Ruizhe joined MSEAS in fall 2023 as an SM student. His current research is on modeling submesoscale physics and dynamics in the ocean. Prior to joining MIT, Ruizhe received his Bachelor’s with Honors in Theoretical and Applied Mechanics from Peking University, China. Apart from academia, he loves movies, hiking, and going to the gym to run and lift weights.

After recently finishing my undergraduate studies at MIT in both course 6-2 and course 18, I joined MSEAS as an MEng student in the Summer of 2022. My current research is on data-driven methods for reduced order modelling and data assimilation. Outside of the lab, I love going on runs, playing guitar, and listening to music!

Upon completing his undergraduate studies in Canada, Manmeet started his Master’s in Mechanical Engineering at MIT in Fall 2018. His principal research focus is on high-order numerical methods for underwater acoustic modelling and simulation. In his free time, he enjoys following and playing soccer and basketball. The picture shown here is from what is known as the Iron Ring ceremony, a customary service in Canadian engineering programs. In this ceremony, graduating students are given an Iron Ring (traditionally worn on the pinky finger) as a constant reminder to remain humble and to always live by a high standard of professional conduct. He is currently working on:

• Precision Ocean Interrogation, Navigation, and Timing (POINT) POSYDON-MIT

I joined MSEAS in the summer of 2020 as a SM student in Computational Science & Engineering (CSE). I completed my Bachelor’s in Aerospace Engineering at Delft University of Technology in the Netherlands. My current research is on data-driven reduced order modelling methods. Outside of academics, I enjoy soccer and the short bike rides to and from places.

Chinmay is a graduate student pursuing a doctorate in Mechanical Engineering. His current work involves the development of intelligent machines and methods to learn and predict the transport of oceanic pollutants (debris and nutrients on a global scale. He spent four wonderful years at IIT Bombay, India from 2011 until 2017 and received a Master’s in Mechanical Engineering from MIT in 2017. Beyond research, he is also an enthusiastic pilot who is always willing to explore beauty of New England. His other hobbies include endurance biking and playing the drums. He is currently working on:

• Advanced Lagrangian Predictions for Hazards Assessments (NSF-ALPHA)
• Red Sea Initiative
• Digging Deep: An integrated approach for assessing the impacts of deep-sea mining
• Long-duration Environmentally-adaptive Autonomous Rigorous Naval Systems (LEARNS)
• Northern Arabian Sea Circulation – autonomous research: Optimal Planning Systems (NASCar-OPS)

His publications so far include:

• Kulkarni, C.S., P.J. Haley, Jr., P. F. J. Lermusiaux, A. Dutt, A. Gupta, C. Mirabito, D.N. Subramani, S. Jana, W.H. Ali, T. Peacock, C.M. Royo, A. Rzeznik, and R. Supekar, 2018. Real-Time Sediment Plume Modeling in the Southern California Bight. In: Oceans ’18 MTS/IEEE Charleston, 22-25 October 2018.
• Dutt, A., D.N. Subramani, C.S. Kulkarni, and P. F. J. Lermusiaux, 2018. Clustering of Massive Ensemble of Vehicle Trajectories in Strong, Dynamic and Uncertain Ocean Flows. In: Oceans ’18 MTS/IEEE Charleston, 22-25 October 2018.
• Ferris, D.L., D.N. Subramani, C.S. Kulkarni, P.J. Haley, and P.F.J. Lermusiaux, 2018. Time-Optimal Multi-Waypoint Mission Planning in Dynamic Environments. In: Oceans ’18 MTS/IEEE Charleston, 22-25 October 2018.
• Coulin, J., P. J. Haley, Jr., S. Jana, C.S. Kulkarni, P. F. J. Lermusiaux, T. Peacock, 2017. Environmental Ocean and Plume Modeling for Deep Sea Mining in the Bismarck Sea. In: Oceans ’17 MTS/IEEE Anchorage, 1-10, 18-21 September 2017.
• Lermusiaux, P.F.J., P.J. Haley Jr., S. Jana, A. Gupta, C.S. Kulkarni, C. Mirabito, W.H. Ali, D.N. Subramani, A. Dutt, J. Lin, A. Y. Shcherbina, C. M. Lee, and A. Gangopadhyay, 2017. Optimal Planning and Sampling Predictions for Autonomous and Lagrangian Platforms and Sensors in the Northern Arabian Sea. Oceanography 30(2):172–185, https://doi.org/10.5670/oceanog.2017.242.
• Lermusiaux, P.F.J., D.N. Subramani, J. Lin, C.S. Kulkarni, A. Gupta, A. Dutt, T. Lolla, P.J. Haley Jr., W.H. Ali, C. Mirabito, and S. Jana, 2017. A Future for Intelligent Autonomous Ocean Observing Systems. The Sea. Volume 17, The Science of Ocean Prediction, Part 2, J. Marine Res. 75(6), pp. 765–813. https://doi.org/10.1357/002224017823524035
• Edwards, J., J. Smith, A. Girard, D. Wickman, P.F.J. Lermusiaux, D.N. Subramani, P.J. Haley, Jr., C. Mirabito, C.S. Kulkarni, and, S. Jana, 2017. Data-driven Learning and Modeling of AUV Operational Characteristics for Optimal Path Planning. In: Oceans ’17 MTS/IEEE Aberdeen, 1-5, 19-22 June 2017, DOI: 10.1109/OCEANSE.2017.8084779
• Subramani, D. N., P. F. J. Lermusiaux, P.J. Haley, Jr., C. Mirabito, S. Jana, C. S. Kulkarni, A. Girard, D. Wickman, J. Edwards, J. Smith, 2017. Time-Optimal Path Planning: Real-Time Sea Exercises. In: Oceans ’17 MTS/IEEE Aberdeen, 1-10, 19-22 June 2017, DOI: 10.1109/OCEANSE.2017.8084776

I joined MSEAS as an SM MechE candidate in the Fall of 2020. My research broadly spans the areas of Bayesian Inference and Machine Learning for oceanic dynamical systems. Prior to joining MIT, I completed my Bachelor’s in Mechanical Engineering and Master’s in Data Sciences at IIT Madras, India. During my 5 wonderful undergraduate years, I had the good fortune of doing research in both academic and industrial settings. For my undergraduate thesis, I worked on augmenting a popular causal inference technique to identify causal climatic dependencies from spatial-temporal data. On the industrial front, my experiences run the gamut from cutting losses for an early-stage food-delivery startup to researching quantitative trading strategies for a hedge fund. Outside of research, I am an avid non-fiction reader (recently started foraying into fiction), a mediocre tennis player and travel enthusiast.

I joined MSEAS in the fall of 2020, pursuing a Masters in Ocean Engineering (SMOE). I am currently an active duty officer in the US Coast Guard, specializing in engineering. I received my Bachelor’s degree in Civil Engineering from the US Coast Guard Academy in Connecticut, where I focused on coastal engineering and stormwater systems. Before MIT I served two tours in Honolulu, HI, as a Naval Engineer-in-Training on Coast Guard ships that patrolled the Pacific Ocean from the Galapagos to the Arctic Circle. I love the ocean and enjoy surfing, free diving, sailing, and paddleboarding.

Zach is a graduate student in the MIT-WHOI Joint Program for Applied Ocean Science and Engineering. He received his Bachelor’s degree in Aeronautics and Astronautics at MIT in June 2018. With MSEAS, Zach’s research focused on the intersection of numerical ocean modeling and the guidance of autonomous vehicles. Aside from research, Zach enjoys staying active by cycling, skiing, and playing basketball. As an undergraduate, he played varsity football for four years as a linebacker and defensive back.​

Jacob is an MIT/WHOI joint program student who has been in the US Navy for 15 years having served on submarines, destroyers, and aircraft carriers. He completed his Bachelor of Science at Purdue University in Atmospheric Science. His areas of interest are reduced-order models. In his time outside of studies, he enjoys spending as much time with his wife and son as possible traveling throughout the US and abroad.

Aaron joined MSEAS in the fall of 2019, starting his masters in Computational Science & Engineering (CSE) with plans to pursue a PhD in MechE-CSE. Broadly, his interests span stochastic differential equations and signal processing. He has begun focusing on numerical solutions to the acoustic wave equation in the presence of uncertainty in addition to Bayesian inference for acoustic inverse problems (see DEEP-AI). Furthermore, he works on developing and improving reduced-order modeling techniques by incorporating differential geometry for applications in uncertainty quantification. Before coming to MIT, Aaron graduated with a Bachelor of Science from Brown University, double concentrating in applied mathematics and engineering, where he researched terahertz optics phenomena. Outside of academia, he enjoys running, water skiing, hiking, and low-level soccer.

Aditya completed his Bachelor’s in Mechanical Engineering at R.V. College of Engineering, Bangalore (2017) before moving to Purdue University to pursue his M.S in the same field. Upon graduating from Purdue in 2019, he joined MIT to pursue his Ph.D. in Mechanical Engineering. His previous work at Purdue focused on the development of numerical tools for investigating the self-similar propagation of low-Reynolds number gravity currents for geophysical applications. Presently his research interests lie in the areas of numerical methods and high-performance computing. Beyond research, Aditya enjoys reading, trekking, cycling, and would like to get involved in activities such as sailing, kayaking, and rowing.

Coming from Greece, Akis started his Master’s in Mechanical Engineering at MIT in Fall 2018. The focus of his research is in stochastics and more specifically uncertainty quantification and reduced-order ocean modelling using the Dynamically Orthogonal Primitive Equations framework of MSEAS. In his free time, he enjoys sailing, a sport in which he believes he can put his knowledge from ocean modelling into practice. He is currently working on:

• Coherent Lagrangian Pathways from the Surface Ocean to Interior (CALYPSO)
• Understanding and Predicting the Gulf of Mexico Loop Current

Manan joined the lab in Fall 2018. He is pursuing his Master’s in Computation for Design and Optimisation(CDO). His research interests include primarily include higher order methods (specifically, HDG). He is currently working on:

• Coherent Lagrangian Pathways from the Surface Ocean to Interior (CALYPSO)

I am an active duty Naval submarine officer with over 12 years of service. 1st year MIT-WHOI Joint Program student interested in machine learning applications to modeling and simulation. Proud father of Michael and Isla Humara and husband to Brianne Humara.

Abhinav is a PhD candidate in Mechanical Engineering, and also a fellow of the Tata Center for Technology and Design at MIT . He received his Bachelor’s degree and Master’s degree in the same field from the Indian Institute of Technology, Kanpur. He was a recipient of the S.N. Bose Scholarship, offered to select undergraduates to perform research in the United States. Pursuant to the scholarship and a follow-up internship, he worked in the MSEAS lab itself for two consecutive summers. Abhinav is currently working on developing state-of-the-art, uncertainty quantification, data assimilation and optimal sampling methods. Apart from research, his hobbies include playing badminton, and cooking Indian food. He is currently working on:

• Coastal forecasting for a sustainable fisheries management system in India

His publications so far include:

• Lermusiaux, P.F.J., D.N. Subramani, J. Lin, C.S. Kulkarni, A. Gupta, A. Dutt, T. Lolla, P.J. Haley Jr., W.H. Ali, C. Mirabito, and S. Jana, 2017. A Future for Intelligent Autonomous Ocean Observing Systems. The Sea. Volume 17, The Science of Ocean Prediction, Part 2, J. Marine Res. 75(6), pp. 765–813. https://doi.org/10.1357/002224017823524035
• Lermusiaux, P.F.J., P.J. Haley Jr., S. Jana, A. Gupta, C.S. Kulkarni, C. Mirabito, W.H. Ali, D.N. Subramani, A. Dutt, J. Lin, A. Y. Shcherbina, C. M. Lee, and A. Gangopadhyay, 2017. Optimal Planning and Sampling Predictions for Autonomous and Lagrangian Platforms and Sensors in the Northern Arabian Sea. Oceanography 30(2):172–185, https://doi.org/10.5670/oceanog.2017.242.

Wael is a third-year graduate student in the MechE-CSE PhD program. His research interests span the fields of computational engineering, uncertainty quantification and data assimilation. His current work focuses on the efficient modeling of ocean acoustic waves propagation and signal tomography in the presence of environmental uncertainties, with the goal of using these tools to develop an underwater GPS system. Before joining MIT, Wael spent four fruitful years at the American University of Beirut (AUB), where he had the opportunity to refine his interests in the history and archaeology of Lebanon and the Middle East. He is currently working on:

• Surface Dynamic Uncertainty Characterization and Transfer (S-DUCT)
• Precision Ocean Interrogation, Navigation, and Timing (POINT) POSYDON-MIT
• Red Sea Initiative

His publications so far include:

• Kulkarni, C.S., P.J. Haley, Jr., P. F. J. Lermusiaux, A. Dutt, A. Gupta, C. Mirabito, D.N. Subramani, S. Jana, W.H. Ali, T. Peacock, C.M. Royo, A. Rzeznik, and R. Supekar, 2018. Real-Time Sediment Plume Modeling in the Southern California Bight. In: Oceans ’18 MTS/IEEE Charleston, 22-25 October 2018.
• Lermusiaux, P.F.J., P.J. Haley Jr., S. Jana, A. Gupta, C.S. Kulkarni, C. Mirabito, W.H. Ali, D.N. Subramani, A. Dutt, J. Lin, A. Y. Shcherbina, C. M. Lee, and A. Gangopadhyay, 2017. Optimal Planning and Sampling Predictions for Autonomous and Lagrangian Platforms and Sensors in the Northern Arabian Sea. Oceanography 30(2):172–185, https://doi.org/10.5670/oceanog.2017.242.
• Lermusiaux, P.F.J., D.N. Subramani, J. Lin, C.S. Kulkarni, A. Gupta, A. Dutt, T. Lolla, P.J. Haley Jr., W.H. Ali, C. Mirabito, and S. Jana, 2017. A Future for Intelligent Autonomous Ocean Observing Systems. The Sea. Volume 17, The Science of Ocean Prediction, Part 2, J. Marine Res. 75(6), pp. 765–813. https://doi.org/10.1357/002224017823524035

My research is related to the development of hybridizable discontinuous Galerkin (HDG) methods for use in large-scale computational fluid dynamics software and ocean modeling. I am also generally interested in numerical methods, stochastic modeling, visualization, and high performance computing. I’ve spent most of my life in the greater Boston metro region and the San Francisco bay area, where I received my Bachelor’s degree in Engineering Physics from Stanford. When not searching for the solutions to life’s mysteries in discontinuous polynomial spaces, I’m an avid kickboxer, swimmer, and classical pianist. I am currently working on:

• High-Order Multi-Resolution Multi-Dynamics Modeling for the Flow Encountering Abrupt Topography (FLEAT) Initiative
• Seamless Multiscale Forecasting: Hybridizable Unstructured-mesh Modeling and Conservative Two-way Nesting

His publications so far include:

• Foucart, C., C. Mirabito, P. J. Haley, Jr., and P. F. J. Lermusiaux, 2018. Distributed Implementation and Verification of Hybridizable Discontinuous Galerkin Methods for Nonhydrostatic Ocean Processes. In: Oceans ’18 MTS/IEEE Charleston, 22-25 October 2018.
• Deluca, S., B. Rocchio, C. Foucart, C. Mirabito, S. Zanforlin, P.J. Haley, and P.F.J. Lermusiaux, 2018. Scalable Coupled Ocean and Water Turbine Modeling for Assessing Ocean Energy Extraction. In: Oceans ’18 MTS/IEEE Charleston, 22-25 October 2018. doi:10.1109/oceans.2018.8604646
• Foucart, C., 2019. Efficient Matrix-Free Implementation and Automated Verification of Hybridizable Discontinuous Galerkin Finite Element Methods. SM Thesis, Massachusetts Institute of Technology, Mechanical Engineering, June 2019.

Jing came from China to MIT for his Ph.D. in Mechanical Engineering and Computation in Fall 2012. He is interested in uncertainty quantification, data assimilation and Bayesian inference for nonlinear dynamical systems, including applications in fluid flows governed by the unsteady incompressible Navier-Stokes equations. He is currently working on:

• Active Transfer Learning (ATL) for Ocean Modeling
• Long-duration Environmentally-adaptive Autonomous Rigorous Naval Systems (LEARNS)

His publications so far include:

• Aoussou, J., J. Lin and P.F.J. Lermusiaux, 2018. Iterated Pressure-Correction Projection Methods for the Unsteady Incompressible Navier-Stokes Equations. Journal of Computational Physics, DOI: 10.1016/j.jcp.2018.06.062