About me
Hi, I'm Samuel. I am a research fellow at Harvard in Prof. Prineha Narang's group, and a Ph.D. student at MIT (Massachusetts Institute of Technology) in Electrical Engineering and Computer Science. I am also a founding parter of my startup Assist-o, offering personal and professional assistants to business people and small companies. I currently spend most of my time in Cambridge, Massachusetts, but often travel around. My main areas of interest are Machine Learning and Quantum Computing, in which I have eight publications and one pending patent.
I am originally from Germany but spent almost all of my life in other countries (the US being my 9th). When I was 5 years old, my family moved to Croatia through a German NGO, to help with post-war reconstruction. There I finished elementary and high school. I also went to school in South Africa for a while, as an exchange student. After graduating from high school, I worked as a volunteer teacher in an orphanage in Kenya, near Nairobi, where I started a small coding school program for disadvantaged children.
During my undergraduate studies, I worked in Ice & Climate research at the Niels Bohr Institute, at the University of Copenhagen in Denmark (see publications). Afterwards, I joined the hedge fund D. E. Shaw & Co. in London and New York City for a while, where I created computer simulations of the bond and foreign exchange market. Before starting my master's degree at EPFL, I spent some time in the sunny and picturesque city of La Jolla, at University of California in San Diego. There, I worked on Machine Learning research (see publications) and enjoyed surfing in the Pacific Ocean.
Since September 2018, I am studying Physics and Data Science at EPFL in Switzerland. As a research assistant, I work in the group of Prof. Giovanni De Micheli on Quantum Computing. I am also the founder and former president of the EPFL Quantum Computing Association and former vice-president of the Debate and Model United Nations association. In the Summer 2019, I worked at the National University of Singapore on Quantum Optimization Algorithms, with applications in finance.
Since February 2020, I work in Prof. Prineha Narang's group at Harvard on Near Term Quantum Algorithms for Optimization Problems. I am starting my Ph.D. in August 2020 at MIT!
Watch my TEDx talk from October 2019 at EPFL
CV
EDUCATION
Starting 2020
MIT (Massachusetts Institute of Technology), USA
- Incoming Ph.D. Student
- Department of Electrical Engineering and Computer Science
2018 - 2020
EPFL (École polytechnique fédérale de Lausanne), Switzerland
- Master of Science: Physics & Data Science
- Master thesis at Harvard University (02/2020 – 08/2020)
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- Graduate School of Arts and Sciences – Prof. Prineha Narang’s group
- Thesis topic: Near Term Quantum Algorithms for Optimization Problems
- EPFL Excellence Fellowship (best master’s students in the physics department)
- GPA 5.5/6.0 (top ≈ 5%)
- Specialization: Quantum Computing & Machine Learning
- Associations and Societies:
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- Founder and President of the Quantum Computing Association
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- Member of the German Academic Scholarship Foundation (Studienstiftung)
2014 - 2017
University of Zagreb, Croatia
- Undergraduate studies: Physics
- Final GPA: 4.9/5.0
- Elected as Student Representative in 2017
- Associations and Societies:
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- Founder of the Debate Society (politics, philosophy, economy, ...)
- Member of the German Academic Scholarship Foundation (Studienstiftung)
2010 - 2014
XV. High school (MIOC), Zagreb, Croatia
- Focus on Physics, Math and CS
- International Physics Olympiads (IPhO): Kazakhstan 2014, Denmark 2013 and Estonia 2012: 3x Bronze Medal
- Award for the best high school graduate in Croatia in 2014 (out of ~40 000 students)
WORK EXPERIENCE
April 2020
Assist-o, Switzerland & USA (Founder, Owner)
- Assist-o is a new and exclusive personal and professional assistant service for busy people and small companies. Check out our website: assist-o.com
- Assist-o AG in Switzerland and Assist-o LLC in Massachusetts
Summer 2019
National University of Singapore (Visiting Researcher)
- Research in Quantum Optimization Algorithms
- Work at the Centre for Quantum Technologies in the group of Dr. Patrick Rebentrost and Prof. Miklos Santha
Since 2019
EPFL, Lausanne, Switzerland (Research Assistant)
- Implementation of optimization and logic synthesis algorithms for Qiskit-Terra (an open source Python library for Quantum Computers maintained by IBM)
- Work in the group of Prof. Giovanni de Micheli and Dr. Mathias Soeken
Since 2018
University of California San Diego, USA (Visiting Researcher)
- 4 publications (ISLPED 2019, BioCAS 2019, ICCAD 2019, TCAD 2019) & 1 further submitted paper
- Machine learning research: Development of fast and energy efficient algorithms for specialized computer architecture
- Optimization of algorithms for Natural Language and Human Activity Recognition
2017 - 2018
EPFL, Lausanne, Switzerland + Technical University Vienna, Austria (Internship)
- Solid State physics research: discovering and analyzing new materials
- Work on Quantum Cryptography algorithms
2016
D. E. Shaw & Co., London, UK & New York City, USA
- Monte Carlo simulations of complex derivatives in Python
- Modeling changes in the foreign exchange and bond market
2015
Niels Bohr Institute, University of Copenhagen, Denmark (Research Internship)
- 1 publication (Climate of the past) & 1 further publication in progress
- Data analysis/data mining in Climate science
2014 - 2017
University of Zagreb, Croatia (Student assistant, Physics competitions)
- Organization of the preparations for the International Physics Olympiad
- 2 of my students won bronze medals at the International Physics Olympiad and received full scholarships for their studies at University of Cambridge
- Teaching Physics I & II: Classical Mechanics, Electromagnetism (~80 students)
2014
Mully Children’s Family Orphanage, Kenya (Volunteer work)
- Taught computer programming, mathematics and physics to 125 high school students
- Organized programming courses for students, to give them a chance to see what programming is and motivate them to pursue a career in it, as it requires few resources
Until 2015
Music performance and recording of CDs
- Participated as a singer on 3 CD recordings for humanitarian purposes
- Participated in 15 humanitarian musicals and concerts as an actor, singer or technician
COMPETITIONS & AWARDS
2019
1st place at the IBM Qiskit Camp Europe Hackathon 2019
- Qiskit – PyTorch integration for Machine Learning
- Project available on GitHub
Since 2018
EPFL Excellence fellowship
- Awarded to the best master’s students of every department (less than 1%)
Since 2017
Studienstiftung des deutschen Volkes (German Academic Scholarship Foundation)
- Awarded to the best ~0.5% students in/from Germany
- The selection is based on excellent academic records, social engagements, rhetorical and social skills, academic and sport competitions, and other personal accomplishments.
2014
Award for the best high school graduate in Croatia in 2014 (out of ~40 000 students)
- Selection was based on final exam results, science and sport competitions and social commitment
2014
Bronze medal at the 45th International Physics Olympiad 2014 (Kazakhstan)
2014
1st place at the Croatian National Physics Competition
2013
Bronze medal at the 44th International Physics Olympiad 2013 (Denmark)
2013
1st place at the Croatian Championship in Triathlon
2012
Bronze medal at the 45th International Physics Olympiad 2012 (Estonia)
LANGUAGES
English
Full professional proficiency
German
Bilingual proficiency
Croatian
Bilingual proficiency
French
Elementary proficiency
PUBLICATIONS
PUBLICATIONS (peer reviewed)
11/2019
QuantHD: A Quantization Framework for FPGA Acceleration of Hyperdimensional Computing
- Journal: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD)
- M. Imani, S. Bosch, S. Datta, S. Ramakrishna, S. Salamat, J. M. Rabaey, T. Š. Rosing
- Research done at University of California, San Diego
- Contribution: QuantHD is a Machine Learning algorithm which can achieve very significant improvements in terms of energy-efficiency and speed, without losing classification accuracy as compared to low-cost state-of-the-art Machine Learning algorithms
- My contribution: I developed large parts of the algorithm, coded the entire software part, developed the underlying mathematics and wrote parts of the paper
- Topic of my TEDx talk at EPFL: go.epfl.ch/TED
11/2019
SemiHD: Semi-Supervised Learning Using Hyperdimensional Computing
- Conference: IEEE/ACM International Conference On Computer Aided Design (ICCAD)
- M. Imani, S. Bosch, M. Javaheripi, B. Rouhani, X. Wu, F. Koushanfar, T. Š. Rosing
- Research done at University of California, San Diego
- Contribution: We developed a new semi-supervised Machine Learning algorithm. We noticed a significant increase in performance, as compared to state-of-the-art algorithms.
- My contribution: I was responsible for coding the entire project, improving the mathematical algorithm and testing it against other state-of-the-art algorithms
10/2019
AdaptHD: Adaptive Efficient Training for Brain-Inspired Hyperdimensional Computing
- Conference: IEEE Biomedical Circuits and Systems (BioCAS)
- M. Imani, J. Morris, S. Bosch, H. Shu, G. De Micheli, T. Š. Rosing
- Research done at University of California, San Diego and EPFL, Lausanne
- Contribution: Improvement to previous Hyperdimensional computing-based Machine Learning algorithms by introducing adaptive learning rates. We managed to significantly decrease the convergence time during training.
- My contribution: I was the first person to introduce the concept of learning rates in HD computing and performed the initial tests with adaptive learning rates. My colleagues at UCSD developed the rest of the project and wrote the paper.
07/2019
CompHD: Efficient Hyperdimensional Computing Using Model Compression
- Conference: IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED)
- J. W. Morris, M. Imani, S. Bosch, B. L. Baxter, H. Shu, T. Š. Rosing
- Research done at University of California, San Diego
- Contribution: We invented an algorithm for ultra-low-power devices with limited memory to perform offline Machine Learning. It does so by compressing multiple vectors into just one vector by encrypting them with randomized vectors, and then decrypting them during inference.
- My contribution: I was responsible for coding most of the project and improving the mathematics and statistics behind the algorithm. I invented an orthogonalization method, which significantly improved the classification accuracy by decreasing the influence of noise caused by the randomness.
05/2018
Particle shape accounts for instrumental discrepancy in ice core dust size distributions
- Journal: Climate of the Past / European Geosciences Union
- M. F. Simonsen, L. Cremonesi, G. Baccolo, S. Bosch, B. Delmonte, T. Erhardt, H. A. Kjær, M. Potenza, A. Svensson, P. Vallelonga
- Research done at the Niels Bohr Institute, University of Copenhagen
- Contribution: Significant progress in measurement techniques for ice and climate science.
- My contribution: I was the first person to have had a detailed look into the dust particle size distribution from ice cores from the North Pole. I found out that laser measurement techniques used for the past 20 years have been very inaccurate. My colleagues theoretically and experimentally confirmed this and wrote the paper on it.
PUBLICATIONS (currently under peer review)
2020
Quantum polar decomposition algorithm
- arXiv:2006.00841
- Submitted to the PRL
- S. Lloyd, S. Bosch, G. De Palma, B. Kiani, Z. Liu, M. Marvian, P. Rebentrost, D. M. Arvidsson-Shukur
- Research done at MIT & Harvard
- Contribution: We developed a quantum polar decomposition algorithm, which can be used for performing quantum machine learning on quantum data (learning unitaries)
2020
A Stochastic Acceleration Method for HD Computing-Based Machine Learning
- arXiv:1911.12446
- Submitted to the IEEE Design Automation Conference (DAC)
- S. Bosch, A. Sanchez de la Cerda, M. Imani, T. Š. Rosing, G. De Micheli
- Research done at EPFL
- Contribution: We developed a new stochastic retraining method for improving the classification accuracy of HD computing-based Machine Learning algorithms which decreases the convergence rate during training by 50% and improves the overall classification accuracy of the algorithm.
- My contribution: I invented the algorithm, developed the theory and wrote the paper. The algorithm was implemented and evaluated by my colleagues at EPFL and UCSD.
2019
- arXiv:1912.06105
- E. Gårding, N. Schwaller, S. Chang, S. Bosch, W. R. Laborde, J. N. Hernandez, C. L. Chan, F. Gessler, X. Si, M. A. Dupertuis, N. MacrisResearch done at EPFL
- Contribution: We developed efficient circuits for measuring entanglement and discord of quantum states and implemented them on IBM quantum computers.
- My contribution: I co-organized the research project with the EPFL Quantum Computing Association, wrote two sections of the paper and helped with the theory and implementation on real IBM quantum computers.
DRAFTS (> 90% of the work completed)
2019
Convex Optimization Algorithms for Quantum Computers with Applications in Computational Finance
- P. Rebentrost, S. Bosch, S. Lloyd
- Research done at CQT, NUS and MIT
- Contribution: We exhibit a quantum algorithm for solving convex optimization problems by exploiting game theory and quantum chemistry algorithms.
- My contribution: I helped developing parts of the algorithm and tested it. Also, I worked on the underlying mathematical theory and helped with the applications in finance.
- I presented the preliminary results in the IWQC workshop at the ICCAD conference 2019.
- Topic of my seminar talk at Stanford University (Gates CS building) in November 2019 (hosted by Prof. Subhasish Mitra).
SELECTED MEDIA APPEARANCES
* The following articles are in Croatian, so You might need to use Google Translate to understand them.
Dnevnik nove TV (the most watched news program in Croatia)
Dobro jutro, Hrvatska (the most watched morning program in Croatia)
projects
COMPLETED PROJECTS
2019
Circuit optimization algorithms for Quantum Computers (Qiskit)
- Implementation of optimization and logic synthesis algorithms for Qiskit-Terra: an open source Python library for Quantum Computers maintained by IBM
- Work in the group of Prof. Giovanni de Micheli and Dr. Mathias Soeken at EPFL
- My pull requests and contributions can be found on GitHub
2019
Numerical simulations of quantum devices on high performance clusters
- Work at EPFL in the group of prof. Tobias Kippenberg
- Parallelization of simulations on large computing clusters
2018
Text Sentiment Classification
- We developed an algorithm which can analyze the meaning of Tweets
- Using TensorFlow, Keras & GloVe
2018
Inverse statistical methods for protein simulations
- Work at EPFL in the group of prof. Paolo De Los Rios (supervisor dr. Stefano Zamuner)
- Project available on GitHub