Hi, I am Ahmed 👋

AI Research Engineer

Muhammad Ahmed is a highly skilled Data Scientist and AI Engineer specializing in computer vision, machine learning, and natural language processing. With a proven track record of success in both research projects and Kaggle competitions, he brings extensive expertise to the table. Ahmed's portfolio highlights his remarkable achievements, demonstrating his proficiency in solving complex data challenges. Armed with a Bachelor's degree in Computer Science and strong research and engineering skills, he is well-prepared to take on innovative data science and AI projects. Connect with Muhammad today to explore exciting collaboration opportunities in these cutting-edge fields.

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About Me

Introduction
Kaggle Competitions Master

Muhammad Ahmed, an accomplished Data Scientist, AI Engineer and Kaggle Competitions Master with a passion for unlocking the power of data. With a strong focus on computer vision, machine learning, and natural language processing, Muhammad has consistently delivered exceptional results in research projects and Kaggle competitions. His impressive portfolio showcases a diverse range of accomplishments, demonstrating his ability to tackle complex data challenges with creativity and precision. Equipped with a Bachelor's degree in Computer Science and a keen eye for research and engineering, Muhammad is eager to embark on new collaborations in the dynamic fields of data science and AI. Connect with him today to explore groundbreaking opportunities that leverage the full potential of data-driven insights.

02+ Years'
Experience
30 Top Ranks
in Competitions
03 Papers
Published
Download CV

Skills

Technical Competence

Data Science & AI

Machine Learning

Deep Learning

Computer Vision

Natural Language Processing

Data Analysis

Frameworks

PyTorch

TensorFlow

Scikit-learn

Keras

OpenCV

Pandas

NumPy

Soft Skills

English Communication

Problem-solving

Teamwork

Critical Thinking

Adaptability

Business Acumen

Programming & Fundamentals

Python

C++

SQL

Data Structures and Algorithms

Containerization & Cloud

Docker

Amazon Web Services

On-click services

Qualifications

Academic and Professional Career
Work
Education
Bachelor of Science

Computer Science

FAST National University of Computer and Emerging Sciences
Karachi, Pakistan
2018 - 2022

AI Engineer

Pioneer Corporation
Tokyo, Japan (Remote)
OCT 2023 - PRESENT

Research Engineer - Computer Vision and Machine Learning

Retrocausal
Redmond, WA, USA (Remote)
JUL 2022 - OCT 2023

Data Scientist

Pikky
India (Remote)
DEC 2021 - JUN 2022

Software Engineer (Intern), Machine Learning Infrastructure

Retrocausal
Redmond, WA, USA (Remote)
NOV 2020 - DEC 2021

Achievements

Accomplishments in various competitions

Kaggle

Gold Medals

3
  1. [Solo Win] Enzyme Stability Prediction (Protein Engineering)

    Rank 2 out of 2482 teams
  2. LLM - Detect AI Generated Text (Large Language Models)

    Rank 3 out of 4358 teams
  3. U.S. Patent Phrase to Phrase Matching (Phrases Similarity Prediction using NLP Transformers)

    Rank 10 out of 1889 teams

Silver Medals

6
  1. Hungry Geese (Game bot using Reinforcement Learning)

    Rank 19 out of 875 teams
  2. CommonLit - Evaluate Student Summaries (Text score prediction using LLM)

    Rank 27 out of 2064 teams
  3. G2Net Gravitational Wave Detection (Signals prediction from blackhole collision using signal processing)

    Rank 41 out of 1219 teams
  4. Feedback Prize - Evaluating Student Writing (Predicted argumentative writing using NLP transformers)

    Rank 52 out of 2058 teams
  5. CommonLit Readability Prize (Passage complexity prediction using NLP Transformers)

    Rank 60 out of 3633 teams
  6. Cassava Leaf Disease Classification (Image Classification using Computer Vision algorithms)

    Rank 94 out of 3900 teams

Bronze Medals

8
  1. Google Landmark Recognition 2020 (Recognize landmarks in images using Computer Vision algorithms)

    Rank 62 out of 736 teams
  2. Jigsaw Multi-languages Toxic Comment Classification Contest (Used bilingual NLP transformers)

    Rank 86 out of 1621 teams
  3. SIIM-FISABIO-RSNA COVID-19 Detection (Detected COVID-19 cases from chest X-ray and CT images using Computer Vision algorithms)

    Rank 127 out of 1305 teams
  4. Shopee - Price Match Guarantee (Matched products based on product descriptions, images, and other metadata with the help of unsupervised approach of making a model with different modalities)

    Rank 128 out of 2426 teams
  5. OpenVaccine: COVID-19 mRNA Vaccine Degradation (Predicted the degradation in RNA using NLP)

    Rank 141 out of 1636 teams
  6. PetFinder.my - Pawpularity Contest (Predicted number of "likes" that a photo would receive based on various features like metadata, image properties, and pet breed information using CV and NLP algorithms)

    Rank 186 out of 3537 teams
  7. Riiid! Answer Correctness Prediction (Tracked knowledge state of students using time series algorithms)

    Rank 288 out of 3395 teams
  8. Mechanisms of Action (MoA) Prediction (Data Science & ML, Improved existing algorithm’s accuracy)

    Rank 316 out of 4373 teams

Publications

  1. Learning by Aligning 2D Skeletons in Time

    Submitted at WACV 2024

    [Demo Video]

  2. Unsupervised Frame-to-Segment Alignment for Temporal Activity Segmentation

    Submitted at WACV 2024

    [Demo Video]

  3. Sequential Embedding-based Attentive (SEA) classifier for malware classification
    Published at IEEE ICCWS 2022

Other Competitions

  1. Qualifiers of International Data Analytics Olympiad (IDAO) 2022

    Secured 2nd rank among teams from institutes like Stanford, IIT, HSE University, University of Tokyo etc and qualified for World Finals to represent my country and university at Moscow, Russia
  2. Geoffrey Hinton Hackathon (Data Science & ML)

    Secured 2nd Rank after competing with professionals and students from top Indian universities like IIT and NIT.
  3. Machine Learning Competition by HackerEarth

    Ranked 1 out of 5164 participants
  4. Data Science Competition by Dphi.tech

    1st position
  5. Data Science Competition by Dphi.tech

    2nd Rank
  6. HackerEarth Deep Learning Competition

    Rank 6 out of 5494 Participants
  7. Melanoma Tumor Size Prediction by MachineHack - Analytics India

    Rank 5 out of 300 participants
  8. JanataHack: Demand Forecasting by Analytics Vidhya

    5th Position out of 300+ Participants
  9. Janatahack: Customer Segmentation by Analytics Vidhya

    9th position out of 500+ participants
  10. Janatahack: Machine Learning in Agriculture by Analytics Vidhya

    Rank 6 out of 600+ teams
  11. ACM League (Competitive Programming) by ACM Maju

    1st Runnersup
  12. ICPC Topi Regional

    Ranked 8th
  13. Procom'19 & DevDay'19. (Speed Programming) by FAST NUCES Karachi

    2nd Runners up
  14. CodeWars 2018 (Competitive Programming) by ACM - FAST NUCES

    Winners

Records

  1. Won a Kaggle Competition solo - 2023

  2. Became Pakistan's first and only Kaggle Competitions Master - 2022

  3. Became Kaggle Competitions Expert - 3rd and youngest in Pakistan to achieve this rank - 2020

Projects

Few important projects

Learning by Aligning 2D Skeleton Sequences in Time

We propose a novel self-supervised temporal video alignment framework for fine-grained human activity understanding. By using 2D skeleton heatmaps instead of 3D coordinates, our approach leverages spatial and temporal self-attention in a video transformer, achieving higher accuracy and robustness.

PDF Video

Permutation-Aware Action Segmentation via Unsupervised Frame-to-Segment Alignment

Our paper presents a novel transformer-based framework for unsupervised activity segmentation, incorporating both frame-level and segment-level cues. By leveraging a frame-level prediction module and unsupervised training via temporal optimal transport, along with a segment-level prediction module and frame-to-segment alignment module, our approach achieves permutation-aware segmentation results.

PDF Video

GML - Auto Data Science

Tired of doing Data Science manually? GML is here for you! GML is an automatic data science library in python built on top of multiple Python packages.

Code

Sequential Embedding-based Attentive (SEA) classifier for malware classification

The rise in smart devices has brought about increased security risks, including the threat of malware. Detecting and combating malware early on is crucial to prevent widespread device corruption and network failure. Our research introduces a lightweight, efficient malware detection model utilizing state-of-the-art NLP techniques.

PDF Code

Do you have any questions?

Schedule a meeting and lets discuss!

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Erol Bicer

References

Testimonials

Andrey Konin

Chief Architect at Retrocausal

I had a pleasure of working with Muhammad at the Retrocausal, collaborating on couple of projects. I was impressed Muhammad's execution ability under tight timeline, he is very good at delivery results with the minimum resources. He would be a great asset to any team!

Alaknanda Agarwal

Senior Product Manager, ICICI Lombard

Ahmed is extremely good with modelling irrespective of size of dataset. It was a pleasure to work with him at Pikky and follow the thought process he used to come up with the recommendation model, among other things.

Contact Me

Get in Touch

Call Me

+923163801959

Location

Karachi, Pakistan
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