VASC Seminar
Francesc Moreno Noguer
Associate Researcher
Institut de Robotica i Informatica Industrial (Barcelona, Spain)

Geometric Deep Learning for Perceiving and Modeling Humans

GHC 6501

Abstract: Perceiving and modeling shape and appearance of the human body from single images is a severely under-constrained problem that not only requires large volumes of data, but also prior knowledge.  In this talk I will present recent solutions on how deep learning can leverage on geometric reasoning to address tasks like 3D estimation of [...]

PhD Thesis Defense
Robotics Institute,
Carnegie Mellon University

Forecasting and Controlling Behavior by Learning from Visual Data

NSH 4305

Abstract: Achieving a precise predictive understanding of the future is difficult, yet widely studied in the natural sciences. Significant research activity has been dedicated to building testable models of cause and effect. From a certain view, a perfect predictive model of the universe is the “holy grail”; the ultimate goal of science. If we had [...]

VASC Seminar
Wenshuo Wang
Postdoctoral Research Associate
Safe AI Lab, Carnegie Mellon University

Human-Level Learning of Driving Primitives through Bayesian Nonparametric Statistics

Gates-Hillman Center 8102

Abstract: Understanding and imitating human driver behavior has benefited for autonomous driving in terms of perception, control, and decision-making. However, the complexity of multi-vehicle interaction behavior is far messier than human beings can cope with because of the limited prior knowledge and capability of dealing with high-dimensional and large-scale sequential data. In this talk, I [...]

Special Events
U.A. and Helen Whitaker Professor of Robotics
Robotics Institute,
Carnegie Mellon University

Town Hall with RI Director and RI Graduate Students

Rashid Auditorium 4401

Dr. Srinivasa Narasimhan, the Interim Director of The Robotics Institute, would like to meet all of RI’s graduate students.  Please join him for a Town Hall meeting at 1pm in Rashid Auditorium on Friday Aug 30!

RI Seminar
Ross Knepper
Assistant Professor
Department of Computer Science, Cornell University

Formalizing Teamwork in Human-Robot Interaction

Gates Hillman Center 6115

Abstract: Robots out in the world today work for people but not with people. Before robots can work closely with ordinary people as part of a human-robot team in a home or office setting, robots need the ability to acquire a new mix of functional and social skills. Working with people requires a shared understanding [...]

VASC Seminar
Hironobu Fujiyoshi
Professor
Chubu University (Japan)

Knowledge Transfer Graph for Deep Collaborative Learning

3305 Newell-Simon Hall

Abstract:  In this talk I will present our latest research about knowledge transfer graph for Deep Collaborative Learning (DCL), which is a method that incorporates Knowledge Distillation and Deep Mutual Learning. DCL is represented by a directional graph where each model is represented by a node, and the propagation of knowledge from the source node to the [...]

Field Robotics Center Seminar
Steve Chien and Jagriti Agrawal
Senior Research Scientist and Technical Staff
Jet Propulsion Laboratory, California Institute of Technology

AI in Space – From Earth Orbit to Mars and Beyond!

3305 Newell-Simon Hall

Abstract: Artificial Intelligence is playing an increasing role in our everyday lives and the business marketplace. This trend extends to the space sector, where AI has already shown considerable success and has the potential to revolutionize almost every aspect of space exploration. We first highlight a number of success stories of the tremendous impact of [...]

RI Seminar
Sarah Bergbreiter
Professor
Mechanical Engineering, Carnegie Mellon University

Microsystems-inspired robotics

Gates Hillman Center 6115

Abstract: The ability to manufacture micro-scale sensors and actuators has inspired the robotics community for over 30 years. There have been huge success stories; MEMS inertial sensors have enabled an entire market of low-cost, small UAVs. However, the promise of ant-scale robots has largely failed. Ants can move high speeds on surfaces from picnic tables [...]

Field Robotics Center Seminar
Robotics Institute,
Carnegie Mellon University

Self-Supervised Learning on Mobile Robots Using Acoustics, Vibration, and Visual Models to Build Rich Semantic Terrain Maps

3305 Newell-Simon Hall

Abstract: Humans and robots would benefit from having rich semantic maps of the terrain in which they operate.  Mobile robots equipped with sensors and perception software could build such maps as they navigate through a new environment.  This information could then be used by humans or robots for better localization and path planning, as well [...]

PhD Thesis Proposal
Robotics Institute,
Carnegie Mellon University

Resource-Constrained State Estimation with Multi-Modal Sensing

GHC 4405

Abstract: Accurate and reliable state estimation is essential for safe mobile robot operation in real-world environments because ego-motion estimates are required by many critical autonomy functions such as control, planning, and mapping. Computing accurate state estimates depends on the physical characteristics of the environment, the selection of suitable sensors to capture that information, and the [...]

RI Seminar
Aaron Parness
Manager, Robotic Climbers & Grippers Group
NASA Jet Propulsion Laboratory, California Institute of Technology

Robotic Grippers for Planetary Applications

Gates Hillman Center 6115

Abstract: The previous generation of NASA missions to the outer solar system discovered salt water oceans on Europa and Enceladus, each with more liquid water than Earth – compelling targets to look for extraterrestrial life. Closer to home, JAXA and NASA have imaged sky-light entrances to lava tube caves on the Moon more than 100 [...]

VASC Seminar
Fuxin Li
Assistant Professor
Oregon State University

Some New Designs of Convolutional and Recurrent Networks

GHC 6501

Abstract: Convolutional networks (CNNs) and recurrent networks have driven the great engineering success of deep learning in recent years. However, as academics, we still wonder whether they are indeed the ultimate models of choice. Especially, CNNs seem unable to characterize predictive uncertainty, and they are highly dependent on small filters on small, rectangular neighborhoods. On [...]

RI Seminar
Tucker Hermans
Assistant Professor
School of Computing, University of Utah

Improving Multi-fingered Robot Manipulation by Unifying Learning and Planning

Gates Hillman Center 6115

Abstract: Multi-fingered hands offer autonomous robots increased dexterity, versatility, and stability over simple two-fingered grippers. Naturally, this increased ability comes with increased complexity in planning and executing manipulation actions. As such, I propose combining model-based planning with learned components to improve over purely data-driven or purely-model based approaches to manipulation. This talk examines multi-fingered autonomous [...]

VASC Seminar
Arthur Szlam
Research Scientist
Facebook AI Research

Language and Interaction in Minecraft

GHC 6501

Abstract:  I will discuss a research program aimed at building a Minecraft assistant, in order to facilitate the study of agents that can complete tasks specified by dialogue, and eventually, to learn from dialogue interactions.  I will describe the tools and platform we have built allowing players to interact with the agents and to record those interactions, and [...]

PhD Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Scaling Up Deep Learning with Model and Algorithm Awareness

GHC 4405

Abstract: In recent years, the pace of innovations in the fields of deep learning has accelerated. To cope with the sheer computational complexity of training large ML models on large datasets, researchers in the systems and ML communities have created software systems that parallelize training algorithms over multiple CPUs or GPUs (multi-device parallelism), or even [...]

RI Seminar
Seth Hutchinson
Professor & KUKA Chair for Robotics
School of Interactive Computing, Georgia Institute of Technology

Design, Modeling and Control of a Robot Bat: From Bio-inspiration to Engineering Solutions

Gates Hillman Center 6115

Abstract: In this talk, I will describe our recent work building a biologically-inspired bat robot. Bats have a complex skeletal morphology, with both ball-and-socket and revolute joints that interconnect the bones and muscles to create a musculoskeletal system with over 40 degrees of freedom, some of which are passive. Replicating this biological system in a [...]

VASC Seminar
Minh Hoai Nguyen
Assistant Professor
Stony Brook University

Attentive Human Action Recognition

Gates-Hillman Center 8102

Abstract:  Enabling computers to recognize human actions in video has the potential to revolutionize many areas that benefit society such as clinical diagnosis, human-computer interaction, and social robotics. Human action recognition, however, is tremendously challenging for computers due to the subtlety of human actions and the complexity of video data. Critical to the success of [...]

PhD Thesis Defense
Robotics Institute,
Carnegie Mellon University

Underwater Localization and Mapping with Imaging Sonar

NSH 3305

Abstract: Acoustic imaging sonars have been used for a variety of tasks intended to increase the autonomous capabilities of underwater vehicles. Among the most critical tasks of any autonomous vehicle are localization and mapping, which are the focus of this work. The difficulties presented by the imaging sonar sensor have led many previous attempts at [...]

RI Seminar
Pieter Abbeel
Professor
Director, Berkeley Robot Learning Lab & Co-Director, Berkeley Artificial Intelligence (BAIR) Lab, UC Berkeley

Deep Learning for Robotics

1305 Newell Simon Hall

Abstract: Programming robots remains notoriously difficult.  Equipping robots with the ability to learn would by-pass the need for what otherwise often ends up being time-consuming task specific programming.  This talk will describe recent progress in deep reinforcement learning (robots learning through their own trial and error), in apprenticeship learning (robots learning from observing people), and [...]

VASC Seminar
Xiaodong Yang
Principle Scientist
QCraft

Temporal Modeling and Data Synthesis for Visual Understanding

GHC 6501

Abstract: In this talk, I will present two recent pieces of work on leveraging temporal information and synthetic data to enhance video and image understanding. In the first part, I will introduce a progressive learning framework, Spatio-TEmporalProgressive (STEP), for action detection in videos. STEP is able to more effectively make use of longer temporal information, [...]

Field Robotics Center Seminar
Ioannis Pitas
Professor
Department of Informatics, Aristotle University of Thessaloniki

Multiple Drone Vision and Cinematography

3305 Newell-Simon Hall

Abstract: The aim of drone cinematography is to develop innovative intelligent single- and multiple-drone platforms for media production to cover outdoor events (e.g., sports) that are typically distributed over large expanses, ranging, for example, from a stadium to an entire city.  The drone or drone team, to be managed by the production director and his/her [...]

RI Seminar
Chung-Wei Lin
Assistant Professor
Department of Computer Science and Information Engineering (CSIE), National Taiwan University (NTU)

Modeling, Design, and Analysis for Intelligent Vehicles: Intersection Management, Security-Aware Design, and Automotive Design Automation

Newell-Simon Hall 4305

Abstract: Advanced Driver Assistance Systems (ADAS), autonomous functions, and connected applications bring a revolution to automotive systems and software. In this talk, several research topics in the domain of automotive systems and software will be introduced: (1) graph-based modeling, scheduling, and verification for intersection management, (2) security-aware design and analysis considering timing, game theory, and [...]

PhD Thesis Proposal
Robotics Institute,
Carnegie Mellon University

Open-world Object Detection and Tracking

NSH 3002

Abstract: Computer vision today excels at recognition in narrow slices of the real world. Our systems seem to accurately detect cats, cars, or chairs, but largely ignore the vast diversity of objects in the world that are absent from our training datasets. Perception in the open world, however, requires detecting and tracking any object, regardless [...]

PhD Thesis Defense
Robotics Institute,
Carnegie Mellon University

Personalized and weakly supervised learning for Parkinson’s disease symptom detection

GHC 8102

Abstract: Parkinson's Disease (PD) is a neurodegenerative disorder that affects approximately one million Americans. Medications exist to manage the symptoms, but doctors must periodically adjust dosage level and frequency as a patient's disease progresses. These adjustments are typically based on observations made during short clinic visits, which provide an incomplete picture of a patient's daily [...]

VASC Seminar
Shih-En Wei
Research Scientist
Facebook Reality Labs

VR facial animation via multiview image translation

GHC 6501

Abstract:  A key promise of Virtual Reality (VR) is the possibility of remote social interaction that is more immersive than any prior telecommunication media. However, existing social VR experiences are mediated by inauthentic digital representations of the user (i.e., stylized avatars). These stylized representations have limited the adoption of social VR applications in precisely those [...]

VASC Seminar
Stephen Lombardi
Research Scientist
Facebook Reality Labs

Neural Volumes: Learning Dynamic Renderable Volumes from Images

GHC 6501

Abstract:   Modeling and rendering of dynamic scenes is challenging, as natural scenes often contain complex phenomena such as thin structures, evolving topology, translucency, scattering, occlusion, and biological motion. Mesh-based reconstruction and tracking often fail in these cases, and other approaches (e.g., light field video) typically rely on constrained viewing conditions, which limit interactivity. We [...]

Special Events

RI40: Past, Present, and Future

Gates-Hillman Center 4401

Please plan to join us on Friday, October 25, 2019 as we celebrate 40 years of people, robots, and innovation! 40 years ago Carnegie Mellon University’s Robotics Institute opened its doors with the dream of ushering in a new age of thinking robots. During the ensuing decades, we have experienced many research successes in intelligent [...]

Seminar
H. Harry Asada
Ford Professor of Engineering; Director, d'Arbeloff Laboratory for Information Systems and Technology
Massachusetts Institute of Technology

RI40 Seminar: From Direct-Drive to SuperLimb Bionics

1305 Newell Simon Hall

In 1980-81 the first Direct-Drive robot was developed at the CMU Robotics Institute. After almost 40 years, Direct-Drive has a renewed interest in the leg robotics community. Robotic legs powered by direct-drive or low gear-reduction motors can better interact with the ground and absorb impacts. In this seminar I will talk about robot design in [...]

Field Robotics Center Seminar
Tom Scherlis & Advaith Sethuraman
Undergraduate Students
Department of Electrical and Computer Engineering, Carnegie Mellon University

Tartan AUV: A Dive into Carnegie Mellon’s RoboSub Team

NSH 4305

Abstract: Founded last year, Tartan AUV is Carnegie Mellon’s undergraduate underwater robotics team which competes annually in the RoboSub competition. RoboSub teams must design, build, and test autonomous underwater vehicles that compete each August to complete tasks related to underwater navigation, object detection and manipulation, and acoustic beacon localization. In this talk we will provide [...]

RI Seminar
Rebecca Taylor
Assistant Professor
Mechanical Engineering, Carnegie Mellon University

DNA and gammaPNA in programmable nanomaterials for sensing, robotics and manufacturing

Gates Hillman Center 6115

Abstract: When programmable nanomaterials are used in conjunction with rapid microfabrication techniques like two photon polymerization, it becomes possible to rapidly prototype microstructures with nanoscale components. In this research presentation I introduce DNA nanotechnology using a commonly used simple nanotube motif, and I will illustrate how nucleic acid nanotubes can be used in sensing, robotics [...]

VASC Seminar
Franziska Mueller
M.Sc. (Doctoral Candidate)
Max Planck Institute for Informatics

Towards Lightweight Real-time Hand Reconstruction in Challenging

GHC 6501

Abstract: Humans naturally use their hands to interact and communicate with their surroundings. Reconstructing these complex and dexterous hand interactions enables sign-language recognition and translation, better assistive robots, and more immersive human-computer interaction (e.g. for AR and VR). To make hand reconstruction usable for the aforementioned applications and to a wide set of users, the [...]

Special Events
Ming Luo
Stanford University
Mechanical Engineering Department, Stanford University

Soft Robotics challenges: Design, Fabrication, Control, and Motion Planning

Gates-Hillman Center 8102

Abstract: More and more robots of the future will be soft. A soft body can absorb impact forces from collisions with obstacles, making robots suitable for unpredictable environments and safe for human-robot interaction. However, widespread application of soft robotics in daily life, business, and consumer products have not yet been achieved, because established robotic technologies, [...]

VASC Seminar
Madalina Fiterau
Assistant Professor
UMass Amherst,College of Information and Computer Sciences

Hybrid Methods for the Integration of Heterogeneous Multimodal Biomedical Data

GHC 6501

Abstract:  The prevalence of smartphones and wearable devices for health monitoring and widespread use of electronic health records have led to a surge in heterogeneous multimodal healthcare data, collected at an unprecedented scale. My research focuses on developing machine learning techniques that learn salient representations of multimodal, heterogeneous data for biomedical predictive models. The first [...]

PhD Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Online and Consistent Occupancy Grid Mapping

GHC 4405

Abstract: Actively exploring and mapping an unknown environment requires integration of both simultaneous localization and mapping (SLAM) and path planning methods. Path planning relies on a map that contains free and occupied space information and is efficient to query, while the role of SLAM is to keep the map consistent as new measurements are continuously [...]

PhD Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

A Planning Framework for Persistent, Multi-UAV Coverage with Global Deconfliction

NSH 3001

Abstract: Planning for multi-robot coverage seeks to determine collision-free paths for a fleet of robots, enabling them to collectively observe points of interest in an environment. Persistent coverage is a variant of traditional coverage where coverage-levels in the environment decay over time. Thus, robots have to continuously revisit parts of the environment to maintain a [...]

RI Seminar
Girish Chowdhary
Assistant Professor
Department of Agricultural and Biological Engineering, University of Illinois at Urbana-Champaign

The Robots are Coming – to your Farm! AKA: Autonomous and Intelligent Robots in Unstructured Field Environments

Gates Hillman Center 6115

Abstract: What if a team of collaborative autonomous robots grew your food for you? In this talk, I will discuss some key advances in robotics, machine learning, and autonomy that will one day enable teams of small robots to grow food for you in your backyard in a fundamentally more sustainable way than modern mega-farms! [...]

PhD Thesis Proposal
Robotics Institute,
Carnegie Mellon University

‘Unboxing’ anomaly detection and panoptic segmentation

GHC 4405

Abstract: Panoptic segmentation is a recent problem in computer vision that attempts to classify each pixel in an image according to its semantic and instance label (accomplishing both semantic segmentation and instance segmentation respectively). Most existing panoptic and instance segmentation methods run a detection-first pipeline, where a bounding box is placed around an object and [...]

PhD Thesis Defense
Robotics Institute,
Carnegie Mellon University

Self-Supervised Learning on Mobile Robots Using Acoustics, Vibration, and Visual Models to Build Rich Semantic Terrain Maps

NSH 3305

Abstract: Humans and robots would benefit from having rich semantic maps of the terrain in which they operate. Mobile robots equipped with sensors and perception software could build such maps as they navigate through a new environment. This information could then be used by humans or robots for better localization and path planning, as well [...]

VASC Seminar
Carlos Vallespi
Staff Engineer and Technical Lead Manager
Uber ATG

Self-Driving Cars & AI: Transforming our Cities and our Lives

GHC 6501

Abstract:  Recent algorithmic and hardware improvements resulted in several success stories in the field of Artificial Intelligence (AI) which impact our daily lives. However, despite its ubiquity, AI is only just starting to make advances in what may arguably have the largest societal impact thus far, the nascent field of autonomous driving. At Uber ATG, [...]

PhD Thesis Proposal
Robotics Institute,
Carnegie Mellon University

Transfers Between Multiple Service Robots

GHC 4405

Abstract: With the deployment of more robots, human-robot interaction will no longer be limited to a one-to-one interaction between a user and a robot. Instead, users will likely have to interact with multiple robots, simultaneously or sequentially, throughout their day to receive services and complete different tasks. In this thesis proposal, I am proposing joint [...]

PhD Thesis Proposal
Robotics Institute,
Carnegie Mellon University

Machine Learning Parallelism Could Be Adaptive, Composable and Automated

NSH 3305

Abstract: In recent years, the pace of innovations in the fields of machine learning has accelerated. To cope with the sheer computational complexity of training large ML models on large datasets, researchers in SysML have created algorithms and systems that parallelize ML training and inference over multiple CPUs or GPUs, or even multiple computing nodes [...]

MSR Speaking Qualifier

MSR Thesis Talk – Matt Martone

Newell-Simon Hall 3305

Title: Design and Control of a Large Modular Hexapod   Abstract: Legged robotic systems have made great strides in recent years, but unlike wheeled robots, limbed locomotion does not scale well.  Long legs demand huge torques, driving up actuator size and onboard battery mass.  This relationship results in massive structures that lack the safety, portability, [...]

RI Seminar
Jeff Clune
Associate Professor
Computer Science, University of Wyoming

Improving Robot and Deep Reinforcement Learning via Quality Diversity and Open-Ended Algorithms

Gates Hillman Center 6115

Abstract: Quality Diversity (QD) algorithms are those that seek to produce a diverse set of high-performing solutions to problems. I will describe them and a number of their positive attributes. I will then summarize our Nature paper on how they, when combined with Bayesian Optimization, produce a learning algorithm that enables robots, after being damaged, to adapt in 1-2 minutes [...]

PhD Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Online Kinodynamic Planning for Teams of Aerial Robots in 3-D Workspaces

NSH 4305

Abstract: An efficient online planning or replanning methodology is a critical requirement for scalable and responsive real world multi-robot deployments. The need to replan typically stems from the invalidation of existing plans due to incomplete knowledge of the environment, or, from scenarios that necessitate changing goal locations in response to evolving application requirements. In this [...]

VASC Seminar
Larry Zitnick
Research Scientist
Facebook AI Research

Go, fastMRI, and Minecraft: Exploring the limits of AI

GHC 6501

Abstract: The application of AI across various domains demonstrates both the promise of existing techniques but also their limitations. In this talk, I explore three recent projects and how they shed light on the progress of AI and the challenges to come. These projects include ELF OpenGo a reimplementation of AlphaZero, fastMRI for reducing the time [...]

Special Events

Robotics Institute Administrative Staff Winter Tree Lunch

Newell-Simon Hall 4201

Please join us for our annual Robotics Institute Administrative Staff Winter Tree Decorating Lunch. A light lunch will be provided but staff-created treats will always be welcomed.

PhD Thesis Proposal
Robotics Institute,
Carnegie Mellon University

Expressive Real-time Intersection Scheduling: New Methods for Adaptive Traffic Signal Control

GHC 6501

Abstract: Traffic congestion is a widespread problem throughout global metropolitan areas. In this thesis, we consider methods to optimize the performance of traffic signals to reduce congestion. We begin by presenting Expressive Real-time Intersection Scheduling (ERIS), a schedule-driven intersection control strategy that runs independently on each intersection in a traffic network. For each intersection, ERIS [...]

PhD Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

Open-world 3D Object Detection

NSH 4305

Abstract: Perception for autonomous robots presents a set of unique challenges: finding the right representation for 3D signals, adapting to an open-world setting, and exploiting geometric priors. Successfully detecting objects regardless of their labels lays a solid foundation for safe navigation. I will present two of my recent works in this line. First, I will [...]

VASC Seminar
Zhiding Yu
Research Scientist
NVIDIA Research

Towards Weakly-Supervised Visual Understanding

GHC 6501

Abstract:  Learning with weak and self-supervisions recently emerged as compelling tools towards leveraging vast amounts of unlabeled or partially-labeled data. In this talk, I will present some of the latest advances in weakly-supervised visual scene understanding from NVIDIA. Specifically, I will summarize and discuss some challenges and potential solutions in weakly-supervised learning, and introduce our [...]

MSR Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

MSR Thesis Talk: Jenny Nan

Smith Hall 200

Title: Combining Deep Learning and Verification for Precise Object Instance Detection   Abstract: Deep learning based object detectors often return false positives with very high confidence. Although they optimize generic detection performance, such as mean average precision (mAP), they are not designed for reliability. For a reliable detection system, if a high confidence detection is [...]

MSR Speaking Qualifier
Robotics Institute,
Carnegie Mellon University

MSR Thesis talk – Vasu Agrawal

NSH 4305

Title: Ground Up Design of a Multi-modal Object Localization System   Abstract:   Rapid situational awareness is the key to enabling a successful response from first responders during an emergency, where time is of the essence. Emergency personnel are often sent into incident scenes to gather information, but this is often a dangerous and slow process.  Subterranean environments [...]

MSR Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

MSR Thesis Talk – Swaminathan Gurumurthy

GHC 4405

Title: Improving generalization in data-driven models with task-specific knowledge Abstract: With the rise of the over-parameterized deep learning models and massive datasets, many have started advocating towards minimizing the amount of prior knowledge added to a learning model. Ironically, the traditional machine learning community advocated for exactly the opposite. Whereas the latter assumes knowledge of [...]

Special Events

RI Winter Party

Newell-Simon Hall Perlis Atrium

Robotics Institute Winter Party Please join us for some fun, food, beverages and conversation! All RI faculty, staff, students and visitors are invited to the Robotics Institute Winter Party! We apologize but due to space limitations in the Atrium we regretfully cannot include family or other non-RI guests.

VASC Seminar
Vivek Boominathan
Postdoctoral Researcher
Rice University

Imaging without focusing: A computational approach to miniaturizing cameras

3305 Newell-Simon Hall

Abstract:  Miniaturization of cameras is key to enabling new applications in areas such as connected devices, wearables, implantable medical devices, in vivo microscopy, and micro-robotics. Recently, lenses were identified as the main bottleneck in miniaturization of cameras. Standard smaller lens-system camera modules have a thickness of about 10 mm or higher, and reducing the size [...]

PhD Thesis Proposal

Adaptive Planning and Control of Wheeled Mobile Robots in Challenging Environments

GHC 4405

Abstract: Over the last two decades, we have seen driverless cars conquer the Mojave desert, drive on mars and operate on our streets and warehouses. One of the most fundamental requirements of such robots is their ability to navigate their environment with minimal human oversight. As more robots graduate from the confines of laboratories to [...]

VASC Seminar
Pablo Garrido
Research Scientist
Epic Games

Towards photo-realistic face digitization from monocular videos

GHC 6501

Abstract:  Recent advances in face capture now enable digitizing high-quality 3D faces for the entertainment industry. Standardized digitization solutions, however, require tailor-made capture systems and extensive manual work, making them expensive and hard to deploy. With the advent of commodity sensors, new lightweight approaches that push the boundaries of human digitization have been introduced, slowly [...]

PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

When to use CNNs for Inverse Problems in Vision

NSH 4201

Abstract: Reconstruction tasks in computer vision aim fundamentally to recover an undetermined signal from a set of noisy measurements. Examples include super-resolution, image denoising, and non-rigid structure from motion\cite{Kong_2019}, all of which have seen recent advancements through deep learning. However, earlier work made extensive use of sparse signal reconstruction frameworks (e.g. convolutional sparse coding). While [...]