Mikhail Gorelkin
1612 Worcester Rd, Apt. 204A, Framingham, MA 01702
mikhail@gorelkin.com
SUMMARY
Principal AI Scientist, Mathematician, and Engineer with over 19 years of experience delivering AI and Generative AI solutions to global businesses and early startups. Proven track record of applying cutting-edge research to solve complex real-world problems across industries, improving production systems and creating competitive advantages for businesses.
KEY SKILLS
- Artificial Intelligence, Natural Language Processing, Machine Learning, Deep Learning, Graph Neural Networks, Reinforcement Learning, Probabilistic Programming, Automated Decision Making
- Generative AI / LLMs and Agentic AI
- Data Science, Forecasting, Optimization, Recommender Systems
- Complex Systems, Multi-Agent Modeling
- Mathematical Modeling, Algorithms
- AI Marketing
- Python, C++, C#, Scala, Julia, SQL, scikit-learn, TensorFlow / Keras, PyTorch, spaCy, Hugging Face, LLMs / Transformers, AutoGen, LangChain, Faiss, Pinecone, Weka, PySpark, Mesa, Akka, Pyro, PyMC 5, Google Colab, Amazon SageMaker, Amazon EC2 / Linux, GitHub Copilot.
MY CUSTOMER LIST INCLUDES
- Visa, Ford, ServiceNow, Deloitte, Boston Consulting Group, Fractal Analytics, IEEE, Scientific Systems Company, AES, Celsius, airSlate, ADΣXT, NOHOLD, Boston Biotech Clinical Research
EXPERIENCE
AI Consultancy, Boston, MA 04.2005 – current
Principal AI Scientist | Mathematician | Engineer
- Leveraging cutting-edge research, designing, and developing AI solutions to tackle complex business challenges for Fortune 500 companies and startups. Improving the effectiveness of existing production systems.
- Generative AI / LLMs and Agentic AI: fine-tuning open-source LLMs with DPO, merging LLMs, creating Mixture of Experts, extending LLMs with RAG, optimizing LLMs for production inference, and developing LLM-based multi-agent systems with MS AutoGen.
Compuware Corp., Technology Department, Detroit, MI 03.2000 – 11.2004
Software Developer VII
- Researched and developed many advanced features for QALoad (automated performance and scalability testing software), which allowed the company to acquire many big clients like Bank of America from competitors. Prepared a paper for publication on discovering server scalability bottlenecks based on the Kruskal-Wallis test and modified Hodges-Lehmann estimators for statistical modeling.
EDUCATION
Voronezh State University,Voronezh, Russia
Master of Science, Mathematics
- Focused on Topological Methods in Nonlinear Functional Analysis.
CONTINUING EDUCATION WITH CERTIFICATION
- AI Agentic Design Patterns with AutoGen, Microsoft & Penn State University, 2024
- Train & Fine-Tune LLMs for Production, Intel, 2023
- Quantum Computation using Qiskit v0.2X, IBM, 2022
- Quantum Computing, Coursera / Saint Petersburg State University, 2021
- Algorithmic Information Dynamics, Santa Fe Institute, 2018
- Parallel Programming, Coursera / École Polytechnique Fédérale de Lausanne, 2017
- Text Mining and Analytics, Coursera / University of Illinois at Urbana-Champaign, 2015
- Statistical Learning, Stanford University, 2014
- Mining Massive Datasets, Coursera / Stanford University, 2014
- Decision Making in a Complex & Uncertain World, Futur earn / University of Groningen, 2014
- Data Mining with Weka. Parts 1 & 2, University of Waik o, 2014
- Big Data and Social Physics, edX / MIT, 2014
- Introduction to Dynamical Systems and Chaos, Santa Fe Institute, 2014
- Introduction to Complexity, Santa Fe Institute, 20
- Game Theory, Coursera / Stanford University, 2013
- Natural Language Processing, Coursera / Columbia Uni rsity, 2013
- Algorithms: Design and Analysis. Parts 1 & 2, Courser / Stanford University, 2013
- Machine Learning, Coursera / Stanford University, 2012
- Model Thinking, Coursera / University of Michigan - Ann rbor, 2012
CONTINUING EDUCATION WITHOUT CERTIFICATION
- Categories for AI, DeepMind, 2023
- Introduction to Quantum Computing & Quantum Machine Learning, IBM, 2022
- Introduction to Agent-Based Modeling, Santa Fe Institute, 2020
- Bayesian Methods for Machine Learning, Coursera / National Research University Higher School of Economics, 2019
- Superhuman OS, Integral Institute, 2018
- Deep Natural Language Processing, University of Oxford & Google DeepMind, 2017
- Knowledge-Based AI: Cognitive Systems, Udacity / Georgia Tech, 2016
- Probabilistic Graphical Models, Coursera / Stanford University, 2016
- Deep Learning (TensorFlow), Udacity / Google, 2016
- Approximation Algorithms. Parts 1 & 2, Coursera / École Normale Supérieure, 2016
- Functional Programming Principles in Scala, Coursera / École Polytechnique Fédérale de Lausanne, 2015
- Deep Learning for Natural Language Processing, Stanford University, 2015
- Neural Networks for Machine Learning, Coursera / University of Toronto, 2015
- Scalable Machine Learning (Spark / PySpark), edX / UC - Berkeley, 2015
- Artificial Intelligence. Part 1, edX / UC - Berkeley, 2014
- Machine Learning: Reinforcement Learning, Udacity / Georgia Tech, 2014
- Web Intelligence and Big Data, Coursera / Indian Institute of Technology - Delhi, 2012
CONFERENCES
- The Conference on Neural Information Processing Systems, 2020
- The International Conference on Probabilistic Programming, 2018
- O'Reilly Artificial Intelligence Conference, 2016-2018
- IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO), 2007