Ned Bingham
eab242@cornell.edu
Education
PhD Candidate, Electrical and Computer Engineering
Cornell Tech
GPA 4.00
  • Parallel and Distributed Computing (CS 5460)
  • Mobile and Ubiquitous Systems (CS 5454)
  • Introduction to Database Systems (CS 5320)
Manhatten, NY
May 2013 to
Current
Bachelor of Engineering, Electrical and Computer Engineering
Cornell University
GPA 3.29
  • Multivariable Calculus for Engineers (MATH 1920)
  • Introduction to Special Relativity (PHYS 2216)
  • Introduction to Computing Using Matlab (CS 1112)
  • Introduction to Architecture (ARCH 1301)
  • Serial Novel Goes Graphic (ENGL 1123)
  • Physics II Electricity and Magnetism (PHYS 2213)
  • Linear Algebra for Engineers (MATH 2940)
  • Introduction to Nanoscience and Nanoengineering (ENGRI 1200)
  • Transition to Object Oriented Programming (CS 1130)
  • Engineering General Chemistry (CHEM 2090)
  • Physics III Oscillations, Waves, and Quantum Physics (PHYS 2214)
  • Differential Equations for Engineers (MATH 2930)
  • Object Oriented Programming and Data Structures (ENGRD 2110)
  • Introduction to Circuits for Electrical and Computer Engineers (ECE 2100)
  • Embedded Systems (ECE 3140)
  • ECE Practice and Design (ECE 2400)
  • Introduction to Digital Logic Design (ECE 2300)
  • Signals and Systems (ECE 2200)
  • Statics and Mechanics of Solids (ENGRD 2020)
  • Probability and Inference (ECE 3100)
  • Electromagnetic Fields and Waves (ECE 3030)
  • Operating Systems (CS 4410)
  • Digital System Design Using Microcontrollers (ECE 4760)
  • Digital VLSI Design (ECE 4740)
  • Computer Networks and Telecommunications (ECE 4450)
  • Introduction to Microelectronics (ECE 3150)
  • Computer Architecture (ECE 4750)
  • Death of God (RELST 3342)
  • Human Computer Interaction Design (COMM 3450)
  • Asynchronous VLSI Design (ECE 5740)
  • Introduction to Controlled Fusion (ECE 4840)
  • Introduction to Linguistics (LING 1101)
  • Ancient Peoples and Places (ANTHR 1200)
  • International Trade and Finance (ECON 2300)
Ithaca, NY
August 2009 to
May 2013
Experience
Google Platforms
Intern
Mountain View, CA
May 2016 to
August 2016
Qualcomm Research and Development
Intern

I taught approaches to designing asynchronous quasi delay insensitive circuits. To help expose them to asynchronous design paradigms, I also did an exploration on asynchronous bit parallel multipliers, taking them through every design decision and optimization along the way.

San Diego, CA
June 2014 to
September 2014
Intel Corporation
Pre-Silicon Validation Engineer

I exposed and characterized bugs in the firmware for the power controller unit in Intel's recently announced 18-core Haswell-EX processor. I wrote the testing framework for the BIOS and a tool to determine the conditions needed to cover a currently uncovered line of code.

Hudson, MA
May 2012 to
August 2013
Intel Corporation
Pre-Silicon Validation Engineer

I exposed and characterized bugs in the low level cache in Intel's recently announced 15-core Ivytown-EX processor. I was responsible for writing most of the functional coverage conditions and filling those conditions with tests.

Hudson, MA
September 2011 to
January 2012
Architecture Technology Corporation
Intern

I created scripts for Router Marshal to add support for many different routers and created a java plugin for P2P Marshal to add support for eMule.

Ithaca, NY
May 2010 to
August 2010
Indiana University's Perception Action Lab
Lab Programmer

I programmed three displays for scientific experiments in human perception and one program to facilitate assignment of teacher's assistants. I also created their website. For my work, my name was put on two published papers.

Bloomington, IN
2008 to
2009
Publications
[pdf] Object Recognition Using Metric Shape
Young-Lim Lee, Mats Lind, Ned Bingham, Geoffrey P. Bingham

Most previous studies of 3D shape perception have shown a general inability to visually perceive metric shape. In line with this, studies of object recognition have shown that only qualitative differences, not quantitative or metric ones can be used effectively for object recognition. Recently, Bingham and Lind (2008) found that large perspective changes allow perception of metric shape and Lee and Bingham (2010) found that this, in turn, allowed accurate feedforward reaches-to-grasp objects varying in metric shape. We now investigated whether this information would allow accurate and effective recognition of objects that vary in respect to metric shape. Both judgment accuracies and reaction times confirmed that, with the availability of visual information in large perspective changes, recognition of objects using quantitative as compared to qualitative properties was equivalent in accuracy and speed of judgments. The ability to recognize objects based on their metric shape is, therefore, a function of the availability or unavailability of requisite visual information. These issues and results are discussed in the context of the Two Visual System hypothesis of Milner and Goodale (1996, 2006).

August 3, 2012
[pdf] Embodied Memory: Effective and Stable Perception By Combining Optic Flow and Image Structure
Jing Samantha Pan, Ned Bingham, Geoffrey P. Bingham

Visual perception studies typically focus either on optic flow structure or image structure, but not on the combination and interaction of these two sources of information. Each offers unique strengths in contrast to the other's weaknesses. Optic flow yields intrinsically powerful information about 3D structure, but is ephemeral. It ceases when motion stops. Image structure is less powerful in specifying 3D structure, but is stable. It remains when motion stops. Optic flow and image structure are intrinsically related in vision because the optic flow carries one image to the next. This relation is especially important in the context of progressive occlusion, in which optic flow provides information about the location of targets hidden in subsequent image structure. In four experiments, we investigated the role of image structure in "embodied memory" in contrast to memory that is only in the head. We found that either optic flow (Experiment 1) or image structure (Experiment 2) alone were relatively ineffective, whereas the combination was effective and, in contrast to conditions requiring reliance on memory-in-the-head, much more stable over extended time (Experiments 2 through 4). Limits well documented for visual short memory (that is, memory-in-the-head) were strongly exceeded by embodied memory. The findings support J. J. Gibson's (1979/1986, The Ecological Approach to Visual Perception, Boston, MA, Houghton Mifflin) insights about progressive occlusion and the embodied nature of perception and memory.

March 11, 2013