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Ajay Kumar

I'm

About

Ajay Kumar is a passionate computer science lover. He is raised to play with computers whether they are video games or tons of coding. Academically, he is living his journey of being a novel computer scientist, currently a Ph.D. student (3rd year) in the Scalable Data Science (SDS) Lab at the University of Missouri, USA.

Ph.D. Computer Science ( on the way ✈️ )

"The only way to do great work is to love what you do. If you haven't found it yet, keep looking. Don't settle. As with all matters of the heart, you'll know when you find it."

  • Birthday: 22nd December 1997
  • Website: www.ajay-kumar.com
  • Phone: +1 573 801 5748
  • City: Missouri, USA
  • Age: 28
  • Degree: Doctorate
  • Email: ajay.kumar@missouri.edu
  • Freelance: Available

Training 10,000 hours to become a proficient coder with problem-solving skills in interdisciplinary areas. Trained 100+ scientists through conferences and workshops. Worked with 200+ researchers on diverse research problems at the Scalable Data Science (SDS) Lab under Dr. Praveen Rao.

Currently Working On
🔬 PhD Thesis — Target: Dec 2026 · Distributed computing on FABRIC testbed
📝 7+ papers published · ACM BCB, CIKM, Frontiers, Life Science Alliance
💼 Seeking ML / DS / SWE roles — Open to full-time industry positions
GitHub: checking...

Facts

Discover the facts that shape our world. From the fascinating to the mind-boggling, from the fun to the serious, we delve into the details that make our universe so rich and diverse. Join us on this journey of knowledge and exploration, and you might just see the world in a whole new light.

Lines of code

Projects

Lectures attended

People worked with

Programming Languages

Python 100%
R 90%
SQL 88%
Bash 90%

AI / ML & Generative AI

TensorFlow 95%
PyTorch 92%
Scikit-learn 90%
LLMs & Generative AI 92%
AI Agents & Multi-Agents 88%
Keras / HuggingFace 90%

Big Data, Cloud & Data Analysis

Apache Spark 90%
Apache Hadoop / Hive 88%
AWS SageMaker 85%
Data Analysis (Pandas / NumPy / SciPy) 92%
Data Visualization (Matplotlib / Seaborn) 90%
Web Development (Django / Flask / HTML / JS) 83%

Skill Overview

Research & Technical Expertise

From large-scale distributed computing and GPU-accelerated genomic pipelines to LLM-powered agents and deep learning models — Ajay's skill set spans the full data science stack. With a 4.0 GPA PhD and hands-on experience across academia and industry, he brings both depth and breadth to every problem.

  • Machine Learning & Deep Learning (TensorFlow, PyTorch)
  • Generative AI & LLMs (Agents, RAG, Fine-tuning)
  • Big Data & Cloud (Spark, Hadoop, AWS, FABRIC)
  • Bioinformatics & Genomics (GWAS, Variant Calling)
  • Research & Scientific Writing (7+ publications)

Curriculum Vitae

Latest resume available on request. ➡️

Summary

Ajay Kumar

Ph.D. Candidate in Computer Science (graduating Dec 2026) · Graduate Research Assistant at the Scalable Data Science (SDS) Lab · Vice President, ACM Upsilon Pi Epsilon (UPE) at Mizzou. Actively seeking Software Engineering, Data Scientist, and Machine Learning Engineer roles in industry.

  • Columbia, MO, USA
  • +1 573 801 5748
  • ajay.ducs@gmail.com

Education

Doctor of Philosophy (Ph.D.), Computer Science

Aug 2022 - Dec 2026

University of Missouri-Columbia, MO, USA

GPA: 4.0/4.0

Thesis: Optimized scientific workflows on the FABRIC national research testbed, advancing large-scale distributed computing capabilities.
Thesis Advisor: Dr. Praveen Rao

Master of Science, Computer Science

2018 - 2020

Banaras Hindu University (BHU), India

Grade: 8.23/10 · Research-oriented program covering AI, deep learning, data science, and computational theory. Thesis supervised by Dr. Manoj Kumar Singh (GIST, South Korea).

Bachelor of Science, Computer Science

2015 - 2018

University of Delhi, India

Professional Experience

Graduate Research Assistant (GRA) · SDS Lab, University of Missouri

Aug 2022 - Present

Columbia, MO, USA

  • First-author paper on GPU-enabled variant calling (2× speedup) — ACM BCB 2025.
  • First-author paper on BrainScale: FreeSurfer parallelism optimization on FABRIC — submitted to INDIS Workshop, Supercomputing 2025.
  • Scalable 650GB genomic variant analysis using Knowledge Graphs on NSF-funded FABRIC/CloudLab infrastructure.
  • Established AWS × IRRI partnership boosting genomic computational resources by 50%.

Graduate Teaching Assistant (GTA) · University of Missouri

Jan 2025 - May 2026

Columbia, MO, USA

  • CS 4080 — Parallel Programming for High Performance Computing (HPC)
  • CS 3910 — Advanced Cybersecurity
  • CMP_SC 1300 — Computing with Data in Python
  • CS/ECE 4001 — Integrated Cyberinfrastructure & Biomedical Engineering

Project Associate-I (Statistical Genomics) IRRI South Asia Hub

2020 - 2022

South Asia Hub, IN

  • Led in the establishment of a partnership of Amazon Web Services (AWS) and the International Rice Research Institute (IRRI) South Asia Hub (ISAH) and South Asia Regional Center (ISARC).
  • Trained 100+ Indian scientists/professors on "R programming, GWAS, QTLSeqR, GenomicSelection, and PythonAutomation".
  • Performed statistical, exploratory, and predictive analysis/modeling using machine/deep learning, four research papers are in the manuscript (also 150K+ views on Quora answers).
  • Conducted collaborated research with plant breeders, pathologists, molecular biologists, and bioinformaticians to solve domain-specific problems using machine/deep learning, performed data science analytics, and also, wet hands with computational biology skills.

Research Journey

Key milestones from my academic and professional career.

Jun 2019

Software Engineer Intern · SPA, New Delhi

Built govt urban planning site (15K visitors) & biodiversity Android app

Aug 2020

Research Scientist · IRRI South Asia Hub, India

Led AWS-IRRI partnership, trained 100+ scientists, 4 research papers, 200K+ Quora views

Aug 2022

PhD Student · University of Missouri, USA

Started at SDS Lab under Dr. Praveen Rao. FABRIC, GPU computing, Knowledge Graphs

2023

First Major Paper · VariantKG

Scalable genomic variant analysis on 650GB dataset using Knowledge Graphs & Graph ML

2024

Awards & Recognition

$2,500 ACM UPE Award · $5,500 FABRIC Fellowship · CIKM Demo presentation · Et-GWAS published (8 citations)

2025

Research & Recognition

ACM BCB paper (2× GPU speedup) · BrainScale submitted to SC'25 · 🏆 1st Place Claude Builder Club Hackathon · Outstanding TA Award · VP, UPE-Mizzou

Dec 2026

PhD Graduation (Expected)

Thesis: Optimized scientific workflows on FABRIC national research testbed

Key Achievements

$2,500 ACM UPE Executive Council Award

Honored for leading international chapter operations as Vice President, recognized by the ACM Upsilon Pi Epsilon honor society for outstanding contributions.

$5,500 FABRIC Competitive Travel Fellowship

Secured a competitive travel fellowship from FABRIC to present research findings and build global collaborations at prestigious international venues.

8,000+ Member Technical Community

Grew and actively manage a high-engagement technical community driving industry-relevant discussions and knowledge sharing through LinkedIn, GitHub, and YouTube.

7+ Published Research Papers

Published/co-published in prestigious international venues, contributing to advancements in computing, distributed cloud computing, and artificial intelligence. View on Google Scholar.

🏆 1st Place — Claude Builder Club Hackathon

Won first place at the Mizzou Claude Builder Club Hackathon with Equine Lameness Predictor — an AI-powered diagnostic tool for detecting horse lameness using Claude and computer vision.

Outstanding Teaching Assistant Award

Recognized with the Outstanding Teaching Assistant Award at University of Missouri-Columbia for excellence in teaching Parallel Programming (HPC), Cybersecurity, and Python courses.

Publications

Research contributions in distributed computing, genomics, machine learning, and AI. Full list on Google Scholar →

16 Citations Google Scholar
2 h-index Google Scholar
7+ Papers Int'l Venues
2 Conferences ACM BCB & CIKM
2025
S. Prasanna, A. Kumar, D. Rao, E.J. Simoes, P. Rao
Frontiers in Big Data, 2025
Journal 1 citation
A scalable tool for analyzing 650GB of human genomic variants using Knowledge Graphs and Graph Machine Learning on NSF-funded FABRIC and CloudLab distributed infrastructure.
2025
A. Kumar, P. Rao, P. Sanders
16th ACM Conference on Bioinformatics, Computational Biology and Health Informatics (ACM BCB), 2025
Conference
Optimizes a scalable distributed multi-GPU pipeline achieving 2× speedup for COVID-19 human genome variant calling on FABRIC/CloudLab using Google's JobShop Scheduling with NVIDIA Parabricks.
2025
BrainScale: Utilizing FABRIC for FreeSurfer Optimization and Choosing the Right Level of Parallelism
A. Kumar, P. Rao
INDIS Workshop, SC'25 (Supercomputing 2025) — Under Review
Workshop Under Review
BrainScale leverages the FABRIC national research testbed to optimize FreeSurfer neuroimaging workflows, systematically benchmarking parallelism strategies across distributed HPC resources to maximize throughput for large-scale brain imaging studies.
2024
N. Gnanapragasam, V.V. Prasanth, K.T. Sundaram, A. Kumar, B. Pahi, et al.
Life Science Alliance, 2024
Journal 8 citations
Novel extreme-trait GWAS methodology for uncovering rare variants across 3,000 rice genomes, enabling precision genomic selection for crop improvement.
2024
K. Shehzad, A. Kumar, M. Schutz, C. Webb, P. Nalela, M.J. Das, P. Rao
33rd ACM International Conference on Information and Knowledge Management (CIKM), Demo Track, 2024
Conference 1 citation
Democratizes human genome variant calling by enabling scalable analysis on commodity clusters using Apache Spark, Hadoop, and multi-cloud environments (FABRIC, CloudLab, AWS).
2024
S. Prasanna, A. Kumar, D. Rao, E. Simoes, P. Rao
arXiv preprint arXiv:2407.20879, 2024  •  Preprint of Frontiers in Big Data (2025)
Preprint 2 citations
Scalable analysis of 650GB of human genomic variants using Knowledge Graphs and Graph Machine Learning on NSF-funded FABRIC and CloudLab distributed infrastructure. Preprint of the published Frontiers in Big Data article.
2024
S. Zeng, T. Adusumilli, S.Z. Awan, M.S. Immadi, D. Xu, T. Joshi
bioRxiv, 2024  •  g2pdeep.org
Preprint 3 citations
Web-based deep learning framework for multi-omics phenotype prediction and biomarker discovery, supporting plant breeders with an accessible web interface at g2pdeep.org.
2023
A. Kumar, K.T. Sundaram, N. Gnanapragasam, U.M. Singh, K.J. Pranesh, et al.
bioRxiv, 2023  •  PyPI: DeepMap
Preprint 1 citation
Deep learning model for prediction-based crop breeding that outperforms traditional ML by 13–20%, deployable with a four-line Python interface via PyPI.

Research Knowledge Graph

Explore connections between papers, tools, topics and venues — click and drag nodes

Paper Topic Tool Venue

Talks & Conferences

Presentations and demos at international research venues.

2025
Talk
Optimizing the Variant Calling Pipeline Execution on Human Genomes Using GPU-Enabled Machines
16th ACM BCB — ACM Conference on Bioinformatics, Computational Biology and Health Informatics
USA, 2025
Conference Talk Paper →
2024
Demo
A Scalable Tool for Democratizing Variant Calling on Human Genomes Using Commodity Clusters
33rd ACM CIKM — International Conference on Information and Knowledge Management
Boise, ID, USA — October 2024
Demo Presentation Paper →
2021
Training
R Programming, GWAS, QTLSeqR, Genomic Selection & Python Automation for Researchers
International Training Workshop — IRRI South Asia Hub
India, 2021  •  100+ scientists trained
Invited Workshop

Portfolio

As a dedicated researcher in the fields of Artificial Intelligence, Machine Learning, and Computational Biology, I have consistently demonstrated my ability to drive innovation and contribute to cutting-edge projects.

  • All
  • Machine Learning Projects
  • Optimization Projects
  • Hackathon Projects

Services

Ajay Kumar offers a comprehensive suite of AI and data-driven services, leveraging his expertise in cutting-edge technologies. His services span generative AI, machine learning, optimization, research, development, and data analysis. Ajay specializes in developing innovative AI models, designing efficient algorithms, and implementing scalable solutions across various domains. His interdisciplinary approach combines AI with computational biology and other fields, driving innovation and scientific discovery. Clients benefit from his full-stack development skills, data science consulting, and ability to deliver actionable insights. Known for his collaborative spirit and commitment to excellence, Ajay not only provides technical solutions but also offers training and mentorship to enhance team capabilities. His rare combination of theoretical knowledge and practical skills makes him an invaluable asset for organizations seeking to leverage AI and data-driven technologies for competitive advantage.

Generative AI

I specialize in developing cutting-edge generative AI models, including text-to-image, language models, and creative AI applications. My services cover model design, training, fine-tuning, and deployment, ensuring innovative solutions that push the boundaries of AI-generated content across various domains.

Machine Learning

I offer machine learning services, including algorithm design, predictive modeling, and deep learning solutions tailored to specific business needs. My expertise includes data science consulting, model deployment, and custom software development. I also provide training and mentorship to enhance team skills in machine learning applications.

Optimization

I excel in optimization techniques for various domains, including algorithm efficiency, resource allocation, and process improvement. My services encompass mathematical modeling, heuristic methods, and machine learning-based optimization, delivering solutions that maximize performance and minimize costs across complex systems.

Research

I conduct cutting-edge research in AI, ML, and computational biology. My services include literature reviews, experimental design, data analysis, and publication support. I specialize in interdisciplinary projects, combining expertise in AI with domain-specific knowledge to drive innovation and scientific discovery.

Development

I offer full-stack development services with a focus on AI-driven applications. My expertise covers front-end and back-end development, database design, API integration, and cloud deployment. I specialize in creating scalable, efficient software solutions that leverage the latest technologies.

Data Analysis

I provide comprehensive data analysis services, including data cleaning, exploratory data analysis, statistical modeling, and data visualization. My expertise covers big data technologies, predictive analytics, and business intelligence, delivering actionable insights to drive informed decision-making.

Testimonials

Ajay Kumar is highly regarded for his exceptional skills and contributions in artificial intelligence, machine learning, and computational biology, as reflected in numerous testimonials from colleagues and peers. Trinath Adusumilli commended Ajay's practical expertise and innovative algorithm design that significantly enhanced project performance, while Aarthi Desai highlighted his conscientiousness and dedication to producing quality work. Bandana Pahi praised his willingness to help others and his proficiency in computational programming, emphasizing his problem-solving abilities and creative thinking. Vamshi Venkat noted Ajay's unique approach to exploring new methods in AI, making him a valuable asset in research and technology. His strong work ethic, collaborative spirit, and commitment to excellence were consistently acknowledged by others, including Deepti Sagare-Shetti and Atul Joshi, who recognized his adaptability and drive for success. Overall, Ajay is portrayed as a knowledgeable and dedicated professional whose presence positively impacts any team he joins, making him an invaluable asset in the tech industry.

Ajay Kumar excels in AI, ML, and DL, combining theoretical knowledge with practical skills. His innovative work on the G2PDeep application significantly improved AI system performance. Ajay's speed, accuracy, and clear communication make him invaluable. His collaborative spirit, mentoring commitment, and dedication position him as a rising force in AI. Any organization would be fortunate to have Ajay on their team.

Trinath Adusumilli

Full Stack Developer at Mastercard

Ajay Kumar is an exceptional computational biologist and programmer with expertise in AI, ML, DL, and software development. His proficiency in developing accurate packages and software for biological data analysis is impressive. Ajay's dedication, problem-solving skills, and creative thinking make him a valuable team member. His willingness to help others and listen attentively is commendable. With his skills and positive attributes, Ajay will undoubtedly be a great asset to any team he joins.

Bandana Pahi

Bioinformatician at IRRI, South Asia Hub

Ajay Kumar excels in Computational Biology and AI, demonstrating eminent expertise and a unique approach to exploring new methods. His proficiency in Machine Learning, Data Science, and Deep Learning is applied professionally in scientific contexts. Ajay's optimistic learning style and ability to apply his skills across various domains make him highly recommendable for positions in Research and Tech-Industry.

Vamshi Venkat

Research Associate/Data Scientist at Johns Hopskins University

Having known Ajay since college and worked with him on various projects, I can attest to his hard work and commitment to excellence in researching new domains and applying ML/DL concepts. His collaborative nature and eagerness to learn make him a valuable team member. I am confident he will be a great asset to any organization he joins.

Atul Joshi

Data Scientist at UHG

In my collaborations with Ajay, I have found him to be sincere, hard-working and dedicated. I wish him all the best for future endeavours. I'm sure he will continue to excel wherever he goes.

Varad Srivastava

Generative AI at Barclays

News & Updates

Recent highlights from research, awards, and community activities.

2025
Pub.

Paper published in Frontiers in Big Data — "A Scalable Tool for Analyzing Genomic Variants of Humans Using Knowledge Graphs and Graph Machine Learning"

2025
Talk

Presented at 16th ACM BCB Conference on GPU-optimized variant calling pipeline achieving 2× speedup.

Oct 2024
Demo

Demo paper presented at ACM CIKM 2024, Boise, ID — "Democratizing Variant Calling on Human Genomes Using Commodity Clusters"

2024
Award

Honored with $2,500 ACM UPE Executive Council Award for leading international chapter operations as Vice President.

2024
Grant

Secured $5,500 FABRIC competitive travel fellowship to present research and build global collaborations.

2024
Pub.

Paper published in Life Science Alliance — "Extreme Trait GWAS (Et-GWAS): Unraveling Rare Variants in the 3,000 Rice Genome" — 8 citations.

Contact

If you are looking to hire me as full-time, internship or freelance. Please don't hesitate to reach out. I am always ready to listen and help. Let's make something great together.

Location:

Columbia, MO, USA

Call:

+1 573 801 5748

Schedule a Meeting
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