الٓمٓ
Tashin Ahmed / アハメド・タシン
তাশীন আহমেদ। ˈtæʃɪn; Name of origin: Tashin (Hausa) - Rising & Ahmed (Arabic) - Highly praised/Magnificent
🔰 AI Researcher & Engineer 〄 with a performance history in AI competitions.
[tashinahmed] under domain [aol.com]
I like to work simultaneously on fundamental R&D in terms of systems (along with data crunching to terminal solution) including Neural Network Architectures (on every domain, i.e. Computer Vision, Natural Language Understanding, Sequential Learning in AI and so on). Furthermore, I want to actively participate in the True and Safe AGI revolution since I believe my areas of long-term research interests will play a crucial role in this revolution.
Previously, I worked as an AI Research Engineer at Smart Studios Malta and a Data Scientist at AriSaf Tech Japan K.K. I was a Research Assistant at Dept. of CSE, United International University, funded by ICT Ministry of Bangladesh & part of ICT Innovation Fund. I also served as a Research Volunteer at Collaborative Robotics Lab - University of Virginia. Before that, I have completed my internship at CSIR - Central Drug Research Institute, Uttar Pradesh, India.
Industrial Experiences: Classical Computer Vision, Orthophoto Analysis and Segmentation, Quantitative Analysis, Algorithmic Trading, High Frequency Trading, Optical Character Recognition (English, Bengali, Japanese), Medical Image Analysis, Board Game AI.
Long-term Research Interests: Neuro-Dynamic Programming, Cellular Automaton, Swarm (AI) Intelligence, Multimodal & Reincarnating RL, Meta Learning, Core Neural Network Architectures.
I have relocated to 🇯🇵 Japan 🗾 🍙 🍱 recently.
New accepted workshop paper @ NeurIPS 2024:
Collective Wisdom in Language Models: Harnessing LLM-Swarm for Agile Project Management
in NeurIPS 2024 -
Workshop on Open-World Agents (OWA-2024)
Experiences
Professional Experiences
For details visit here.
January 2023 - July 2024
AutoScan: Damage detection system that detects dents from different parts of a car in a controlled environment.
- Developed a custom data labeling tool to streamline annotation workflows.
- Translated an existing C++ program into a Python DL-based solution for enhanced car part detection.
- Integrated IR sensor data with video frames, creating a rule-based system for precise panel detection.
- Built a program compatible with Nomnio’s software and scanner, utilizing five camera angles and IR sensors.
- Enhanced the system's performance by upgrading the core architecture with SOTA AI.
Agriculture & Rural Payments Agency: Orthophoto analysis for agro based landcover detection on whole Malta map.
- Processed large GeoTIFF files (40GB each) for training SOTA AI models for landcover segmentation.
- Focused on identifying cultivable land, water bodies, and agricultural features.
- Utilized MS Azure AI platform to address challenges in multi-band dataset processing.
AirImpact: Above ground Biomass detection with AI.
- Above ground Biomass detection with AI.
- Conducted tree counting with DL from orthophotos (planetscope data).
- Prepared a PoC (AI end to end model architecture) for above-ground biomass (AGBM) detection.
hubble_s: Behavioral analysis with AI technology.
- Provided theoretical solution on AI architecture & support on building Behavioral OS.
Colleagues and advisors: Dr Leander Grech, Dr Mark Borg and Dr Jean Paul Ebejer.
July 2022 - November 2022 (Seasonal)
Kaggle 101 in Bangla: Prepared a MOOC for Kaggle enthausiasts of Bangladesh in Bangla/Bengali language.
- Focuses on practical Kaggle competitions, teaching data analysis and modeling.
- Aims to make technical education accessible to Bengali speakers.
- The specialization course remains incomplete, and the relevance of Kaggle 101 is gradually diminishing.
- Currently, the course content is approximately 20% outdated.
May 2021 - December 2022 (Full-Time)
TradeX: Automated trader for stock, ForEx and Crypto (Internal Project).
- Participated in a FinTech moonshot project, utilizing the in-house AI solution, Core Engine.
- Designed a rule-based system that proved more profitable than the existing AI system.
- The rule-based system contributed to significant cost savings for the company.
- Collaborated with senior management in brainstorming sessions for product innovation.
- Provided strategic input for enhancing the Core Engine's AI-driven performance.
- Assisted in shaping future in-house product development initiatives based on project insights.
Junior Software Engineer at AriSaf Tech Japan K.K.
November 2020 - April 2021 (Full-Time)
Say Halal: Halal Packaged item detection and a super app for Muslims in Japan (Internal Project).
- Contributed to AI-based in-house product development.
- Performed data analysis and preparation for machine learning models, specifically for Japanese OCR.
- Developed a rule-based string processing model for multi-class classification of natural language datasets.
- The rule-based model achieved significant improvements compared to traditional machine learning models.
- Focused on enhancing classification efficiency and accuracy through rule-based approaches.
Colleagues and advisors: Toru Yoshihara and Jahidur Rahman.
February 2020 - June 2020 (Contractual)
- Contributed to the govt. funded project - BWriterGuide, focusing on the advancement of the Bengali OCR system.
- Tasked with enhancing the system's accuracy & performance to serve users & improve text recognition in Bangla.
- Managed the deployment of essential modules, utilizing Heroku for seamless integration & scalability.
- A segment of this project was published with necessary adjustments to ensure clarity & impact in its presentation.
Supervisor - Dr Chowdhury Mofizur Rahman. Co-Supervisor Chowdhury Rafeed Rahman.
December 2019 - February 2020 (Internship)
- Collaborated with Dr Sukant Khurana & his analytics team on Multiple Sclerosis under medical image analysis.
- Hypothesis investigation related to various lesion features, maximum length of coordinates, area, and perimeter.
- Analyzed the effects of major and minor axis lengths, eccentricity, convex area, and volume on EDSS scores.
- Focused how changes in lesion characteristics influence clinical outcomes in Multiple Sclerosis patients.
Supervisor - Dr Sukant Khurana.
Volunteer Experiences
Till October 2024
Till July 2024
November 2020 - 2022
Mostly I lent my hands on bug hunting for neurips.cc website till now. Tested environments like gather town for virtual conferences.
June 2020 - October 2020 (Apprenticeship)
Worked with Md Mofijul Islam on a multimodal based action recognition learning model. Competed in Hateful Memes competition hosted by FB & DrivenData.
Content Tester & Community Leader at DeepLearning.AI
March 2022 - November 2022
Tested resources (video lectures, codes, manuals) for unreleased courses.
KaggleX BIPOC Mentor (Cohort 3) Peer Reviews
Publications
Published
Collective Wisdom in Language Models: Harnessing LLM-Swarm for Agile Project Management
Tahmid Hussain, Tashin Ahmed, MD SHAHEDUL HAQUE, Mohammad Rifat Ahmmad Rashid
Accepted for - NeurIPS 2024 -
Workshop on Open-World Agents (OWA-2024)
(Poster Presentation, Track: Workshop)
GraphKAN: Graph Kolmogorov Arnold Network for Small Molecule-Protein Interaction
Predictions
Tashin Ahmed, Md Habibur Rahman Sifat
Accepted for - ICML 2024 - Machine Learning for
Life and Material Science: From Theory to Industry applications (Poster Presentation,
Track: Workshop)
Pipeline Enabling Zero-shot Classification for Bangla Handwritten Grapheme
Linsheng Guo, Md Habibur Rahman Sifat, Tashin Ahmed (Initiator)
Accepted for - EMNLP 2023 - Workshop
on Bangla
Language Processing (BLP) (Oral Presentataion, Track: Main - Long)
Evaluating The Effectiveness of Capsule Neural Network in Toxic Comment Classification using
Pre-trained BERT Embeddings
Md Habibur Rahman Sifat, Noor Hossain Nuri Sabab, Tashin Ahmed (Initiator and
directional lead)
Accepted for - TENCON 2023 - IEEE Region
10 Technical
Conference (Main Conference : Oral Presentation)
Dual phase convolutional neural network based system aimed at small rice grain dataset for disease
identification
Tashin Ahmed (bachelor’s thesis, lead), Chowdhury Rafeed Rahman, Md. Faysal Mahmud Abid
Accepted for - AAAI 2023 - AI for
Agriculture and Food Systems (Workshop : Lightning Talk + Poster)
Referred at -
Geographical Research Bulletin
Automatic Signboard Detection and Localization in Densely Populated Developing Cities
Md Sadrul Islam Toaha, Sakib Bin Asad, Chowdhury Rafeed Rahman, SM Haque, Mahfuz Ara Proma, Md Shuvo, Ahsan
Habib, Tashin Ahmed (co-supervisor), Md Basher
Published in - Signal Processing: Image Communication
Classification and understanding of cloud structures via satellite images with
EfficientUNet
Tashin Ahmed, Noor Hossain Nuri Sabab
Published in - Springer
Nature Computer Science (SNCS)
Preprints + Ongoing Works + On Hold
- Teaching Convolutional Neural Networks to Solve Conway’s Reverse Game of Life
- Bengali Lip Reading from Video Dataset with 3D Convolutional Neural Network
- Automated Market Trend Forecasting and Order Placement: A Hybrid Approach integrating Multiple AI Systems
- Exploring Adaptive Memory Patterns in Reinforcement Learning Agents
Competitions
Best Performances
Basically, I tried to create memory patterns for different role set i.e. defence, offence, and attack. Different RL methods have been tested for different roles. Highest skill point gained in leaderboard μ=1169.9.
Tried to put different categories of bots that are correlated to Swarm Intelligence by utilizing different NN techniques. Highest gain on the LB was μ=1085.5.
Competition was about beaviorial representation learning from ants and beetles using video dataset. We have worked with PyTorch SimCLR a Simple framework for Contrastive Learning of visual Representations for our model.
The "Eyes on the Ground" project is a collaboration between ACRE Africa, the KALRO, IFPRI, and the Lacuna Fund, to create a large ML dataset that provides a close-up view of smallholder farmer's fields, with the aim of developing a Picture Based Insurance framework.
Projects
Research Projects
AutoScan AI Scanner
SOTA Object Detection and Tracking system to detect multiclass objects in controlled environment. Classical Computer Vision approach taken in terms of AI failure that saves cost both in terms of money and time.
ARPA-Orthoseg
Othophoto Analysis on bigdata for multiclass classification and segmentation for agro based project.
Project for Agriculutre and Rural Payment Agency of Malta.
Dhan
Oushodhi
An AI-based mobile phone application (Android) for detecting different Rice Grain diseases in context of Bangladesh.
Undergraduate Capstone Project.
BWriter Guide
A user-friendly Bangla writer web application which will have many options for the user to choose from.
This project is funded by ICT Ministry, Bangladesh & part of ICT Innovation Fund.
Say Halal
AST's internal research and development project for a mobile phone app that uses Japanese OCR and a natural language-based classification system.
Games & Simulations (Academic Projects)
TETRIS
Single player Tetris game created in C++ & Java both. Graphics added for both version.
10
different
levels
are created depending on play time with addictive scoring system.
LIFE
Zero-player
game
for
observing cellular
automaton & evaluation of their
growth. Recreation of Conway's game of
Life using C language & OpenGL.
MAZE
A maze creator algorithm which creates random mazes using OLC Engine & have GUI
written in C++ comes with automated maze solver plus a game to solve maze puzzle. Both
program
tested on
TURBO C++.
Certifications
MOOCs
DeepLearning.AI Tensorflow Developer: Professional Certificate
deeplearning.ai
Grade: 93.785%
Data-driven Astronomy
University of Sydney
Grade: 89%
Social Psychology (with Honors)
Wesleyan University
Grade: 92%
Others
Outstanding Reviewer
First Workshop on Bangla
Language Processing (BLP) - EMNLP 2023
Certification
(Private)
Duolingo English Test (w/o preparation scored 140/160, IELTS comparative score -
7.5/9)
Duolingo English Test
Certification
(Private)
Triplebyte Certified
Triplebyte
Certification
Eterna (Solve Puzzles, Invent Medicines)
Achievements
Certification
Others
Write Ups
Time Series
Analysis
(TSA) for beginners
You have access to 10 notebooks (created using Kaggle Notebook) to get you started with
Time
Series
Analysis (TSA). Continue reading
to find out more.
TL;DR
All ten of the notebooks are briefly described in this discussion, along with links to
each
notebook.
A variety of arbitrary pattern generation strategies, validations, label construction,
and
diverse
ML and DL techniques, including manually
constructed CNN, DNN, LSTM, and RNN using TensorFlow Sequential layers—all of which are
ideal
for
beginners—were tried to be provided.
The last two notebooks demonstrate basic EDA and the application of DNN and CNN to the
Sunspots
dataset.
Sunspots
Dataset: Sunspots are transient occurrences on the photosphere of the
Sun that
appear as spots that are darker than their surroundings. These are areas of lower
surface
temperature brought on by magnetic flux concentrations that prevent convection. Sunspots
typically
come in pairs with completely different magnetic polarity. (incomplete)
Introduction to Genetic Algorithms (GA)
This blog post is an assembly of GA from the perspective of biological anecdote to a
deep dive
on it's history, simple architecture and use cases.
Capsule Neural Network (CapsNet): A Forgotten ANN
Architecture
CapsNets are artificial neural networks (ANN) that better capture
hierarchical relationships. They’re inspired by biological neural arrangements. CapsNet
use “capsules”, which reuse outputs
from multiple capsules to stabilize representations for...
