PhD Student at ETH Zürich | Former Intern @ Google, Microsoft, Amazon
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
https://armandnicolicioiu.github.io/
ETH Zürich
Doctor of Philosophy - PhD
October 1, 2024 – Present
University of Bucharest
Master of Science - MS, Artificial Intelligence
January 1, 2020 – January 1, 2022
University POLITEHNICA of Bucharest
Bachelor's degree, Computer Science and Engineering
January 1, 2015 – January 1, 2020
ETH Zürich
Doctoral Student
October 1, 2024 – Present
Zurich, Switzerland
Institute of Science and Technology Austria
Research Intern
March 1, 2024 – August 1, 2024
Viena, Austria
ETH Zürich
Research Intern
October 1, 2023 – January 1, 2024
Zurich, Switzerland
Idiap Research Institute
Research Intern
May 1, 2023 – September 1, 2023
Martigny, Valais, Switzerland
Amazon Web Services (AWS)
Software Development Intern
November 1, 2022 – March 1, 2023
Tübingen, Baden-Württemberg, Germany
Software Engineering Intern
June 1, 2022 – September 1, 2022
Zurich, Switzerland
.lumen - Empowering the Blind
Machine Learning Researcher
October 1, 2020 – October 1, 2021
Microsoft
Software Engineering Intern
July 1, 2019 – September 1, 2019
Redmond, WA, United States
Microsoft
Software Engineering Intern
July 1, 2018 – September 1, 2018
Redmond, WA, United States
Arnia Software
Machine Learning & Computer Vision Junior Researcher
January 1, 2017 – November 1, 2017
București, România
Sparktech Software
Machine Learning Engineer Intern
July 1, 2016 – October 1, 2016
București, România
Politehnica University of Bucharest
Multi-Agent Systems and Learning Agents Summer School
June 1, 2016 – June 1, 2016
București, România
Smart Quiz Bot for Self-Learners
July 1, 2020 – July 1, 2020
• Implemented a Quiz Bot that generates questions out of any technical book to help students that were forced to become self-learners. • Developed during Microsoft's Silver Lining Coding Challenge, a 2-days hackathon for students whose internship got cancelled due to the Covid-19 pandemic.
Few shot learning by features adaptation with Graph Neural Networks
January 1, 2020 – Present
• Final thesis for my Bachelor's degree. • Research in meta-learning and few-shot classification using Graph Neural Networks and Attention mechanisms. • Presented at EEML 2019 Summer School, winning the best Deep Learning poster award. • Implemented in PyTorch. Code: https://github.com/ArmandNM/meta-learning
Genre Classification from Lyrics
December 1, 2019 – December 1, 2019
• 1st place winner hackathon project built in a team of two using NLTK and Tensorflow. • Applied Natural Language Processing techniques to predict the genre of a song based only on the lyrics. • As a bonus task, we tried to predict the Billboard top 100 using a siamese neural network that would predict which one of two songs would be more succesful.
Webcam hand tracker
November 1, 2016 – Present
• Captures hand motion from the webcam and uses Python with OpenCV for processing. • We were able to move the cursor precisely and click only with hand gestures. • Also implemented an on-screen keyboard.
Server Client Application
August 1, 2015 – Present
● Built in highschool as a personal project ● The application uses TCP/IP protocol and is implemented in C# ● Sends data between the server and the clients or between two different clients ● Has integrated GUI, making it user friendly
Cultural Fit Analysis
The candidate's profile shows a strong inclination towards research and cutting-edge AI/ML applications, which could be a good fit for an innovative, data-driven culture. The diverse project portfolio, including personal projects and hackathon wins, demonstrates initiative and a passion for technology beyond formal roles. However, the primary focus on research and software engineering internships, rather than dedicated data analyst roles, suggests a potential gap in direct experience with typical business intelligence, reporting, or stakeholder communication aspects often required in a Data Analyst role. The candidate's profile leans more towards a Machine Learning Engineer or Research Scientist than a traditional Data Analyst.
Soft Skills & Operational Fit
The candidate's project descriptions and experience highlight a proactive, research-oriented individual with a strong drive for problem-solving and innovation. Participation in hackathons and winning awards suggests a competitive spirit and ability to deliver under pressure. The focus on research and academic pursuits indicates a preference for deep, analytical work, which aligns well with complex data analysis challenges. The variety of internships across different companies and research institutes suggests adaptability and a willingness to learn new environments and technologies.