Haris Jabbar
Founder at SuperPandas
Munich, Bavaria, Germany
Summary
👤
Senior🎓
Top SchoolHaris Jabbar is a founder and NLP specialist based in Munich with a decade of experience bridging academic research and product-focused machine learning. He has worked on large language models since before they were mainstream, contributing as a PhD researcher and scientific researcher at leading German universities and now founding SuperPandas to productize that expertise. His background blends rigorous academic training in computational science and data science with hands-on industry roles—from building predictive finance applications at Siemens to winning a Tetra Pak hackathon that led to a commercial engagement. Comfortable moving models from research to production, he has particular experience making transformer models more efficient. Colleagues describe him as mission-driven about practical uses of LLMs and unusually persistent in uncovering incremental gains that materially improve system performance.
10 years of coding experience
6 years of employment as a software developer
Online Courses, Data Science, Online Courses, Data Science at DataCampMaster's degree, Computational Science, 1.8, Master's degree, Computational Science, 1.8 at Technical University of MunichLudwig Maximilian University of MunichExchange Student, Neuroscience, 5/6, Exchange Student, Neuroscience, 5/6 at Ecole polytechnique fédérale de LausanneMaster of Science (MSc), Computational Science and Engineering, Master of Science (MSc), Computational Science and Engineering at Technische Universität MünchenMSc, Computer Engineering, 4.00/4.00, MSc, Computer Engineering, 4.00/4.00 at University of Engineering and Technology, Taxila
Urdu, English
Stackoverflow
1reputation
0reached
1answer
0questions
Github Skills (167)
transformers10
language-model10
python10
dialog10
datasets10
deep-learning10
speech10
latex10
ai10
computer-vision10
transformer10
evaluation-framework10
nlp10
multiclass-classification10
lightning10
Programming languages (7)
Github contributions (5)
morphpiece/lm-evaluation-harness
Jun 2024 - Nov 2024
A framework for few-shot evaluation of language models.
Contributions:7 pushes in 4 months
MaveriQ/barlowtwins
May 2021 - Oct 2021
PyTorch implementation of Barlow Twins.
Contributions:2 PRs, 18 pushes, 2 branches in 4 months
pytorchbarlow-twinsdeep-learningtwinspytorch-implementation
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