(All Seminars)

Location: Atkinson Hall Auditorium

Time: 5:00pm - 7:00pm

"Learning Adaptive Models for Human-Robot Teaming" 

Atkinson Hall 4004/4006

Howard Thomas - University of Rochester

"Key Challenges in Agricultural Robotics with Examples of Ground Vehicle Localization in Orchards and Task-Specific Manipulator Design for Fruit Harvesting"

EBU 1 - Qualcomm Conference Room 

Amir Degani - Technion (Israel Institute of Technology) 


Dr Amir Degani is an Associate Professor at the Technion - Israel Institute of Technology. Dr Degani is the Director of the Civil, Environmental, and Agricultural Robotics (CEAR) Laboratory researching robotic  legged locomotion and autonomous systems in civil and agriculture applications. His research program includes mechanism analysis, synthesis, control and motion planning and design with emphasis on minimalistic concepts and the study of nonlinear dynamic hybrid systems.

His talk will present the need for robotics in agriculture and focus on examples of solutions for two different problems. The first is the localization of an autonomous ground vehicle in a homogenous orchard environment. The typical localization approaches are not adjusted to the characteristics of the orchard environment, especially the homogeneous scenery. To alleviate these difficulties, Dr Degani and his colleagues use top-view images of the orchard acquired in real-time. The top-view observation of the orchard provides a unique signature of every tree formed by the shape of its canopy. This practically changes the homogeneity premise in orchards and paves the way for addressing the “kidnapped robot problem”.

The second part of the talk will focus on efforts to define and perform task-based optimization for an apple-harvesting robot. Since there is a large variation between trees, instead of performing this laborious optimization on many trees, Dr Degani and his colleagues look for a “lower dimensional” characterization of the trees. Moreover, the shape of the tree (i.e., the environment) has a major influence on the robot’s simplicity. Therefore, Dr Degani and his colleagues strive to find the best training system for a tree to help simplify the robot’s design.

"The Business of Robotics: An introduction to the commercial robotics landscape, and considerations for identifying valuable robot opportunities."

Center for Memory Recording Research (CMRR)

Phil DuffyBrain Corp

Phil Duffy is the Vice President of Innovations at Brain Corp. As VP of Innovations, he leads product commercialization activities at Brain Corp to discover novel product and market opportunities for autonomous mobile robotics. His team is responsible for defining product strategy for Brain Corp's AI technology, BrainOS. A serial entrepreneur and product strategist, Phil has a proven track record for growing technology start-ups, and commercializing and launching innovative, robotic products in the B2B and B2C markets. Phil joined Brain Corp in 2014 and brings with him 20+ years leadership experience in product management, marketing, and China manufacturing. This talk will provide an overview of the commercial robotics landscape, identify valuable robot opportunities, and focus on important elements to consider when developing and marketing robotics technology.

"Efficient memory-usage techniques in deep neural networks via a graph-based approach"

Qualcomm Conference Room (EBU-1)

Salimeh Yasaei Sekeh - University of Maine 

Dr. Salimeh Yasaei Sekeh is the Assistant Professor of Computer Science in the School of Computing and Information Sciences at the University of Maine. Her research focuses on designing and analyzing machine learning algorithms, deep learning techniques, applications of machine learning approaches in real-time problems, data mining, pattern recognition, and network structure learning with applications in biology. This talk introduces two new and efficient deep memory usage techniques based on the geometric dependency criterion. This first technique is called Online Streaming Deep Feature Selection. This technique is based on a novel supervised streaming setting and it measures deep feature relevance while maintaining a minimal deep feature subset with relatively high classification performance and less memory requirement. The second technique is called Geometric Dependency-based Neuron Trimming. This technique is a data-driven pruning method that evaluates the relationship between nodes in consecutive layers. In this approach, a new dependency-based pruning score removes neurons with least importance, and then the network is fine-tuned to retain its predictive power. Both methods are evaluated on several data sets with multiple CNN models and demonstrated to achieve significant memory compression compared to the baselines.

"Human-Machine Teaming at the Robotics Research Center at West Point" 

Qualcomm Conference Room (EBU-1) 

Misha Novitzky - West Point 

Dr. Misha Novitzky is the Assistant Professor of the Robotics Research Center in the United States Military Academy at West Point. His work focuses on human-machine teaming for cooperative tasks in stressful and unconstrained environments. This talk will provide a brief overview of the various projects being conducted by the Robotics Research Center at the United States Military Academy, located in West Point, New York. In particular, the talk will focus on human-machine teaming. Most human-robot interaction or teaming research is performed in structured and sterile environments. It is our goal to take human-machine teaming outside into unstructured and stressful environments. As part of this effort, we will describe Project Aquaticus in which humans and robots were embedded in the marine environment and played games of capture the flag against similarly situated teams, and present results of our pilot studies. While Project Aquaticus was previously performed at the Massachusetts Institute of Technology, we will describe why the Robotics Research Center at West Point is an exceptional location to perform future human-machine teaming research.

"Introducing Qualcomm Snapdragon Ride"

Center for Memory and Recording Research (CMRR)

Ahmed Sadek - Qualcomm 

The Criticality of Systems Engineering to Autonomous Air Vehicle Development

Ariele Sparks - Northrop Grumman

Systems Engineering the World's Most Energetic Laser

Robert Plummer - LLNL

Applying a Decision Theoretic Framework for Evaluating System Trade-Offs

Nirmal Velayudhan - ViaSat

Scaling the Third Dimension in Silicon Integration

Srinivas Chennupaty - Intel

The Cost of Taking Shortcuts

David Harris - Cubic Transporation Systems

An Integrated Medium Earth Orbit - Low Earth Orbit Navigation, Communication and Authentication System of Systems

David Whelan - UC San Diego

Handling Scale (System and Developer) and Reliability in Large and Critical Systems

Sagnik Nandy - Google

People-First Systems Engineering: Challenges and Opportunities in Smart Cities

Jeff Lorbeck - Qualcomm