curriculum vitae

Carnegie Mellon University – Ph.D. in Machine Learning

• Co-advised by Prof. Tom Mitchell and Dr. Barnabàs Pòczos
• GPA: 4.0 (4.0 scale)
• Thesis: Curriculum Learning
• Thesis committee: Tom Mitchell, Barnabàs Pòczos, Ruslan Salakhutdinov, Rich Caruana

Carnegie Mellon University – M.S. in Machine Learning

• Co-advised by Prof. Tom M. Mitchell and Dr. Barnabàs Pòczos
• GPA: 4.0 (4.0 scale)
• Thesis: Understanding the Neural Basis of Speech Production Using Machine Learning
• Master’s degree requirements completed while working towards obtaining my Ph.D.

University of Cambridge – Master of Philosophy (M.Phil.) in Advanced Computer Science

• Advised by Prof. Pietro Lió
• Thesis: Machine Learning Methods for Computational Microscopy
• Grade: Pass with Distinction

Linköping University – Erasmus Exchange Student

• I spent the third year of my undergraduate studies as an Erasmus exchange student at Linköping University, Sweden

Politehnica University of Timisoara – B.Eng. in Computer Science and Information Technology

• GPA: 9.98 (scale 10.0)
• 1^st out of 140 students

Senior Research Scientist at Google AI

• Mountain View, CA, USA

Research Scientist at Google AI

• Mountain View, CA, USA

Software Engineering Intern at Google Research

• Expander team in Google Research , Mountain View, CA, USA
• Research on deep learning models for graph-based semi-supervised learning, published at NeurIPS 2019.

Software Engineering Intern at Google X

• Self-Driving Car team in Google X (current Waymo), Mountain View, CA, USA
• Undisclosed Machine Learning projects for the Google self-driving car.

Software Developer Intern at Microsoft

• Cortana team at Microsoft Corporation, Redmond, WA, USA
• Undisclosed Machine Learning project for Cortana, Windows’ digital personal assistant.

Independent Research Project in Computer Vision

• Advised by Dr. Marius Leordeanu
• Unsupervised object discovery in video based on multiple frames matching. We also proposed a fast method for detecting the main object of interest in a video, titled VideoPCA. Published at BMVC 2015.

Research Internship in Machine Learning at EPFL

• Laboratory for Probabilistic Machine Learning at École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
• Advised by Dr. Matthias Seeger
• Used topic models to explore the correlation between social media messages from Twitter and the location of the users, with applications to user profiling, topic tracking and content recommendation. I was responsible with applying various machine learning models and parallelizing the code in order to scale well.

Research for Undergraduates Program

• Politehnica University of Timisoara, Romania
• Advised by Prof. Emilia Petrisor
• Implemented algorithms for spectral clustering of nodes in a graph, based on minimum graph cut, with applications to data mining and statistics, such as clustering information from documents on the web and medical images segmentation.

• Center for Machine Learning and Health (CMLH) Fellowship in Digital Health (2018)

• Gates Cambridge Scholarship (2014)
• Google Anita Borg Memorial Scholarship (2013)
• GE (General Electric) Foundation Scholar Leaders Program (2012)

• Best poster award at the Eastern European Machine Learning Summer School in Bucharest, Romania (2019)
• Machine Learning Department Teaching Assistant Award (2018)
• Carnegie Mellon University Neurohackathon: 2^nd place (2017)
• KTH University Programming Challenge, Sweden: Top 10 contestants (2013)
• ACM International Collegiate Programming Contest (ACM-ICPC): Honorable Mention in Southeastern European Regional (2013, 2012, 2011)
• Microsoft Imagine Cup:
  • Top 20 in the World Finals (2012)
  • 1^st team in the Romanian National Finals (2012)
• Romanian National Olympiad in Informatics:
  • Gold Medal: 2008
  • Bronze Medal: 2010
  • 1^st Place: 2004
  • 2^nd Place: 2005
  • Honorable Mention: 2010, 2008, 2007, 2003
• Kangaroo International Mathematical Competition: 2^nd prize in Romanian National Finals (2009, 2010)

Teaching Assistant for Graduate Machine Learning

• Graduate level introduction to machine learning class 10-701 Graduate Machine Learning at Carnegie Mellon University
• Taught by Prof. Pradeep Ravikumar and Prof. Manuela Veloso
• I was awarded a Machine Learning Department Teaching Assistant Award

Teaching Assistant for Topics in Deep Learning

• Graduate level deep learning class 10-707 Topics in Deep Learning at Carnegie Mellon University
• Taught by Prof. Ruslan Salakhutdinov

Teaching algorithms for competitive programming

• Co-organized a competitive programming seminar at Politehnica University of Timisoara for university and high-school students interested to train for algorithmic competitions (e.g. ACM-ICPC, informatics olympiad).
• Taught algorithms and data structures used in competitive programming, designed and solved practice problems and internal competitions.

LiveX Learning Platform

• Tutoring system for kindergarten and school children based on a software platform that runs in the cloud, Windows Phone 7 devices and a set of electronic learning cubes called “IQubes” (our hardware invention).
• Project proposed by our team, called IQube, that competed in the world finals of the Microsoft Imagine Cup competition.

Face and Hand Gesture Recognition for Human - Computer Interaction

• Framework for C++ developers to extend their graphical user interfaces with more natural means of communication.
• Works in real-time using a computer web camera.

Public Transport Route Recommendation

• Python application for the Timisoara city public transport system using real-time information from GPS devices installed on public transport vehicles.
• Overlays optimal routes suggestions on Google Maps (before they supported such a feature).

Handwritten digits recognition

• C library implementing various linear algebra methods.

• Mentorship:
• - Mentor for the CMU AI mentoring program (2019 - now)
• - Mentor for first year PhD students at CMU (2019 - now)

• Organized a workshop on Adaptive & Multitask Learning at ICML 2019.

• Founding member of the AI+ Club at Carnegie Mellon University (CMU).

• I was a reviewer for the following journals, conferences and workshops: ICML (2019), AISTATS (2019, 2020), ICLR (2018, 2020), ICLR-LLD (2019), PLOS ONE (2019), ICML-GRL (2020), NeurIPS (2020), AAAI (2021).

• Treasurer of the Romanian Students Association at CMU.

• Member of the Doctoral Review Committee of the Machine Learning Department at CMU.

• Member of the Education Review Committee of the Machine Learning Department at CMU, which aims to improve the PhD program.

• President of the Romanian Students Association at CMU.

• Student representative in the faculty leadership board at Politehnica University of Timisoara.

• Volunteer for AIESEC, international youth organization.

• Volunteer for Liga AC, student organization at Politehnica University.