Eli Niktab

Eli Niktab Email and Phone Number

Applied Machine Intelligence Fellow @ The Australian National University
Canberra, ACT, AU
Eli Niktab's Location
Canberra, Australian Capital Territory, Australia, Australia
Eli Niktab's Contact Details

Eli Niktab personal email

About Eli Niktab

I have research experience in academic, policy making, clinical, and industrial settings, specializing in exploring multi-feature data (particularly omics) through in silico, in vitro, and in vivo methodologies. My primary interests include Applied AI for Health, Stochastic Modeling of Heterogeneous Systems, Manifold Learning for Regulatory Networks, and Functional Genomics.

Eli Niktab's Current Company Details
The Australian National University

The Australian National University

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Applied Machine Intelligence Fellow
Canberra, ACT, AU
Eli Niktab Work Experience Details
  • The Australian National University
    Applied Machine Intelligence Fellow
    The Australian National University
    Canberra, Act, Au
  • The Australian National University
    Applied Artificial Intelligence Scientist
    The Australian National University Aug 2024 - Present
    Canberra, Australian Capital Territory, Australia
  • Ai-Omics
    Founder
    Ai-Omics Sep 2023 - Present
    Wellington, New Zealand
    Our advanced AI algorithms analyze individual genomes to provide tailored recommendations for optimal health management and the most effective chemotherapy regimens.
  • Callaghan Innovation
    Ai Research Scientist
    Callaghan Innovation Mar 2021 - Aug 2024
    Wellington Region, New Zealand
    https://www.callaghaninnovation.govt.nz/people/our-people/eli-niktab/>> Led the Precision Medicine initiative at CI resulted in proprietary algorithms.>> Implemented solutions using Neo4j graph databases that significantly reduced search time on the customer's data, enabling the introduction of new services and further R&D.>> Developed knowledge bases using graph neural networks on TensorFlow and Google JAX platforms. >> Developed NLP models based on Large Language Models (LLMs) and LangChain for applications requiring advanced text analysis. Notably, I implemented LLMs for protein structure analysis.>> Developed petabyte-scale search/retrieval data solutions and genome-scale algorithms for genomic analysis on GPU-accelerated hardware, reducing analysis time from days to hours.>> Developed advanced statistical analysis and physics-informed deep learning models for signal processing, enabling inference on edge devices in the field.>> Developed real-time inference object-tracking algorithms.>> Assisted organizations across diverse sectors with data solution architectures, ensuring best practices in MLOps and the Team Data Science Process.>> Reviewed grant applications for government research and development funding schemes.
  • 4Omix
    Principal Technical Consultant
    4Omix Feb 2023 - Jul 2024
    >>Disease Prediction, Protein–protein interactions, Sequencing and metabolic pathways analysis.
  • Ministry Of Education Of New Zealand
    Senior Data & Applied Scientist
    Ministry Of Education Of New Zealand Jan 2020 - Mar 2021
    Wellington, New Zealand
    >> Designed the data science project life-cycle and standardized project structure within the Analytic and Insight team.>> Mentored and trained analysts to adopt machine learning methodology and ingrain data science techniques in their research and evaluation pipelines to ensure delivery of reliable, fast, and robust insights.>> Trained staff on best programming practices (e.g., version control systems, writing processable technical documentation). >> Led MoE’s Initiative to develop an in-house natural language processing (classification, summarization & business insight generation) suite of software that is capable of handling the Maori language.>> Participated in the design and implementation of the world-class database solutions used during the New Zealand national Covid-19 pandemic lockdowns to provide every student in need with devices and connectivity. >> Migrated MoE’s legacy payroll data to a new solution capable of fuzzy matching, anonymizing, cleaning, and integrating data in a range of downstream analyses.
  • Ministry Of Education Of New Zealand
    Data Scientist
    Ministry Of Education Of New Zealand Sep 2019 - Dec 2019
    Welington
    >> Data wrangling, time series forecasting, cohort analysis, and data visualization for various projects, including New Zealand's school-wide Positive Behaviour for Learning and Learning support.>> Performed a battery of qualitative research using New Zealand’s Integrated Data Infrastructure (IDI) that holds microdata about life events, like education, income, benefits, migration, justice, and health of every New Zealander and wrote detailed reports for the sector and the stakeholders. >> Worked with the Workforce task group to identify and model New Zealand’s teacher recruitment and retention.
  • New York University
    Research Scientist
    New York University Oct 2018 - Sep 2019
    >> Research and statistical modeling. >> Modeled breast cancer susceptibility from proteogenomics data.Python, C/C++, SQL, Bash, gcloud CLI, Docker CLI NYU HPC, GCP, CentOS, Slurm, Tensorflow, Keras, Abseil, Protobuf, CUDA, Bazel, Singularity, Git
  • Asurequality
    Science Technician Ii
    Asurequality Jan 2018 - Dec 2018
    Wellington & Wairarapa, New Zealand
    >> ELISA development, optimization, and analysis for the New Zealand Mycoplasma Bovis response team.
  • Victoria University Of Wellington
    Teaching Assistant
    Victoria University Of Wellington Feb 2018 - Nov 2018
    Wellington, Wellington Region, New Zealand
    >> Taught and tutored R, Advanced Genetics and Physiology to second and third-year university students.
  • Victoria University Of Wellington
    Graduate Research Assistant
    Victoria University Of Wellington Jul 2015 - Dec 2017
    Wellington
    >> Designed genome-scale algorithms and implemented machine learning methods (eg. feature extraction and classification) for analysis of next-generation sequencing data. >> Developed software for cellular image analysis.>> Modeled genetic polymorphisms using deep learning, Bayesian heuristics, and applied various statistical and mathematical models to big biological data.Python, C/C++, Matlab, SQL, R, Perl, Docker CLI NeSI & Rāpoi HPC, Debian OS, Numpy, Tensorflow, Keras, BLAST, CUDA, Bazel, Git
  • Naenae College
    Teaching Assistant
    Naenae College Jul 2016 - Sep 2016
    Wellington & Wairarapa, New Zealand
    Tutored high school level chemistry.

Eli Niktab Skills

Molecular Biology Genetics Python R Latex Dynamic Modeling For System Biology Matlab Data Analysis Dna Sequencing Machine Learning Scikit Learn Elisa Keras Snp Genotyping Yeast

Frequently Asked Questions about Eli Niktab

What company does Eli Niktab work for?

Eli Niktab works for The Australian National University

What is Eli Niktab's role at the current company?

Eli Niktab's current role is Applied Machine Intelligence Fellow.

What is Eli Niktab's email address?

Eli Niktab's email address is ma****@****hoo.com

What skills is Eli Niktab known for?

Eli Niktab has skills like Molecular Biology, Genetics, Python, R, Latex, Dynamic Modeling For System Biology, Matlab, Data Analysis, Dna Sequencing, Machine Learning, Scikit Learn, Elisa.

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