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Tashin Ahmed AI Researcher and Engineer profile

Tashin Ahmed / アハメド・タシン

তাশীন আহমেদ। ˈtæʃɪn; Name of origin: Tashin (Hausa) - Rising & Ahmed (Arabic) - Highly praised/Magnificent

🧠 On the trail of Hive Mind 🔰 AI Researcher & Engineer 〄

[tashinahmed] under domain [aol.com]

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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.


last updated: October 2024 (partial)


Experiences


Professional Experiences

For details visit here.

Cross Compass, Tashin Ahmed AI Engineer.
Research Engineer (AI R&D) at Cross Compass
October 2024 - Present (Permanent)

Joined as a Research Engineer in Advanced AI Technology Development Group under Digital Industry Business Unit at Cross Compass (XC) from Oct 2024.


Smart Studios employee, Tashin Ahmed AI Research Engineer.
AI Research Engineer at Smart Studios Malta
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.


Amar iSchool course instructor, Tashin Ahmed Course Instructor.
Course Instructor at Amar iSchool
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.


AriSaf Tech employee, Tashin Ahmed Data Scientist and AI Researcher.
Data Scientist at AriSaf Tech Japan K.K.
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.


Research Assistant Tashin Ahmed from United International University UIU, Dhaka, Bangladesh
Research Assistant at Dept. of Computer Science & Engineering, United International University
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.


Tashin Ahmed research intern from CSIR-CDRI, Uttar Pradesh, India
Remote ML Research Intern at CSIR-Central Drug Research Institute, UP, India
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


Tashin Ahmed as a Technical Program Committee Member at International Joint Conference on Neural Networks (IJCNN)
Member of The Program Committee (Reviewer) at The Thirteenth International Conference on Learning Representations (ICLR 2025)
Till October 2024


Tashin Ahmed as a Technical Program Committee Member at International Joint Conference on Neural Networks (IJCNN)
Technical Program Committee Reviewer at The International Joint Conference on Neural Networks (IJCNN 2024)
Till July 2024


Student Volunteer Tashin Ahmed NeurIPS
Student Volunteer at Conference on Neural Information Processing Systems (NeurIPS)
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.


Collaorative Robotics Lab researcher Tashin Ahmed
Research Volunteer at Collaborative Robotics Lab (CRL) - University of Virginia
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.


deeplearning.ai content tester, leader, volunteer Tashin Ahmed Content Tester & Community Leader at DeepLearning.AI
March 2022 - November 2022
Tested resources (video lectures, codes, manuals) for unreleased courses.


deeplearning.ai content tester, leader, volunteer Tashin Ahmed KaggleX BIPOC Mentor (Cohort 3) Kaggle
August 2023 - November 2023




Peer Reviews

Peer reviewer Tashin Ahmed for Image and Vision Computing, Elsevier Peer reviewer Tashin Ahmed for Journal of Plant Diseases and Protection, Springer Peer reviewer Tashin Ahmed for International Journal of Electrical and Computer Engineering Systems Peer reviewer Tashin Ahmed for Artificial Intelligence Reviewer, Springer Peer reviewer Tashin Ahmed for IET Image Processing Peer reviewer Tashin Ahmed for Signal Processing: Image Communication Peer reviewer Tashin Ahmed for Applid Intelligence Peer reviewer Tashin Ahmed for Springer Nature Computer Science Peer reviewer Tashin Ahmed for First Workshop on Bangla Language Processing @ EMNLP 2023 Peer reviewer Tashin Ahmed for International Joint Conference on Neural Networks, IEEE Peer reviewer Tashin Ahmed for International Joint Conference on Neural Networks, IEEE 2024 Peer reviewer Tashin Ahmed for Machine Learning for Life and Material Science: From Theory to Industry applications, ICML 2024 Peer reviewer Tashin Ahmed for ICLR 2025


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


Google Research Football with Manchester City F.C. Top 6%. Solo participation. 🥉 Tier.
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.


Halite by Two Sigma Top 8%. Solo participation. 🥉 Tier.
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.


Multi Agent Behaviour Challenge - (CVPR 2022) (Ant & Beetle Groups Video Data) 2nd position.
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.


CGIAR Crop Damage Classification Challenge 🥉 Bronze Medalist.
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...



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