Nima Leclerc

Nima Leclerc

Quantum Research Scientist at MITRE and Partner at Abelian

Boston, MA

Google Scholar, Github, LinkedIn

CV

Hi.
I am an Iranian-American electrical engineer and materials scientist at the at the University of Pennsylvania, and a 2022-2023 Policy Graduate Associate at Perry World House. My doctoral work has focused on engineering scalable quantum processors in silicon for the next generation of quantum computers, by combining techniques quantum control, device engineering, materials science, and optimization theory. I received my undergraduate engineering training in Materials Science and Engineering Cornell University. At Cornell, I studied the ways in which electronic transport can be engineered to yield more energy efficient information processing devices. Working there, I embodied the approach of combining theoretical and experimental approaches to engineer novel electronic devices, which culminated in my senior honors thesis. Prior to transferring to Cornell in 2017, I was a Mechanical Engineering major at San Francisco State University, where I developed a new class of solid-state battery electrolytes.

I have co-authored several publications and conference presentations and given invited talks in fields of energy storage, semiconductor devices, and quantum engineering and have won numerous awards in doing so. I have worked across academic, government, and private sectors developing classical and quantum computing technologies. Using my expertise in condensed matter/quantum physics, materials science, nanofabrication, and machine learning, I'm interested in combining these approaches to develop scalable quantum control protocols and device architectures to solve challenging problems in drug design and encryption. My policy work at Penn's Perry World House complements my doctoral research. I work with federal legislatures, global leaders, and lobbyists to develop policy around the national security implications of quantum technologies.

I grew up in beautiful Lafayette, CA. Apart from my research, engineering, and policy work, I'm also a competitive long distance runner and concert pianist. Browse my site to learn more!

Education

University of Pennsylvania

Masters in Electrical Engineering, 2020-2022

Dean's Fellow, Policy Graduate Fellow, Penn Track Club.

Working on spin-based quantum computing in silicon.

Cornell University

Bachelors in Materials Science and Engineering (concentration in electronic/quantum technology materials) and minor in Computer Science, 2017-2020

Cornell Tradition Fellow, CURB Research Mentor, Cornell Materials Society, Cornell Piano Society, Cornell Track Club.

Honors thesis focused on quantum mechanical noise sources in next-generation, low-power transistors.

San Francisco State University

Former Bachelors Candidate in Mechanical Engineering, 2015-2017

NCAA Division II Cross Country Athlete.

Developed a new solid-state battery electrolyte.

Awards

Perry World House Graduate Fellowship, 2021

Perry World House Profile

Selected to be among 26 from 200+ applicants at Penn to investigate the national security implications of quantum technologies.

The Dean's Fellowship, 2021

Dean's Fellowship

Selected among hundreds to receive $50,000/year for tuition and living expenses over 5 years of my doctoral studies.

Computational Chemistry and Materials Science Summer Fellowship, 2021

CCMS Fellowship

Selected among hundreds based on proposed work for spin-based quantum sensors (declined).

Cornell Engineering Learning Initiative Research Fellowship, 2017

Awarded $1,850 through competitive proposal review process to develop solid-state electrolyte batteries. Funded by Boeing, work conducted at Cornell.

The Cornell Tradition Fellowship, 2017

The Cornell Tradition

Awarded competitive $2,000 fellowship for my commitment to public service.

Summer Undergraduate Research Fellowship (SURF), 2017

Proposal selected from competitive-review process to develop 3D microbatteries for heart transplants at Caltech.

Robert L. Pender Memorial Scholarship, 2016

Parkmered News Mention

Single awardee among 100+ applicants for a $1,000 award for my research on solid-state batteries.

Semi-Finalist for the SMART Scholarship, 2016

SMART Scholarship

Selected to be a semi-finalist for the SMART undergraduate scholarship for work in the Army Research Laboratory.

Scholar-Athlete, 2016

News Mention for Award Reception

Award for maintaining high grade-point-average as a NCAA student-athlete.

Research Experience

Quantum Hardware Lab, 2021-2023

Fabricating silicon-based quantum dot processors, developing optimal quantum control protocols with microwave pulse engineering, and inventing the world's first quantum random access memory to systematically increase qubit connectvity. As the first PhD student in the lab, I'm spearheading efforts in setting up the lab's infrastructure, mentoring new masters and PhD students, and leading my own projects in quantum pulse engineering for high-fidelity control.

Quantum Engineering Lab, 2020-2021

Worked with experimental and theoretical collaborators at Penn and Brown, I developed a qubit inverse-design algorithm based on Bayesian optimization. Wrote a section of an NSF annual report.

Griffin Group, 2019-2020

Developed the theoretical groundwork for a new class of quantum bits: electric field controlled spins in ferroelectrics. Collaborated with experimental groups at Berkeley and Oxford to synthesize and physically realize electrostatic spin control. Primary contributor of a codebase to automate theoretical calculations on supercomputing facilities. Presented findings at several conference venues and prepared/submitted manuscripts. Learn more here.

Jena-Xing Lab, 2017-2020

Contributed to the development of the first III-V epitaxial semiconductor-superconductor tunnel junnel junction. Built a low-frequency noise characterization setup from scratch to identify sources of quantum mechanical noise in semiconductor heterostructures for honors thesis. Spearheaded first principles modeling efforts within the group. Mentored masters students on material design problems. Learn more here.

Neaton Group Page, 2018

Awarded the competitive SULI inernship to design valleytronic devices under Dr. Jeffrey Neaton at The Molecular Foundry . Utilized advanced electronic structure theory to design a new class of beyond-Moore's law device materials. Presented work at several conference venues. Learn more here.

Robinson Lab, 2017-2018

My proposal was awarded to integrate a solid state electrolyte (LiPON) into a nanoparticle cathode system. Utilized statistical mechanical models, plasma and colloidal synthesis, and electrochemical characterization to design highly energy and power dense solid state batteries. Learn more here.

Greer Lab, 2017

I was awarded a SURF fellowship based on my proposal to develop 3D nanoarchitected batteries. Used two-photon lithography to fabricate 3D polymer nanoscaffolds and deposited Li anodes with LiI solid-state electrolytes to facilitate high-energy dense storage. Learn more here.

Adelstein Group, 2015-2017

Using electronic structure methods and molecular dynamics, I designed a new class of Lithium thiophosphate solid-state electrolytes for high energy storage batteries. I led my own project in collaboration with the Quantum Simulations Group at Lawrence Livermore National Lab to predict lithium diffusion pathways in these materials from quantum mechanics. I later presented my work at several national conferences. Learn more here.

Industry Experience

Kepler Computing, 2021

Spearheaded the device design efforts at Kepler Computing (low-power computing device startup in Berkeley, CA). Established an automated testing framework for characterizing the polarization and electronic properties of ferroelectric memory devices. Developed thermodynamic, electronic structure, and device modeling frameworks to aid the design and measurement of ferroelectric films and memories. Key efforts in the company's device engineering currently rely on the frameworks that I have developed. Worked closely with faculty at UC Berkeley, including Dr. Ramamoorthy Ramesh.

PsiQuantum, 2019

PsiQuantum Page

Developed a framework for the optimal design of superconducting single-photon detectors, necessary for readout of photonic quantum computers. I combined experimental results, theoretical models, and Bayesian optimization to design detectors with maximal efficiency. The designs I created are curretly being used by the company, being fabricated in large-scale tapeouts. Worked closely with Dr. Faraz Najafi and Dr. Jeremy O'Brien.

Teaching Experience

Inspirit AI

Machine Learning Innovator Program Instructor (college level), Winter 2021
Deep Learning Course Instructor (high school level), Summer 2021
Machine Learning Course Instructor (high school level), Spring 2021

University of Pennsylvania

Head Teaching Assistant for Fundamentals of Linear Algebra and Optimization (CIS 515), Spring 2022
Head Teaching Assistant for Fundamentals of Linear Algebra and Optimization (CIS 515), Spring 2021
Teaching Assistant for Fundamentals of Linear Algebra and Optimization (CIS 515), Fall 2020

Cornell University

Teaching Assistant for Principles of Large-Scale Machine Learning (CS 4787), Spring 2020

San Francisco State University

Math, Science, and Engineering Tutor at Campus Academic Resource Program, Fall 2015 - Spring 2017

Outreach

#savethefrontline co-founder, 2020

#savethefrontline

Co-founded a nonprofit with a team of Cornell alumni at the start of the COVID-19 pandemic to establish a distribution framework of PPE to healthcare workers and other first responders in New York City. Raised almost $350,000 for PPE and distribution costs and delivered nearly 95K supplies to those in need. Established partnerships with local businesses in NYC to expedite distribution. Efforts were featured in several media outlets.

CURB Peer Mentor, 2018-2019

CURB Mentor Program Page

Volunteered as a peer mentor for four semesters through CURB at Cornell. Efforts focused on introducing freshmen and sophomores to undergraduate research, identifying research interests, and establishing connections with Cornell faculty. 100 % success rate in matching students with their top 3 research groups.