Peter Hussami, Algorithms Developer in Budapest, Hungary
Peter Hussami

Algorithms Developer in Budapest, Hungary

Member since March 15, 2017
Peter is an expert in algorithms and statistics/data science, but his specialty—which few others can deliver—is mathematical modeling. These tasks are often written out in plain language at the start, and he’s good at formalizing these problems, then providing full, working solutions and integrating them (domain expertise in audio analysis/pattern recognition, identity verification, NPL, sensor analysis, scheduling, routing, and credit scoring).
Peter is now available for hire




Budapest, Hungary



Preferred Environment

Python, Linux

The most amazing...

...project I’ve ever worked on was a cool content-based music recognition system, back when nobody else had such a system.


  • Principal Data Scientist

    2015 - PRESENT
    • Created and maintained various statistical models for a lending company—the aim was to automate all aspects of the company's lending operations.
    • Designed and implemented several successful credit risk evaluation models. Notably, I built models that supported big data and they made inferences on heterogeneous records.
    • Designed and implemented statistical identity verification tools (big data style).
    • Built scrapers for various social networks.
    • Developed an OCR-based identity verification module.
    • Made various further prediction models for collection, residence verification, and more.
    Technologies: Linux, Amazon Web Services (AWS), Amazon, Python
  • Freelance Data Scientist

    2018 - 2018
    Knexus Research Corporation (via Toptal)
    • Investigated the possibility of replicating data by generating high-dimensional synthetic clones of the input, under strict differential privacy constraints. The solution was quite successful, the invented method might well be a mathematical novelty.
    Technologies: Statistical Analysis, Python
  • Research Contractor

    2015 - 2017
    Furukawa Electric
    • Built a pilot system for direction detection using sound; specifically in an outdoor setting. The system's intended use is to enhance existing radar technology in the automotive field. Accuracy is lower than that of radar, but audio is a low-cost means to an orthogonal measurement.
    • Developed a solution was able to measure the direction of passing cars, as well as show a consistent direction for the car it was mounted on.
    • Ideated also physical solutions for alleviating wind distortion.
    Technologies: Python, Audio Analysis
  • Researcher

    2015 - 2017
    General Electric
    • Delivered a high-accuracy direction-detection system using sound only.
    • Fused the sound and video sensor data for enhanced motion detection.
    • Built a successful traffic counting and classification system that was able to count passing vehicles and separate buses, cars, and more.
    • Used Python (NumPy) to build the systems.
    Technologies: NumPy, Python, Audio Analysis
  • Algorithm Developer

    2015 - 2015
    • Built natural language models (NLP) for semantic data analysis.
    • Developed automated semantic tagger modules for deriving meaning in the text.
    • Used various algorithm optimization techniques for asymptotic speedup of the semantic search.
    Technologies: Python, Natural Language Processing (NLP)
  • Algorithm Developer and Programmer

    2011 - 2015
    Applied Logic Laboratory
    • Built a syntax parser specifically for searching through English-language patents.
    • Developed an information-rich semantic representation over the parsed syntax.
    • Created a search engine for matching semantic information.
    • Built scrapers and built scraped data into a structured dictionary automatically.
    Technologies: Java, Python, C++, C, Natural Language Processing (NLP)
  • Research Intern

    2006 - 2006
    • Created a server-side log analyzer. The log analyzer's purpose was to predict the identity based on user input.
    • Designed the log analyzer so that it parsed server logs into structured data and estimated their distance—delivering probabilistic results.
    Technologies: C++, C
  • Algorithm Developer and Programmer

    2004 - 2005
    Bioscrypt Corporation
    • Participated in building the company's fingerprint recognition algorithm. The algorithmic work included image cleansing, filtering, and feature extraction.
    • Wrote parts of the matching algorithm.
    • Developed exported APIs to the system.
    • Created test tools.
    Technologies: Embedded C, C++, C
  • Programmer | Inventor

    2000 - 2002
    Connexus Corporation
    • Invented one of the world's first content-based music recognition systems, it came earlier than the current market leader. The system monitored a large number of radio stations (US), to deliver high-accuracy recognition information of the contents, songs, commercials, recorded interviews etc.
    • Designed the system so that it made heavy use of the Fourier transform to convert audio data into a musical score.
    • Wrote fast algorithms that were supplied to match a time sequence of these fingerprints.
    • Built automated management tools for recording and tagging unknown patterns; inserting them into the central database and various other smaller components.
    Technologies: C++, C, Audio Analysis
  • Research Intern

    1998 - 1998
    • Built a pilot program for converting an audio signal into musical notation. The criterion was for the musical score thus derived can be used for regenerating the original signal in a way that humans would still recognize it.
    Technologies: C++, C, Audio Analysis


  • Hungarian Spell Checker

    This is a rule-based syntax parser and spell checker for Hungarian. The purpose is to determine if a compound term is spelled as a single word, separated by a hyphen, or composed of multiple words.

  • How to Approach Machine Learning Problems (Publication)
    How do you approach machine learning problems? Are neural networks the answer to nearly every challenge you may encounter? In this article, Toptal Freelance Python Developer Peter Hussami explains the basic approach to machine learning problems and points out where neural may fall short.


  • Languages

    Python, Python 3, C++, Python 2, SQL, C, Embedded C, R, Java
  • Paradigms

    Data Science, Automation
  • Storage

    MySQL, PostgreSQL
  • Other

    Statistical Analysis, Machine Learning, Artificial Intelligence (AI), Natural Language Processing (NLP), Numerical Methods, Mathematics, Statistics, Algorithms, Big Data, Data Structures, Statistical Modeling, Research, Audio Analysis
  • Frameworks

    Flask, Django
  • Tools

  • Platforms

    Linux, Amazon, Amazon Web Services (AWS)
  • Libraries/APIs



  • PhD degree in Mathematics
    2005 - 2011
    Central European University - Budapest, Hungary
  • Bachelor of Science degree in Mathematics
    1995 - 2000
    Massachusetts Institute of Technology | MIT - Cambridge MA, USA

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