David Nader
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David Nader Email & Phone Number

Applied Scientist 2 at Microsoft
Location: Williamsburg, Virginia, United States 14 work roles 5 schools
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Role
Applied Scientist 2
Location
Williamsburg, Virginia, United States

Who is David Nader? Overview

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David Nader is listed as Applied Scientist 2 at Microsoft, based in Williamsburg, Virginia, United States. AeroLeads shows a matched LinkedIn profile for David Nader.

David Nader previously worked as Research Assistant at William & Mary and Teacher Assistant at William & Mary. David Nader holds Doctor Of Philosophy - Phd, Computer Science, Gpa 3.75 from William & Mary.

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Microsoft

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Profile bio

About David Nader

I am a Research Assistant and a PhD candidate in Computer Science at William & Mary, with over 7 years of experience in machine learning and software engineering research. My main focus is exploring the synergies of causal inference and deep learning to automate and improve software maintenance tasks, such as bug fixing, code summarization, and traceability link recovery.I have published and presented multiple papers in prestigious conferences and journals, such as ICSE, TOSEM, and TSE, demonstrating my expertise in applying state-of-the-art techniques, such as T5 models, Bayesian probabilistic methods, and information theory, to various software engineering problems. I have also gained valuable industry experience as a research intern at Microsoft and Cisco, where I developed and evaluated novel interpretability methods for large language models for code. I am passionate about advancing software engineering with cutting-edge artificial intelligence and causal inference approaches. I am eager to pursue opportunities that allow me to contribute to this exciting and challenging domain.

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Microsoft
Microsoft
Applied Scientist 2
Seattle, WA, US
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14 roles

David Nader work experience

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Applied Scientist 2

Seattle, WA, US

Research Assistant

Current

Virginia

  • Explored synergies at the intersection of causality and deep learning to automate software engineering task
  • Defined a causal inference technique for interpreting large language models trained on code [ArXiv’23]
  • Surveyed the most prominent SE and DL conferences and journals (128 papers across 23 unique SE tasks) to propose general guidelines on the use of deep learning in software engineering [TOSEM’22]
  • Investigated a T5 model to support 4 software‑related tasks: automatic bug‑fixing, assert statement generation, code summarization, and code mutant injection [ICSE’21]
  • Proposed and developed a Bayesian probabilistic approach to improve the effectiveness of traceability links by ‑10% [ICSE’20]
  • Designed and executed a convolutional neural net to identify security‑related issues (96% success rate) [ICSME’19]
Jan 2019 - Present

Teacher Assistant

Virginia

  • Assisted in teaching 4 undergraduate and graduate courses: Neural Networks & Deep Learning, Software Engineering, Software Development, and Reasoning Under Uncertainty
  • Supervised students in final projects, graded exams, and weekly homework
Aug 2017 - Jun 2019

Research Intern

United States

  • Collaborated with a four‑person team to research an interpretability model to enhance large language models for code [to be published 2023].
  • Formulated and designed a debugging tool based on explainability rationales and shapley values for large language models for code
Oct 2021 - Mar 2022

Ph.D. Intern

RTP

  • Investigated an information theory approach to interpret and evaluate software retrieval techniques [to be published 2023]
  • Analyzed potential applications of software traceability algorithms for security‑related requirements
May 2020 - Aug 2020

Researcher Assistant

Colombia

  • Developed a hybrid adaptive evolutionary algorithm to detect and recommend feasible software refactorings [GECCO’18]
  • Designed genetic algorithms and other search‑based techniques to optimize software maintainability tasks
Jan 2015 - Jun 2018

Graduate Teaching Assistant

Bogota

  • Taught Computer Programming to 2 groups of 30 sophomores in weekly sessions for 2 semesters
  • Awarded Graduate Assistantship (top %5)
Jan 2015 - Dec 2015

Research Scholar

United States

  • Proposed and developed a Bayesian probabilistic approach to improve the effectiveness of traceability links by ‑10% [ICSE’20]
Jan 2017 - Jun 2017

Software Engineer

Bogotá D.C. Area, Colombia

  • Engineered reactive and functional programming architectures for enabling fast development of any type of marketplace business [project link]
  • Programmed automated pipelines for the construction and deployment of highly scalable software reducing stakeholders’ costs by 45%
Feb 2016 - Dec 2016

Software Engineer

Secretaría De Educación Del Distrito

Bogotá D.C. Area, Colombia

  • Maintained and refactored legacy software architecture of public high‑school institutions in Bogota
  • Managed and instructed the adoption of software practices in the government institution optimizing 65% of the development process
Mar 2015 - Feb 2016

Team Leader

Bogotá

  • Managed the research team of 7 computer scientists to enhance and simplify the software construction pipeline (achieved Level 4 CMMI)
  • Engineered the required architecture for a technology migration that impacts the core system (helped client productivity by 40%)
Oct 2013 - Oct 2014

Intern Software Test Engineering

Munich Area, Germany

  • Created automatic test scripts to integrate functional and non‑functional reports reducing testing time by 8% on new releases
Apr 2013 - Sep 2013

Software Developer

Bogotá D.C. Area, Colombia

  • Refactored software business components augmenting comprehensibility of the core system by 60%
  • Programmed a critical pl/sql back‑end module for portfolio operations for the biggest financial entities in Colombia
Jan 2012 - Sep 2012

Student Assistant

Colombia

Special interest in areas such as: - Programming Languages JAVA and C++ - Algorithms

Jan 2009 - Dec 2011
5 education records

David Nader education

Doctor Of Philosophy - Phd, Computer Science, Gpa 3.75

• Coursework: Data Analysis and Simulation, Advance Software Engineering, Cybersecurity, Data‑driven Security & Privacy

Master Of Science (Msc) Computer Engineering, Computer Engineering, Gpa 3.85

Activities and Societies: Alife Research Group• Award: Indian Government Scholarship ITEC; C‑DAC; Noida, India • Coursework: Artificial.

Master Of Science (M.Sc.) Informatics, Computer Engineering

• Exchange program (top 1%) in Machine Learning and Data Mining

Bachelor'S Degree, Computer Engineering, Gpa 3.7

• Award: Undergraduate Scholarship (Top 5%) • Coursework: Software Engineering, Artificial Life, and Complexity Science

FAQ

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What company does David Nader work for?

David Nader works for Microsoft.

What is David Nader's role at Microsoft?

David Nader is listed as Applied Scientist 2 at Microsoft.

Where is David Nader based?

David Nader is based in Williamsburg, Virginia, United States while working with Microsoft.

What companies has David Nader worked for?

David Nader has worked for Microsoft, William & Mary, Cisco, Universidad Nacional De Colombia, and Ksmti.

How can I contact David Nader?

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What schools did David Nader attend?

David Nader holds Doctor Of Philosophy - Phd, Computer Science, Gpa 3.75 from William & Mary.

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