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For more information please visit my own personal homepage: badalyan.it
Hello,
I am a mathematician from Berlin, Germany, and an excited Neural Networks programmer. I wrote my master's thesis on Neural Networks and Differential equations showing that Neural Networks are Differential Equations that help us to use the whole maths theory to find better and more stable Neural Networks being robust against adversarial examples. I love to go inside of the Machine Learning programs and understand every part of it, why it works well or bad and with the help of my immense mathematical understanding to improve it, if necessary. For this, I studied the whole bunch of applied Mathematics: Finite Element Methods, Optimisation Theory, Differential Equations, Statistics and Stochastics. This knowledge picks me up on others who only use the standard machine learning packages and are not able to create really robust and stable networks. Besides of that I love coding and implementing my ideas on Neural Networks if necessary improve Google's Tensorflow or PyTorch by writing APIs if they are not advanced enough. I constantly improve my Machine Learning/Big Data knowledge by active programming and visiting various workshops, seminars and university courses where I am actively discussing methods with my colleagues.
That's about me, I will be thankful for every offer and for every question I will be glad to answer it!
Projekt- und Berufserfahrung
- yuvedoData Scientist AI-DeveloperMEDIZINFebruar 2020 - Heute (4 Jahre und 11 Monate)Berlin, Deutschland-Developing AI for a medicine application which suggests the optimal behavior for the user to reach and boost their goals-Coupling Supervised Learning with Reinforcement Learning to enable online learning of user needs and make instant suggestions to the user-Data Mining, Data Tracking, Data Preparation, and Cleansing-Creation of synthetic data to boost the AI and find the principal architecture of the AI which learns our original data more precise-Check with the synthetic data what is needed to couple the Supervised Learning AI and the Reinforcement Learning AI-Developing the Neural Network for the Supervised Learning with custom losses and custom layers utilizing the efficient architecture of Tensorflow-Developing the Neural Network for the Reinforcement Learning with custom losses and custom layers
- psaichology.orgMain developer of Neural Networks / Data ScientistDIGITALAGENTUREN & IT-CONSULTINGMai 2019 - Heute (5 Jahre und 8 Monate)Berlin, Deutschland-Uebertragung von Teilaspekten der menschlichen Psychologie in die KI : KI-Lernen der psychologischen Modellen des Menschen-Data Analyse/Preparation/Optimierung von psychologischen Daten, strategische Wahl der geeigneten Verfahren, Einsetzen von Trial and Error Methoden-Data Denoising/ Clustering/ Dimensionality Reduction mit statistischen Methoden, sowohl selbstgeschriebener code als auch Benutzung von Statistiklibraries wie PandasData fitting: Design und Aufbau geeigneter Neuronaler Netze, Hyperparametertuning: Einsetzen von modernen automatisierten Tools mittels AutoML um Zeit zu sparen,-Vergleich zwischen verschiedenen Machine Learning Bibliotheken, selbstgeschriebene Neuronale Netze-Erfolgreiche Validierung der Netwerkmodelle, neue Ergebnisse in der Psychologie.
Externe Empfehlungen
Ausbildung und Abschlüsse
- MathematicsHumboldt University of Berlin2019Mathematik an der Humboldt Universität zu Berlin, Abschlussnote 1,0
- PhysicsHumboldt University of Berlin2020