CV

Resume

Education

• Ph.D in Electical Engineering and Computer Science, UC Berkeley, 2022
  • GPA: 3.96
  • Received a NSF Graduate Research Fellowship for Robotics and Computer Vision in Spring 2019
• B.S.E. in Electrical Engineering (Magna Cum Laude), Princeton University, 2016
  • GPA: 3.88
  • Minors in Computer Science, Robotics and Intelligent Systems, and Italian Language
  • Winner of the Peter Mark Prize
  • Elected to Phi Beta Kappa, Society of Sigma Xi, and Tau Beta Pi
  • Received the Dorothea Van Dyke McLane Prize
  • Elected to Gamma Kappa Alpha (National Italian Honor Society)

Publications

FogROS2: An Adaptive Platform for Cloud and Fog Robotics Using ROS 2

Mechanical Search on Shelves with Efficient Stacking and Destacking of Objects

Optimal Shelf Arrangement to Minimize Robot Retrieval Time

Mechanical Search on Shelves using a Novel “Bluction” Tool

LEGS: Learning Efficient Grasp Sets for Exploratory Grasping

Simulation of Parallel-Jaw Grasping using Incremental Potential Contact Models

A Multi-Chamber Smart Suction Cup for Adaptive Gripping and Haptic Exploration

Mechanical Search on Shelves using Lateral Access X-RAY

Kit-Net: Self-Supervised Learning to Kit Novel 3D Objects into Novel 3D Cavities

FogROS: An Adaptive Framework for Automating Fog Robotics Deployment

AVPLUG: Approach Vector PLanning for Unicontact Grasping amid Clutter

Object Rearrangement Using Learned Implicit Collision Functions

Exploratory Grasping: Asymptotically Optimal Algorithms for Grasping Challenging Polyhedral Objects

X-Ray: Mechanical Search for an Occluded Object by Minimizing Support of Learned Occupancy Distributions

Accelerating Grasp Exploration by Leveraging Learned Priors

Robust Task-Based Grasping as a Service

One-Shot Shape-Based Amodal-to-Modal Instance Segmentation

Non-Markov Policies to Reduce Sequential Failures in Robot Bin Picking

Minimal Work: A Grasp Quality Metric for Deformable Hollow Objects

GOMP: Grasp-Optimized Motion Planning for Bin Picking

Efficiently Planning Soft Non-Planar Area Contact Grasps using 6D Friction Cones

REACH: Reducing False Negatives in Robot Grasp Planning with a Robust Efficient Area Contact Hypothesis Model

Robust Toppling for Vacuum Suction Grasping

Automating Planar Object Singulation by Linear Pushing with Single-point and Multi-point Contacts

Adversarial Grasp Objects

Segmenting Unknown 3D Objects from Real Depth Images using Mask R-CNN Trained on Synthetic Data

Mechanical Search: Multi-Step Retrieval of a Target Object Occluded by Clutter

Learning Ambidextrous Robot Grasping Policies

Linear Push Policies to Increase Grasp Access for Robot Bin Picking

Teaching

EECS 16B: Designing Information Devices and Systems II

CS 188: Introduction to Artificial Intelligence

Blog Posts

Drilling Down on Depth Sensing and Deep Learning

15 minute read

Work Experience

• Ambi Robotics (March 2022 - Present), Berkeley, CA
  • Research Scientist
• NVIDIA (June 2020 - November 2020), Seattle, WA (Remote)
  • Seattle Robotics Lab Intern
• VirtualAPT (July 2016 - August 2017), Brooklyn, NY
  • Head of Electrical Engineering
• MIT Lincoln Laboratory (June - August 2015), Lexington, MA
  • Advanced Imager Technology Intern (Group 87)
• Nufern (June - August 2014), East Granby, CT
  • R&D Laser Intern
• Northeast Utilities (June - August, 2013), Berlin, CT
  • Transmission Protection and Controls Engineering Student Technician