Calendar of Events
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RI Event
Wen-Tse Chen
Towards Efficient Multi-Agent and Temporal Credit Assignment in Reinforcement Learning
Abstract: This thesis tackles the core challenge of credit assignment in reinforcement learning (RL), where agents must determine which actions or agents deserve credit for outcomes in complex environments. Traditional RL struggles when rewards are sparse, delayed, or shared among multiple agents, as is common in real-world tasks like robotics or game AI. To address […]
PhD Thesis Proposal
Cornelia Bauer
Embracing Contact: Leveraging Physical Interactions for Enhanced Robotic Control
Abstract: As robotic systems become increasingly capable and commercially available, particularly in the form of humanoids and dexterous hands, enabling them to physically interact with their environment remains a fundamental challenge. Humans effortlessly use contact with their surroundings to perform agile movements and manipulate both delicate and heavy objects. For robots, in contrast, effectively leveraging […]
MSR Thesis Defense
Zhouchonghao Wu
Towards Off-road Autonomous Driving via Teacher Action Distillation Policy Optimization
Abstract: Off-road autonomous driving poses significant challenges such as navigating unmapped, variable terrain with uncertain and diverse dynamics. Addressing these challenges requires effective long-horizon planning and adaptable control. Model Predictive Control (MPC) methods rely on dense sampling and accurate dynamics models, making them computationally expensive and unsuitable for real-time long-horizon planning. In contrast, Reinforcement Learning […]
MSR Thesis Defense
Xiaohan Liu
From Object Pushing to Self Pushing: Whole-Body Control for Ballbots
Abstract: Dynamically stable mobile robots, like ballbots, are agile but highly sensitive to manipulator-induced disturbances. This feature makes loco-manipulation of dynamically stable mobile robots a tightly coupled whole-body control problem. This thesis investigates how manipulators can be leveraged not only for interacting with objects, but also for locomotion. First, we investigate effective wheelchair maneuvering using […]
2 events,
PhD Thesis Defense
Charles Noren
Towards Robotic Convoying in Unstructured Environments
Abstract: Multi-agent robotic teaming is the only realistic solution to many large-scale autonomous operations. Conventionally, operations are modeled as a set of tasks that are largely decoupled from each other and the environment at execution time. However, this operational model fails when the successful execution of a task requires multiple agents to synchronize their actions […]
PhD Thesis Defense
Kangle Deng
Learning to Create 3D Content
Abstract: With the popularity of Virtual Reality (VR), Augmented Reality (AR), and other 3D applications, developing methods that let everyday users capture and create their own 3D content has become increasingly essential. However, current 3D creation pipelines often require either tedious manual effort or specialized capture setups. Additionally, resulting assets often suffer from baked-in lighting, […]
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1 event,
PhD Thesis Defense
Katherine Shih
Learning From People: Assistive Robotics and Optimization from Preferences
Abstract: Robotic algorithms rarely come perfectly pre-configured, and when choosing parameters, tradeoffs must often be made: between performance and robustness; efficiency and safety; the comfort of the user and the comfort of bystanders. While engineers can tune parameters by hand or carefully design reward functions to optimize over, this is not always a straightforward task. […]
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MSR Thesis Defense
Nader Zantout
Towards Practical Vision-and-Language Navigation Systems Through 3D Referential Grounding
Abstract: As robots transition toward practical deployment as collaborative agents in human environments, it becomes essential to improve language-conditioned environmental understanding. A vision-and-language navigation (VLN) system must adapt to both the types of language used and the actions expected by a human collaborator. Often, a single sentence containing spatial relations and semantic attributes---e.g., “fetch the […]
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3 events,
MSR Thesis Defense
Eric Cai
Object-Centric Goal Prediction Towards Precise, Generalizable Placement
Abstract: Recent advances in robotic manipulation have established the effectiveness of learning from demonstration. However, while end-to-end policies excel in expressivity and flexibility for complex skill learning, they struggle to efficiently adapt to task variations in geometry and configuration. Conversely, alternative approaches relying on object-centric goal prediction offer improved generalizability, but rely on restrictive assumptions […]
PhD Thesis Defense
Akhil Padmanabha
Advancing Multimodal Sensing and Robotic Interfaces for Chronic Care
Abstract: The healthcare system prioritizes reactive care for acute illnesses, often overlooking the ongoing needs of individuals with chronic conditions that require long-term management and personalized care. Addressing this gap through technology can empower patients to better manage their conditions, greatly enhancing quality of life and independence. Multimodal sensing, incorporating inertial, acoustic, and vision-based sensors, […]
MSR Thesis Defense
Peya Mowar
Towards Automating Accessibility in Digital Authoring Workflows
Abstract: Most digital content today remains inaccessible to people with disabilities, who make up 16% of the global population. A long-standing challenge in accessible computing is ensuring digital authors consistently provide the metadata required to make their content accessible through assistive technologies. Despite numerous specialized accessibility tools, authors often lack the time, training, or incentive […]
1 event,
PhD Thesis Defense
Jinkun Cao
Vision-based Human Motion Modeling and Analysis
Abstract: Modern computer vision has achieved remarkable success in tasks such as detecting, segmenting, and estimating human pose in images and videos—often reaching or even surpassing human-level performance. However, significant challenges remain in predicting and analyzing future human motion. This thesis explores how vision-based methods can improve the fidelity and accuracy of human motion modeling […]
1 event,
MSR Thesis Defense
Anurag Bagchi
ReferEverything: Towards Segmenting Everything We Can Speak of in Videos Using Text-to-Video Diffusion Models
Abstract: In this thesis we present REM, a framework for segmenting a wide range of concepts in video that can be described through natural language. Our method unlocks the universal visual-language mapping learned by video diffusion models on Internet-scale data by fine-tuning them on small-scale Referring Object Segmentation datasets. Our key insight is preserving the […]
1 event,
PhD Thesis Defense
Montiel Abello
Building richer 3D maps: utilizing a hybrid geometry representation and auxiliary inputs in neural surface reconstruction
Abstract: As robots are increasingly deployed in real-world environments, their perception systems face growing demands. Tasks such as tracking and manipulation require maps with both high spatial fidelity and detailed object-level organization, which must be delivered faster to support timely decision-making and control. Concurrently, advances in vision foundation models allow us to build powerful prediction […]
2 events,
MSR Thesis Defense
Mayank Mishra
A Robotic Disaster Response System for Autonomous Inspection, Respiration Rate Estimation, and Amputation Detection of Casualties
Abstract: In mass casualty situations, quickly identifying and prioritizing injuries can be the difference between life and death. Traditional triage systems rely heavily on trained human responders, but in complex or hazardous environments, human access may be delayed or limited. Robotic systems offer a promising solution to this problem by enabling remote, scalable, and fast […]
PhD Thesis Defense
Vidhi Jain
Lowering Barriers in Human-Robot Communication
Abstract: For robots to collaborate naturally in homes, they must interpret diverse forms of human expression - visual gestures, natural language instructions, environmental context - and translate them into actions. Existing robot policies typically rely on structured language goals and static visual observations, which restricts both the sensory context and the ways users can specify […]
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4 events,
PhD Thesis Proposal
Anoop Bhat
Traveling Salesman Problems with Moving Targets and Obstacles
Abstract: The moving target traveling salesman problem with obstacles (MT-TSP-O) seeks a trajectory for an agent that intercepts several moving targets within a particular time window for each target, all while avoiding stationary obstacles. The MT-TSP-O combines the combinatorial challenges of the standard TSP with the continuous decision over when and where to intercept each […]
MSR Thesis Defense
Xintong Duan
Towards fast and generalizable decision making with diffusion models
Abstract: Many real-world decision-making problems are combinatorial in nature, where states can be seen as a combination of basic elements. Due to combinatorial complexity, observing all combinations of basic elements in the training set is infeasible, which leads to an essential yet understudied problem of zero-shot generalization to states that are unseen combinations of previously […]
MSR Thesis Defense
Aditti Ramsisaria
A Conformable Linear Electrode Platform for Impedance Mapping of Soft Tissue Interfaces
Abstract: Soft electrode arrays capable of conforming to complex anatomical surfaces are vital for emerging biomedical sensing technologies. They are particularly relevant in applications requiring large-area, high-resolution mapping. Reducing the time required for such mapping is critical to minimize overall procedure duration and improve clinical efficiency. However, the electrical performance of such systems under mechanical […]
PhD Speaking Qualifier
Yizhou Huang
Multi-level reasoning for versatile multi-robot assembly
Abstract: Robotic assembly is a critical category of tasks in modern manufacturing. Compared to a single-robot workstation, a multi-robot system offers several advantages: 1) it expands the system's workspace, 2) improves task efficiency, and, more importantly, 3) enables robots to achieve significantly more complex and dexterous tasks, such as cooperative assembly. However, effectively coordinating the […]
1 event,
MSR Thesis Defense
Yogita Choudhary
Enhancing Safety and Performance in Multi-agent Systems and Soft Robots via Reinforcement Learning
Abstract: With the growing deployment of robots across various safety-critical applications, ensuring safety has become increasingly essential to prevent accidents and enhance reliability. Addressing safety in robotic systems presents several inherent challenges. Firstly, in multi-agent settings, incorporating safety filters can adversely impact overall task performance, as agents must simultaneously ensure collision avoidance and timely task completion. To […]
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2 events,
MSR Thesis Defense
Vedant Mundheda
Off-road Autonomous Driving via Guided Reinforcement Learning
Abstract: Off-road autonomous driving presents a complex set of challenges, including navigation through unmapped environments, variable terrain geometries, and uncertain, non-stationary dynamics. These conditions demand planning and control strategies that are both long-horizon and adaptable. Traditional Model Predictive Control (MPC) methods rely on dense sampling and precise dynamics modeling, which limits their feasibility for real-time […]
MSR Thesis Defense
Jeff Tan
Dynamic and Large-Scale 3D Reconstruction via Feedforward Priors
Abstract: Methods for 3D reconstruction from images or videos typically fall into two categories: 1) scene-specific test-time optimization (often via differentiable rendering) and 2) large-scale data-driven priors (often in the form of feedforward neural networks). This thesis presents two works that combine both paradigms for dynamic and large-scale 3D reconstruction from casual images and videos. […]
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1 event,
PhD Thesis Proposal
Jeong Hun Lee
Just Keep Swimming: Towards Bio-Inspired Robotic Swimming
Abstract: Fish demonstrate an efficient and agile swimming modality that allows them to navigate complex fluid environments with ease. This has been attributed to complex, intricate flow interactions with the surrounding fluid. However, underwater robots have yet to realize the same performance as their biological counterparts. This thesis addresses some of the challenges behind achieving […]