Tileli Amimeur

About Tileli Amimeur

General Skills: •Data-driven, predictive modeling in Python with Keras/Theano/Tensorflow, Pandas, Scikit Learn•Deep learning approaches: GANs, AEs, Transformer-based models, Resnets, CNNs, RNNs, etc.•PCA, PLS, Linear/Logistic Regression, Decision Trees, Clustering, SVMs, etc.•AI algorithms and approaches: Reinforcement Learning, MDPs, POMDPs, Constraint Satisfaction, Planning, Search, etc.•Statistical modeling and parameter inference with Bayesian Inference and Markov Chain Monte Carlo•Modeling of dynamic systems using ODE\'s in Python and Mathematica•Computer vision software in Python with OpenCVML/AI in Biotech:• Created the Antibody-GAN to design customizable human antibody discovery libraries for therapeutic purposes and general antibody research. Preprint HERE: Design of optimized proteins from protein stability data sets using a Deep Neural Net• Automated experimental design of genetic circuits in Synthetic Biology using a Partially Observable Markov Decision Process• Computer vision object detection and tracking in the wetlab using Scale Invariant Feature Transform algorithm• Raspberry PI controlled, vision-based \'colony picker\'(hacked from a RepRap 3D printer) and web control interfaceHardware - Intel:• CPU and SOC Power Management for the Atom Products DivisionSoftware - Bell Labs, Dolby Labs, NASA:• Various projects in networking and embedded systems in C++ and C

Experience

1. Ai Scientist

   Xaira Therapeutics

   May 2025 — Present

Education

• The University of Texas at Austin

  Bachelor's degree, Electrical and Computer Engineering

  2004 — 2008

• The University of Texas at Austin

  Master's degree, Electrical Engineering

  2008 — 2010

Skills

• Verilog
• Matlab
• Data Analytics
• Electrical Engineering
• Algorithms
• Research
• Simulations
• Computer Architecture
• Probabilistic Models
• Software Development
• Python
• Rtl Design
• C
• Vlsi
• Embedded Systems
• Processors
• Soc
• Signal Processing
• Modeling
• C++
• Circuit Design
• Data Analysis
• Machine Learning