhang, A. Cherian, C. Rodriguez-Opazo, W. Deng, and S. Gould.
Paper: https://www.merl.com/publications/TR2025-139
MERL Co-Organized Workshops:
1. "The Workshop on Anomaly Detection with Foundation Models (ADFM)" by K.-C. Peng, Y. Zhao, and A. Aich.
Workshop link: https://adfmw.github.io/iccv25/
2. "The 8th International Workshop on Computer Vision for Physiological Measurement (CVPM)" by D. McDuff, W. Wang, S. Stuijk, T. Marks, H. Mansour, V. R. Shenoy.
Workshop link: https://sstuijk.estue.nl/cvpm/cvpm25/
MERL Keynote Talks at Workshops:
1. Tim K. Marks, Keynote Speaker at the Workshop on Computer Vision for Physiological Measurement (CVPM).
Workshop website: https://vineetrshenoy.github.io/cvpmSeptember2025/
2. Tim K. Marks, Keynote Speaker at the Workshop on Analysis and Modeling of Faces and Gestures (AMFG).
Workshop website: https://fulab.sites.northeastern.edu/amfg2025/
Workshop Papers:
1. "Joint Training of Image Generator and Detector for Road Defect Detection" by K.-C. Peng.
paper: https://www.merl.com/publications/TR2025-149
2. "Radar-Conditioned 3D Bounding Box Diffusion for Indoor Human Perception" by R. Yataka, P. Wang, P.T. Boufounos, and R. Takahashi.
paper: https://www.merl.com/publications/TR2025-154
3. "L-GGSC: Learnable Graph-based Gaussian Splatting Compression" by S. Kato, T. Koike-Akino, and T. Fujihashi.
paper: https://www.merl.com/publications/TR2025-148
- MERL researchers presented 3 conference papers and 3 workshop papers, co-organized 2 workshops, and delivered 2 invited talks at the IEEE International Conference on Computer Vision (ICCV) 2025, which was held in Honolulu, HI, USA from October 19-23, 2025. ICCV is one of the most prestigious and competitive international conferences in the area of computer vision. Details of MERL contributions are provided below:
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NEWS Hongbo Sun Awarded 2025 IEEE Power & Energy Society (PES) Prize Paper Award Date: July 27, 2025 - July 31, 2025
Where: Austin,TX
MERL Contact: Hongbo Sun
Research Area: Electric SystemsBrief- Hongbo Sun has been recognized with the 2025 IEEE PES Prize Paper Award for co-authoring the paper “Methods for Analysis and Quantification of Power System Resilience”, published in the IEEE Transactions on Power Systems in 2023. The paper summarizes the report prepared by an IEEE PES Task Force that defines and quantifies power system resilience. Resilience is a fairly new technical concept for power systems, and it is important to precisely delineate this concept for actual applications. This paper defines resilience, compares resilience with related technical concepts, and summarizes measures to enhance system resilience. Several gaps are identified to indicate further needs for research and development.
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AWARD MERL intern and Researchers wins 2025 IEEE CCTA Best Student Paper Award Date: August 27, 2025
Awarded to: Yingjie Hu (Student, Intern), Karl Berntorp, Stefano Di Cairano (MERL Researchers)
MERL Contact: Stefano Di Cairano
Research Areas: Control, Dynamical Systems, Signal ProcessingBrief- MERL intern Yingjie Hu was recognized as the winner of the 2025 IEEE CCTA Best Student Paper Award for the paper "Optimal Measurement Projection in GNSS-RTK Factor Graph Optimization" written in collaboration with MERL Researchers Karl Berntorp and Stefano Di Cairano during the internship at MERL
The paper develops methods for measurement projections for reducing the computational burden of factor graph optimization algorithms in GNSS applications, thus enabling their use in real-time in a wider range of positioning applications.
The IEEE Conference on Control Technology and Application is the conference of the IEEE Control Systems Society focused on applications and technological advances of control systems
- MERL intern Yingjie Hu was recognized as the winner of the 2025 IEEE CCTA Best Student Paper Award for the paper "Optimal Measurement Projection in GNSS-RTK Factor Graph Optimization" written in collaboration with MERL Researchers Karl Berntorp and Stefano Di Cairano during the internship at MERL