Sakib Chowdhury

Sakib Chowdhury

PhD Student in Robotics, Stevens Institute of Technology

I am a PhD student at Stevens Institute of Technology, advised by Dr. Yi Guo. My research focuses on policy learning for robotic manipulation — force-conditioned imitation learning from human demonstrations using generative policy architectures like diffusion, ACT, and flow matching, alongside experience with world foundation models. I completed my M.Sc. at Stevens along the way, and before that my B.Sc. at Bangladesh University of Engineering and Technology (BUET). I've also worked as a Machine Learning Engineer at Celloscope, building Bengali speech and document-understanding systems deployed in production. My detailed resume is here.

News

Research

I work on robot learning for mobile manipulators in complex dynamic environments, advised by Dr. Yi Guo. Previously I worked with Dr. Shaikh Anowarul Fattah, with Dr. Apratim Roy on my undergraduate thesis, and with Dr. A. B. M. Alim Al Islam as an undergraduate research assistant at BUET.

Force-Conditioned Imitation Learning from Vision-Only Human Demonstrations via Robot Replay

Imitation Learning · Force/Contact Control · Submitted to ICRA 2027

A method for recovering a time-varying reference contact force from a single, uninstrumented human demonstration: a handheld tool is tracked visually, its trajectory is replayed on the robot under position control, and the external wrench is recovered from onboard joint-torque sensing via the robot's own dynamics model — no wrist force/torque sensor, no instrumentation on the demonstrator. A visuomotor diffusion policy jointly predicts reference pose and wrench, supplied at deployment as a time-varying setpoint to an admittance controller. On a pasta scooping-and-transfer task with a Kinova Jaco2 arm, this raises success from 82.5% (pose-only) to 97.5%, using just five minutes of human demonstration.

FlashPlan: A Fast Neural Motion Planner for Robotic Ball Catching

Motion Planning · Neural Networks · Submitted to ICRA 2027

A single-pass neural motion planner for time-critical interception: given the current and goal joint configurations plus an obstacle representation, FlashPlan directly predicts a compact, collision-free, time-normalized joint trajectory — no iterative search — with a median planning latency of ~6.5 ms versus 90–160 ms for classical sampling-based planners, and consistently low latency across the workspace rather than the wide, geometry-dependent variance those planners show. A torque-constrained time-scaling stage then computes the fastest dynamically feasible execution time via binary search. On a simulated robotic ball-catching task, this raises success from 87.4% (RRT-Connect) to 95.2% while more than doubling the available control window before ball arrival.

Learning to Strike for Robotic Table Tennis

Robotics · Residual Learning · Submitted, Under Review

A custom-built high-speed 6-DOF robotic arm that plays table tennis: a residual predictor estimates the ball's striking position from just two early position samples, correcting a physics-based trajectory estimate for real-world effects like restitution and friction rather than modeling them explicitly. Once positioned, a random forest regressor learns the striking velocity needed to return the ball to a target location. In simulation, this reaches a 98.5% interception success rate, with both learned components running in a few milliseconds.

Neural voice banking system overview

Neural Voice Banking System

Speech-to-Speech · ASR/TTS · Production Deployment

A speech-to-speech banking system in Bangla, built at Celloscope, that lets users perform routine banking tasks — balance transfers, balance inquiries — entirely by voice, with synthetic-voice responses for a full voice-to-voice experience. The system is integrated into Agrani Bank's voice banking app and combines several state-of-the-art speech models to keep the interaction fast and secure.

Synthetic NID generation pipeline overview

SynthNID: Synthetic Data to Improve End-to-end Bangla Document Key Information Extraction

Document Understanding · Synthetic Data · EMNLP 2023

A pipeline that generates realistic, fully-labeled synthetic Bangladeshi National ID cards — random names and identifiers composited onto random backgrounds with noise and blur — to train an OCR-free key-information extraction model where real labeled Bangla documents are scarce. Mixing synthetic with real data during fine-tuning consistently improves extraction accuracy on real NID cards, especially for Bangla-script fields.

Pixelated sEMG electrode array diagram

A Simulated Intelligent Pixelated Electrode Array for Surface Electromyography Sensors

Biomedical Sensors · Signal Processing · IEEE Sensors Journal 2024

A "pixelated" sEMG electrode array — a grid of micrometer-scale unit electrodes linked by electronic switches — that electronically grows or shrinks its effective size to exploit the natural low-pass filtering electrodes provide, maximizing signal-to-noise ratio for each subject's own skin and tissue composition. A statistical SNR estimator finds the optimal setting in a short calibration phase, improving real EMG SNR by 20–71% over a fixed electrode.

SpectroCardioNet architecture overview

SpectroCardioNet: An Attention-Based Deep Learning Network Using Triple-Spectrograms of PCG Signal for Heart Valve Disease Detection

Biomedical Signal Processing · Attention Networks · IEEE Sensors Journal 2022

A compact dual-path network for detecting heart valve disease from phonocardiogram (heart sound) spectrograms: a spectral attention path emphasizes diagnostically relevant time-frequency regions, while a parallel sequential path tracks how frequency content evolves over time. Trained from scratch with only 2.4M parameters — far smaller than transfer-learning baselines — it beats prior published methods on two PCG benchmarks.

SHONGLAP corpus preparation workflow

SHONGLAP: A Large Bengali Open-Domain Dialogue Corpus

NLP · Weak Supervision · LREC 2022

A framework that turns public Bengali political talk-show and debate audio into a fully annotated open-domain dialogue corpus — denoising, diarization, speech-to-text, and weak-supervision-based speaker-role labeling in place of manual annotation. The resulting 7,700+ dialogue corpus, the first of its kind for Bengali, measurably improves BanglaBERT's performance when fine-tuned on a downstream classification task.

CovTANet architecture overview

CovTANet: A Hybrid Tri-Level Attention-Based Network for Lesion Segmentation, Diagnosis, and Severity Prediction of COVID-19 Chest CT Scans

Medical Imaging · Attention Networks · IEEE Trans. Industrial Informatics 2021

An end-to-end network that segments COVID-19 lesions in chest CT scans, then explicitly routes those lesion-focused features into joint diagnosis and severity classifiers — rather than classifying raw CT volumes directly. A tri-level (channel, spatial, pixel) attention mechanism, used throughout, helps the segmentation network handle diffuse, irregularly shaped lesions, and the full pipeline substantially outperforms baseline networks, especially at early, mild-symptom diagnosis.

Projects

A selection of engineering and applied-ML projects, spanning embedded systems, computer vision, speech, and reinforcement learning. More on my GitHub.

Bengali license plate recognition pipeline

Bengali License Plate Recognition with Document Understanding Transformers

YOLOv8 · Document Transformers · Deployed System

A production license-plate detection and recognition system deployed at Kalna Bridge Toll Plaza. YOLOv8 localizes plates, and a document-understanding transformer — trained on 2M synthetic plates and then fine-tuned on real data — reads the Bengali text, outperforming traditional OCR. Three cameras at different angles feed a majority-voting scheme to reduce misprediction.

BOLUS cattle health monitoring device

BOLUS — Cattle Health Monitoring

IoT · Embedded Systems · Remote Sensing

A small hardware bolus placed inside a cow's stomach for up to five years, sending movement, temperature, and other health data to a remote server, where an AI system estimates the current health condition of the herd for dairy farms.

Track Me vehicle tracking hardware
GPS/GSM tracking module and companion app

Track Me — Vehicle Tracking System

Embedded Hardware · GSM/MQTT · Firebase

A vehicle-tracking device combining voltage, current, accelerometer, and GPS sensing, connected over GSM and pushing data to Firebase via MQTT. Users track and monitor their vehicle's movement and power state through a companion app.

Brushless DC motor speed controller

Electronic Speed Controller for BLDC Motors

Power Electronics · MOSFET Drivers · Arduino

A three-phase electronic speed controller for brushless DC motors, built from three MOSFET half-bridges gated through TLP250 optocouplers, with bootstrapped high-side drive and Arduino-synchronized commutation.

Bangla ESPnet TTS/ASR inference overview

Bangla ESPnet — TTS & ASR

Speech Synthesis · Speech Recognition · ESPnet

Trained ESPnet's LJSpeech TTS recipe on 360 hours of Google SLR Bangla audio for an end-to-end Bangla TTS system, and its ASR recipe on a combined 760 hours of Google SLR and Mozilla Common Voice Bangla data — both built as part of the conversational-AI banking platform at Celloscope.

Whisper model architecture

Fine-tuning Whisper on Bengali

ASR · Low-resource Languages

Whisper's Bengali performance lags its high-resource languages; this project fine-tunes Whisper on large-scale Bengali speech data to close that gap, with a notebook reusable for fine-tuning on any target dataset.

Robotic arm sorting objects by shape

Robotic Arm with Computer Vision for Shape Sorting

Computer Vision · Robotic Arm · Champion, BUET Industrial Automation Challenge 2017

A vision-guided robotic arm that identifies the shape of objects on a running conveyor belt and sorts them accordingly. Built for a BUET Robotics Society competition — our team won outright — and later showcased at Digital Bangladesh 2017.

Lunar Lander reinforcement learning agent

Reinforcement Learning Playground — Lunar Lander & Half Cheetah

Deep Q-Learning · PPO · PyTorch / MuJoCo

Deep Q-learning agent for Lunar Lander (3 fully-connected layers, average score of 106 over 100 episodes), and a Proximal Policy Optimization agent for the MuJoCo Half Cheetah environment.

Smaller experiments — a GAN trained on my own face, a Flappy Bird RL agent, Diffie–Hellman end-to-end encryption, MSP430 drivers, a 4-bit SAP computer in Verilog, and more — live on GitHub.

Publications

Force-Conditioned Imitation Learning from Vision-Only Human Demonstrations via Robot Replay

Sakib Chowdhury, Raymond Huang, Vanessa Chen, Yi Guo
Submitted to ICRA 2027 (under review)

Recovers a time-varying reference contact force from a single, uninstrumented human demonstration via robot replay and onboard joint-torque sensing, and trains a visuomotor policy that jointly predicts pose and wrench for admittance-controlled deployment.

FlashPlan: A Fast Neural Motion Planner for Robotic Ball Catching

Sakib Chowdhury, Yi Guo
Submitted to ICRA 2027 (under review)

A single-pass neural motion planner with a torque-constrained time-scaling stage, achieving low and spatially consistent planning latency and improved simulated ball-catching success over classical sampling-based planners.

Learning to Strike for Robotic Table Tennis

Sakib Chowdhury, Yi Guo
Submitted (under review)

Residual-learning approach to predicting striking position and velocity for a high-speed table-tennis-playing robotic arm from sparse ball trajectory observations.

SynthNID: Synthetic Data to Improve End-to-end Bangla Document Key Information Extraction

Syed Monsur, Shariar Kabir, Sakib Chowdhury
EMNLP Bangla Language Processing Workshop, 2023

Uses large-scale synthetic document generation to improve key-information extraction from Bangla documents in low-data settings.

A Simulated Intelligent Pixelated Electrode Array for Surface Electromyography Sensors

Sakib Chowdhury, Dipayon Kumar Sikder, Apratim Roy
IEEE Sensors Journal, Vol. 24, No. 4, 2024 (Undergraduate Thesis)

A pixelated sEMG electrode array that modulates electrode size to maximize signal-to-noise ratio across body locations and skin types, reducing sample duration without added computational overhead — suitable for low-power wearables.

Joint Optimization of Energy Efficiency and Data Fidelity for Real-Time Air Condition Monitoring

Shamir Ahmed, Sakib Chowdhury, A. B. M. Alim Al Islam
Submitted at Heliyon Journal (under review), 2023

A joint optimization scheme balancing sensor energy consumption against data fidelity for continuous, real-time air-condition monitoring.

SpectroCardioNet: An Attention Based Deep Learning Network Using Triple-Spectrograms of PCG Signal for Heart Valve Disease Detection

Sakib Chowdhury, Monjur Morshed, Shaikh Anowarul Fattah
IEEE Sensors Journal, 2022

A spectral-attention network over triple-spectrogram (spectrogram, delta, double-delta) representations of phonocardiogram signals for automatic cardiac disease detection.

SHONGLAP: A Large Bengali Open-Domain Dialogue Corpus

Syed Mostofa Monsur, Sakib Chowdhury, Md Shahrar Fatemi, Shafayat Ahmed
LREC, 2022

The first large open-domain Bengali dialogue corpus, built from public multi-party podcasts and talk-shows via weak supervision, improving downstream fine-tuning of Bengali language models.

CovTANet: A Hybrid Tri-Level Attention-Based Network for Lesion Segmentation, Diagnosis, and Severity Prediction of COVID-19 Chest CT Scans

Tanvir Mahmud, Md Jahin Alam, Sakib Chowdhury, Shams Nafisa Ali, Md Maisoon Rahman, Shaikh Anowarul Fattah, Mohammad Saquib
IEEE Transactions on Industrial Informatics, 2021

An end-to-end clinical pipeline for COVID-19 chest CT scans combining a tri-level (channel, spatial, pixel) attention segmentation network with joint diagnosis and severity prediction.

A RNN based parallel deep learning framework for detecting sentiment polarity from Twitter derived textual data

Sakib Chowdhury, Md Latifur Rahman, Shams Nafisa Ali, Md Jahin Alam
ICECE, 2020

A parallel RNN architecture that fuses Word2Vec, GloVe, and sentiment-specific word embeddings for Twitter sentiment polarity detection.

Experience

2023 – Present

Stevens Institute of Technology

Graduate Researcher

Developed and trained convolutional motion planners in PyTorch for ultra-high-speed motion planning in mobile manipulators, with a PyBullet simulation environment for a Franka Emika Panda arm mounted on a Husky base. Transferred trained planners from simulation to the real robot, and applied ONNX quantization for faster inference on NVIDIA A6000 GPUs — a 10x speedup over classical planners (RRT, PRM) in the ROS MoveIt framework. This work was partially supported by the US National Science Foundation.

2021 – 2023

Celloscope

Machine Learning Engineer (AI)

Built Bangladesh's first voice banking system — a speech-to-speech interface for balance transfers and inquiries, integrated into Agrani Bank's app — and a production license-plate detection and recognition system deployed at a toll plaza, using document-understanding transformers in place of traditional OCR.

2021 – 2022

Department of CSE, BUET

Research Assistant (Part-Time)

Developed a system that detects train derailment from up to 1200 meters away by sensing track vibrations, under Dr. A. B. M. Alim Al Islam.

2020 – 2021

Adorsho Pranisheba

Intern Engineer (IoT)

Worked on BOLUS, a cattle health monitoring device implanted in dairy cows for up to five years, streaming movement, temperature, and health data to a remote AI system.

Education

2025 – Present

Stevens Institute of Technology

Ph.D., Robotics
2023 – 2026

Stevens Institute of Technology

M.Sc., Electrical and Computer Engineering (Robotics and Automation Systems)
2017 – 2022

Bangladesh University of Engineering and Technology (BUET)

B.Sc., Electrical and Electronic Engineering

Honors & Affiliations