Internship at MERL
MERL's internship program gives students excellent opportunities to work in an industrial research lab environment side-by-side with world-class researchers.
Program Overview
The internship program at MERL emphasizes close collaboration with a particular researcher or members of a small team. Primary areas of work include:
- Artificial Intelligence including:
- Machine Learning
- Computer Vision
- Speech Recognition
- Acoustic Analysis
- Data Analytics
- Cyber-Physical Systems including:
- Signal Processing
- Digital & Optical Communications
- Multi-Physical Modeling
- Planning, Optimization & Control
- Dynamical Systems
- Design of Algorithms and Semiconductor Devices
The primary intent of MERL's internship program is to provide interns with experiences that help them enhance and accelerate their professional career, while contributing to new or ongoing initiatives at MERL. Interns are exposed to relevant industrial problems ranging from speculative and exploratory research to more practical engineering tasks. Interns have a chance to become familiar with the open research culture at MERL, produce publishable work, and develop an appreciation for how breakthrough research makes an impact on future products.
MERL considers graduate students from all over the world. As many of our projects benefit from
specialized knowledge in a given field, graduate students pursuing a Ph.D. typically fill the majority of
internship openings.
Set Your Own Path - Internships at MERL
The duration of a typical internship varies from 3 months to 1 year, with the majority of interns being employed during the summer months. As the summer is a very busy time, we encourage applications for non-summer internships and also prefer early applications for summer internships. Hiring decisions for the summer are typically made around January/February to allow enough time for any necessary paperwork (such as visa applications or other work eligibility forms) to be completed.
Boston is a fantastic city with one of the largest student populations of any city in the US. There are
many social and leisure activities to get involved in, and no shortage of things to do during your stay.
With close proximity to major universities such as MIT and Harvard, there are also many chances to
attend seminars and lectures by well-known experts in various fields. During the summer, MERL organizes a
number of social activities for interns. Some past activities included BBQ outings, whale watching and movie nights.
The key benefits of interning at MERL:
- Experience: At MERL, you work closely with top researchers and participate in a lab-wide R&D culture with a unique mix of curiosity-driven research and market-oriented prototyping.
- Publication: MERL is an open research lab with a strong tradition of publication in high-impact peer-reviewed venues. Internships typically aim at producing publication-worthy results and interns are co-authors on many papers each year.
- Compensation: MERL offers competitive salaries based on relevant education, skills, and work experience.
- Perks: MERL provides relocation assistance including travel costs; subsidies for commuting costs; and entertainment events for interns to get to know Boston and each other.
- Networking: Interns are encouraged to network with MERL's research staff, fellow interns, and faculty at local universities. Weekly socials and seminars provide many venues.
- Opportunity: Many MERL interns have gone on to distinguished careers at MERL. MERL research hosts have often provided letters of reference supporting their ex-interns' candidacies for jobs, fellowships, and tenure.
-
Recent Publications with MERL Interns
Publications are an important output of MERL's research, and internships often lead to one or more publications. Below is a sample listing of some recent publications that include interns as co-authors. Please visit our publications page for a complete listing of MERL papers.
- "Travel-time prediction using neural-network-based mixture models", International Workshop on Statistical Methods and Artificial Intelligence, March 2023.BibTeX TR2023-012 PDF
- @inproceedings{Sharma2023mar,
- author = {Sharma, Abhishek and Zhang, Jing and Nikovski, Daniel and Doshi-Velez, Finale},
- title = {Travel-time prediction using neural-network-based mixture models},
- booktitle = {International Workshop on Statistical Methods and Artificial Intelligence},
- year = 2023,
- month = mar,
- url = {https://www.merl.com/publications/TR2023-012}
- }
, - "Learning Control from Raw Position Measurements", arXiv, January 2023. ,
- "Inverse design of two-dimensional freeform metagrating using an adversarial conditional variational autoencoder", SPIE Photonics West, January 2023.BibTeX TR2023-004 PDF
- @inproceedings{Kojima2023jan,
- author = {Kojima, Keisuke and Koike-Akino, Toshiaki and Wang, Ye and Jung Minwoo and Brand, Matthew},
- title = {Inverse design of two-dimensional freeform metagrating using an adversarial conditional variational autoencoder},
- booktitle = {SPIE Photonics West},
- year = 2023,
- month = jan,
- url = {https://www.merl.com/publications/TR2023-004}
- }
, - "Model-Based Policy Search Using Monte Carlo Gradient Estimation with Real Systems Application", IEEE Transaction on Robotics, DOI: 10.1109/TRO.2022.3184837, Vol. 38, No. 6, pp. 3879-3898, December 2022.BibTeX TR2022-154 PDF
- @article{Romeres2022dec,
- author = {Amadio, Fabio and Dalla Libera, Alberto and Antonello, Riccardo and Nikovski, Daniel N. and Carli, Ruggero and Romeres, Diego},
- title = {Model-Based Policy Search Using Monte Carlo Gradient Estimation with Real Systems Application},
- journal = {IEEE Transaction on Robotics},
- year = 2022,
- volume = 38,
- number = 6,
- pages = {3879--3898},
- month = dec,
- doi = {10.1109/TRO.2022.3184837},
- issn = {1941-0468},
- url = {https://www.merl.com/publications/TR2022-154}
- }
, - "Induction Motor Eccentricity Fault Analysis and Quantification with Modified Winding Function based Model", International Conference on Electric Machines and Systems, DOI: 10.1109/ICEMS56177.2022.9983377, December 2022, pp. 1-6.BibTeX TR2022-153 PDF
- @inproceedings{Wang2022dec,
- author = {Wang, Bingnan and Albader, Mesaad and Inoue, Hiroshi and Kanemaru, Makoto},
- title = {Induction Motor Eccentricity Fault Analysis and Quantification with Modified Winding Function based Model},
- booktitle = {2022 25th International Conference on Electrical Machines and Systems (ICEMS)},
- year = 2022,
- pages = {1--6},
- month = dec,
- doi = {10.1109/ICEMS56177.2022.9983377},
- url = {https://www.merl.com/publications/TR2022-153}
- }
, - "Are Deep Neural Networks SMARTer than Second Graders?", arXiv, December 2022. ,
- "EVAL: Explainable Video Anomaly Localization", arXiv, December 2022. ,
- "Tackling the Cocktail Fork Problem for Separation and Transcription of Real-World Soundtracks", arXiv, December 2022.BibTeX arXiv
- @article{Petermann2022dec2,
- author = {Petermann, Darius and Wichern, Gordon and Subramanian, Aswin Shanmugam and Wang, Zhong-Qiu and Le Roux, Jonathan},
- title = {Tackling the Cocktail Fork Problem for Separation and Transcription of Real-World Soundtracks},
- journal = {arXiv},
- year = 2022,
- month = dec,
- url = {https://arxiv.org/abs/2212.07327}
- }
, - "Point Cloud Soft Multicast for Untethered XR Users", IEEE Transactions on Multimedia, December 2022.BibTeX TR2022-164 PDF
- @article{SoushiUeno;Fujihashi2022dec,
- author = {Soushi Ueno and Fujihashi, Takuya and Koike-Akino, Toshiaki and Watanabe, Takashi},
- title = {Point Cloud Soft Multicast for Untethered XR Users},
- journal = {IEEE Transactions on Multimedia},
- year = 2022,
- month = dec,
- url = {https://www.merl.com/publications/TR2022-164}
- }
, - "STFT-Domain Neural Speech Enhancement with Very Low Algorithmic Latency", IEEE/ACM Transactions on Audio, Speech, and Language Processing, December 2022.BibTeX TR2022-166 PDF
- @article{Wang2022dec2,
- author = {Wang, Zhong-Qiu and Wichern, Gordon and Watanabe, Shinji and Le Roux, Jonathan},
- title = {STFT-Domain Neural Speech Enhancement with Very Low Algorithmic Latency},
- journal = {IEEE/ACM Transactions on Audio, Speech, and Language Processing},
- year = 2022,
- month = dec,
- url = {https://www.merl.com/publications/TR2022-166}
- }
, - "Optimal Control of PDEs Using Physics-Informed Neural Networks", Advances in Neural Information Processing Systems (NeurIPS) workshop, December 2022.BibTeX TR2022-163 PDF
- @inproceedings{Mowlavi2022dec,
- author = {Mowlavi, Saviz and Nabi, Saleh},
- title = {Optimal Control of PDEs Using Physics-Informed Neural Networks},
- booktitle = {Advances in Neural Information Processing Systems (NeurIPS) workshop},
- year = 2022,
- month = dec,
- url = {https://www.merl.com/publications/TR2022-163}
- }
, - "Spatio-Temporal Thermal Monitoring for Lithium-Ion Batteries via Kriged Kalman Filtering", IEEE Conference on Decision and Control (CDC), DOI: 10.1109/CDC51059.2022.9992543, December 2022.BibTeX TR2022-162 PDF
- @inproceedings{Tu2022dec2,
- author = {Tu, Hao and Wang, Yebin and Li, Xianglin and Fang, Huazhen},
- title = {Spatio-Temporal Thermal Monitoring for Lithium-Ion Batteries via Kriged Kalman Filtering},
- booktitle = {IEEE Conference on Decision and Control (CDC)},
- year = 2022,
- month = dec,
- doi = {10.1109/CDC51059.2022.9992543},
- url = {https://www.merl.com/publications/TR2022-162}
- }
, - "Homogeneous Infeasible Interior Point Method for Convex Quadratic Programs", IEEE Conference on Decision and Control (CDC), DOI: 10.1109/CDC51059.2022.9992979, December 2022, pp. 7571-7578.BibTeX TR2022-157 PDF
- @inproceedings{Raghunathan2022dec,
- author = {Raghunathan, Arvind and Jha, Devesh K. and Romeres, Diego},
- title = {Homogeneous Infeasible Interior Point Method for Convex Quadratic Programs},
- booktitle = {IEEE 61st Conference on Decision and Control (CDC), Cancun, Mexico},
- year = 2022,
- pages = {7571--7578},
- month = dec,
- doi = {10.1109/CDC51059.2022.9992979},
- url = {https://www.merl.com/publications/TR2022-157}
- }
, - "Distributed Kalman Filtering: When to Share Measurements", IEEE Conference on Decision and Control (CDC), DOI: 10.1109/CDC51059.2022.9993404, December 2022, pp. 5399-5404.BibTeX TR2022-158 PDF
- @inproceedings{Greiff2022dec,
- author = {Greiff, Marcus and Berntorp, Karl},
- title = {Distributed Kalman Filtering: When to Share Measurements},
- booktitle = {IEEE Conference on Decision and Control (CDC)},
- year = 2022,
- pages = {5399--5404},
- month = dec,
- publisher = {IEEE},
- doi = {10.1109/CDC51059.2022.9993404},
- issn = {2576-2370},
- isbn = {978-1-6654-6761-2},
- url = {https://www.merl.com/publications/TR2022-158}
- }
, - "ODE Discretization Schemes as Optimization Algorithms", IEEE Conference on Decision and Control (CDC), December 2022.BibTeX TR2022-159 PDF
- @inproceedings{Romero2022dec,
- author = {Romero, Orlando and Benosman, Mouhacine and Pappas, Geroge},
- title = {ODE Discretization Schemes as Optimization Algorithms},
- booktitle = {IEEE Conference on Decision and Control (CDC)},
- year = 2022,
- month = dec,
- url = {https://www.merl.com/publications/TR2022-159}
- }
, - "Learning with noisy labels using low-dimensional model trajectory", NeurIPS 2022 Workshop on Distribution Shifts (DistShift), December 2022.BibTeX TR2022-156 PDF
- @inproceedings{Singla2022dec,
- author = {Singla, Vasu and Aeron, Shuchin and Koike-Akino, Toshiaki and Parsons, Kieran and Brand, Matthew and Wang, Ye},
- title = {Learning with noisy labels using low-dimensional model trajectory},
- booktitle = {NeurIPS 2022 Workshop on Distribution Shifts (DistShift)},
- year = 2022,
- month = dec,
- url = {https://www.merl.com/publications/TR2022-156}
- }
, - "Generalizable Human-Robot Collaborative Assembly Using Imitation Learning and Force Control", arXiv, December 2022.BibTeX arXiv
- @article{Jha2022dec,
- author = {Jha, Devesh K. and Jain, Siddarth and Romeres, Diego and Yerazunis, William S. and Nikovski, Daniel},
- title = {Generalizable Human-Robot Collaborative Assembly Using Imitation Learning and Force Control},
- journal = {arXiv},
- year = 2022,
- month = dec,
- url = {https://arxiv.org/abs/2212.01434}
- }
, - "Integrating Physics-Based Modeling with Machine Learning for Lithium-Ion Batteries", Applied Energy, DOI: 10.1016/j.apenergy.2022.120289, Vol. 329, December 2022.BibTeX TR2022-155 PDF
- @article{Tu2022dec,
- author = {Tu, Hao and Moura, Scott and Wang, Yebin and Fang, Huazhen},
- title = {Integrating Physics-Based Modeling with Machine Learning for Lithium-Ion Batteries},
- journal = {Applied Energy},
- year = 2022,
- volume = 329,
- month = dec,
- doi = {10.1016/j.apenergy.2022.120289},
- url = {https://www.merl.com/publications/TR2022-155}
- }
, - "Learning Occlusion-Aware Dense Correspondences for Multi-Modal Images", IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), November 2022.BibTeX TR2022-149 PDF
- @inproceedings{Shimoya2022nov,
- author = {Shimoya, Ryosuke and Morimoto, Tahashi and van Baar, Jeroen and Boufounos, Petros T. and Ma, Yanting and Mansour, Hassan},
- title = {Learning Occlusion-Aware Dense Correspondences for Multi-Modal Images},
- booktitle = {IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)},
- year = 2022,
- month = nov,
- url = {https://www.merl.com/publications/TR2022-149}
- }
, - "What Makes a “Good” Data Augmentation in Knowledge Distillation – A Statistical Perspective", Advances in Neural Information Processing Systems (NeurIPS), November 2022.BibTeX TR2022-147 PDF
- @inproceedings{Wang2022nov,
- author = {Wang, Huan and Lohit, Suhas and Jones, Michael J. and Fu, Raymond},
- title = {What Makes a “Good” Data Augmentation in Knowledge Distillation – A Statistical Perspective},
- booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
- year = 2022,
- month = nov,
- url = {https://www.merl.com/publications/TR2022-147}
- }
, - "Learning Partial Equivariances from Data", Advances in Neural Information Processing Systems (NeurIPS), November 2022.BibTeX TR2022-148 PDF Presentation
- @inproceedings{Romero2022nov,
- author = {Romero, David and Lohit, Suhas},
- title = {Learning Partial Equivariances from Data},
- booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
- year = 2022,
- month = nov,
- url = {https://www.merl.com/publications/TR2022-148}
- }
, - "Latent Iterative Refinement for Modular Source Separation", arXiv, November 2022.BibTeX arXiv
- @article{Bralios2022nov,
- author = {Bralios, Dimitrios and Tzinis, Efthymios and Wichern, Gordon and Smaragdis, Paris and Le Roux, Jonathan},
- title = {Latent Iterative Refinement for Modular Source Separation},
- journal = {arXiv},
- year = 2022,
- month = nov,
- url = {https://arxiv.org/abs/2211.11917}
- }
, - "Physics-Informed Koopman Network", arXiv, November 2022. ,
- "Dual Coding Concatenation for Burst-Error Correction in Probabilistic Amplitude Shaping", IEEE Journal of Lightwave Technology, DOI: 10.1109/JLT.2022.3178675, Vol. 40, No. 16, pp. 5502-5513, November 2022.BibTeX TR2022-145 PDF
- @article{Skvortcov2022nov,
- author = {Skvortcov, Pavel and Koike-Akino, Toshiaki and Millar, David S. and Kojima, Keisuke and Parsons, Kieran},
- title = {Dual Coding Concatenation for Burst-Error Correction in Probabilistic Amplitude Shaping},
- journal = {IEEE Journal of Lightwave Technology},
- year = 2022,
- volume = 40,
- number = 16,
- pages = {5502--5513},
- month = nov,
- doi = {10.1109/JLT.2022.3178675},
- issn = {1558-2213},
- url = {https://www.merl.com/publications/TR2022-145}
- }
, - "Optimal Condition Training for Target Source Separation", arXiv, November 2022. ,
- "Abort-Safe Spacecraft Rendezvous on Elliptic Orbits", IEEE Transactions on Control Systems Technology, November 2022.BibTeX TR2022-142 PDF
- @article{AguilarMarsillach2022nov,
- author = {Aguilar Marsillach, Daniel and Di Cairano, Stefano and Weiss, Avishai},
- title = {Abort-Safe Spacecraft Rendezvous on Elliptic Orbits},
- journal = {IEEE Transactions on Control Systems Technology},
- year = 2022,
- month = nov,
- url = {https://www.merl.com/publications/TR2022-142}
- }
, - "Cold Diffusion for Speech Enhancement", arXiv, November 2022. ,
- "Improving Adversarial Robustness by Learning Shared Information", Pattern Recognition, DOI: 10.1016/j.patcog.2022.109054, Vol. 134, pp. 109054, November 2022.BibTeX TR2022-141 PDF
- @article{Yu2022nov,
- author = {Yu, Xi and Smedemark-Margulies, Niklas and Aeron, Shuchin and Koike-Akino, Toshiaki and Moulin, Pierre and Brand, Matthew and Parsons, Kieran and Wang, Ye},
- title = {Improving Adversarial Robustness by Learning Shared Information},
- journal = {Pattern Recognition},
- year = 2022,
- volume = 134,
- pages = 109054,
- month = nov,
- doi = {10.1016/j.patcog.2022.109054},
- issn = {0031-3203},
- url = {https://www.merl.com/publications/TR2022-141}
- }
, - "Learning Audio-Visual Dynamics Using Scene Graphs for Audio Source Separation", Advances in Neural Information Processing Systems (NeurIPS), November 2022.BibTeX TR2022-140 PDF
- @inproceedings{Chatterjee2022nov,
- author = {Chatterjee, Moitreya and Ahuja, Narendra and Cherian, Anoop},
- title = {Learning Audio-Visual Dynamics Using Scene Graphs for Audio Source Separation},
- booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
- year = 2022,
- month = nov,
- url = {https://www.merl.com/publications/TR2022-140}
- }
, - "Active Exploration for Robotic Manipulation", IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2022.BibTeX TR2022-139 PDF
- @inproceedings{Schneider2022oct,
- author = {Schneider, Tim and Belousov, Boris and Chalvatzaki, Georgia and Romeres, Diego and Jha, Devesh K. and Peters, Jan},
- title = {Active Exploration for Robotic Manipulation},
- booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
- year = 2022,
- month = oct,
- url = {https://www.merl.com/publications/TR2022-139}
- }
, - "Optimal control of PDEs using physics-informed neural networks", Journal of Computational Physics, October 2022.BibTeX TR2022-143 PDF
- @article{Mowlavi2022oct,
- author = {Mowlavi, Saviz and Nabi, Saleh},
- title = {Optimal control of PDEs using physics-informed neural networks},
- journal = {Journal of Computational Physics},
- year = 2022,
- month = oct,
- url = {https://www.merl.com/publications/TR2022-143}
- }
, - "Smart Actuation for End-Edge Industrial Control Systems", IEEE Transactions on Automation Science and Engineering, DOI: 10.1109/TASE.2022.3216217, October 2022.BibTeX TR2022-138 PDF
- @article{Ma2022oct,
- author = {Ma, Yehan and Wang, Yebin and Di Cairano, Stefano and Koike-Akino, Toshiaki and Guo, Jianlin and Orlik, Philip V. and Guan, Xinping and Lu, Chenyang},
- title = {Smart Actuation for End-Edge Industrial Control Systems},
- journal = {IEEE Transactions on Automation Science and Engineering},
- year = 2022,
- month = oct,
- doi = {10.1109/TASE.2022.3216217},
- url = {https://www.merl.com/publications/TR2022-138}
- }
, - "Cross-Modal Knowledge Transfer Without Task-Relevant Source Data", European Conference on Computer Vision (ECCV), Avidan, S and Brostow, G and Cisse M and Farinella, G.M. and Hassner T., Eds., DOI: 10.1007/978-3-031-19830-4_7, October 2022, pp. 111-127.BibTeX TR2022-135 PDF Video Software Presentation
- @inproceedings{Ahmed2022oct,
- author = {Ahmed, Sk Miraj and Lohit, Suhas and Peng, Kuan-Chuan and Jones, Michael J. and Roy Chowdhury, Amit K},
- title = {Cross-Modal Knowledge Transfer Without Task-Relevant Source Data},
- booktitle = {Computer Vision--ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23--27, 2022, Proceedings, Part XXXIV},
- year = 2022,
- editor = {Avidan, S and Brostow, G and Cisse M and Farinella, G.M. and Hassner T.},
- pages = {111--127},
- month = oct,
- publisher = {Springer},
- doi = {10.1007/978-3-031-19830-4_7},
- isbn = {978-3-031-19830-4},
- url = {https://www.merl.com/publications/TR2022-135}
- }
, - "Incomplete Multi-view Domain Adaptation via Channel Enhancement and Knowledge Transfer", European Conference on Computer Vision (ECCV), DOI: 10.1007/978-3-031-19830-4_12, October 2022.BibTeX TR2022-134 PDF
- @inproceedings{Xia2022oct,
- author = {Xia, Haifeng and Wang, Pu and Ding, Zhengming},
- title = {Incomplete Multi-view Domain Adaptation via Channel Enhancement and Knowledge Transfer},
- booktitle = {European Conference on Computer Vision (ECCV)},
- year = 2022,
- month = oct,
- doi = {10.1007/978-3-031-19830-4_12},
- isbn = {978-3-031-19830-4},
- url = {https://www.merl.com/publications/TR2022-134}
- }
, - "Distributed Radar Autofocus Imaging Using Deep Priors", IEEE International Conference on Image Processing (ICIP), October 2022.BibTeX TR2022-129 PDF Video
- @inproceedings{Mansour2022oct,
- author = {Mansour, Hassan and Lohit, Suhas and Boufounos, Petros T.},
- title = {Distributed Radar Autofocus Imaging Using Deep Priors},
- booktitle = {IEEE International Conference on Image Processing (ICIP)},
- year = 2022,
- month = oct,
- url = {https://www.merl.com/publications/TR2022-129}
- }
, - "quEEGNet: Quantum AI for Biosignal Processing", IEEE Conference on Biomedical and Health Informatics (BHI), DOI: 10.1109/BHI56158.2022.9926814, September 2022.BibTeX TR2022-121 PDF Video Presentation
- @inproceedings{Koike-Akino2022sep,
- author = {Koike-Akino, Toshiaki and Wang, Ye},
- title = {quEEGNet: Quantum AI for Biosignal Processing},
- booktitle = {IEEE Conference on Biomedical and Health Informatics (BHI)},
- year = 2022,
- month = sep,
- publisher = {IEEE},
- doi = {10.1109/BHI56158.2022.9926814},
- issn = {2641-3604},
- isbn = {978-1-6654-8791-7},
- url = {https://www.merl.com/publications/TR2022-121}
- }
, - "Context-Aware Destination and Time-To-Destination Prediction Using Machine Learning", IEEE International Smart Cities Conference, DOI: 10.1109/ISC255366.2022.9922593, September 2022.BibTeX TR2022-120 PDF
- @inproceedings{Tsiligkaridis2022sep,
- author = {Tsiligkaridis, Athanasios and Zhang, Jing and Paschalidis, Ioannis Ch. and Taguchi, Hiroshi and Sakajo, Satoko and Nikovski, Daniel N.},
- title = {Context-Aware Destination and Time-To-Destination Prediction Using Machine Learning},
- booktitle = {IEEE International Smart Cities Conference},
- year = 2022,
- month = sep,
- doi = {10.1109/ISC255366.2022.9922593},
- url = {https://www.merl.com/publications/TR2022-120}
- }
,
- "Travel-time prediction using neural-network-based mixture models", International Workshop on Statistical Methods and Artificial Intelligence, March 2023.