I am co-coordinating the Samsung lab at DTU in the areas of digital Healthcare, mobile computing, Machine learning, smart agriculture, and Cryptography.
Actively looking for undergraduate/postgraduate and PhD students for research opportunities. check here for open areas
Further details for lab research projects: Samsung Lab, DTU
Benefits for participation:
- Work opportunity in the Samsung Lab for research students
- Close interaction with industry and hospitals
- Certificates on completion part of patent/publication
- Possible summer internship in lab
-Flexible work time in close coordination with team members
Project Openings for students:
- Cryptography (Identity-Based Cryptography for lightweight mutual authentication)
-Host Card Emulation with Near Field Communication
- Soil nutrient prediction using AI and spectral imaging
- Cognitive health with physiological signals and AI.
Ongoing Research Projects:
COGMAPS: Mobile-based Attention and Stress improvement with feedback from physiological sensors and EEG headsets
Abstract: Mental exercises such as puzzles, certain games, visual therapies, relaxation exercises and breathing exercise can help improve attention and stress in students. The study involves clinical questionnaires filled before and after an activity for stress and attention management. Sensors such as heart rate, galvanic sensor and EEG headsets to relay bio marker information to a mobile device. The device would apply mobile cloud computing-based machine learning/ deep learning algorithms to predict the mental status and measure the impact of the activity on the attention and stress level of participants. The experiment will be conducted on large number of students for data collection and subsequent deep-learning applications. Students will get an opportunity with real-time data collection using wearable health devices and use data sets for ML and Deep learning techniques.
Past Students: Debarshi Nath, Deeksha (MTech), Anubhav (BTech), Mrigank, Varun and Ankt (BTech), Shikha (PhD), Ayush, Neha, Rajat
2. Selective access for portable devices/IoT devices with efficient revocation (Attribute-based Encryption on mobile devices)
Abstract: Resource-constrained devices such as mobile and Abstract: IoT devices can provide access to shareable data with a group of users that must be accessed selectively, such as a portable healthcard or a family car. Ciphertext Attributed-based Encryption (CP-ABE) can provide Role-based access control. In this work, we look into the proposal of an optimized CP-ABE algorithm whose ciphertext remains constant with the increase in the number of attributes in the access control policy. It must also provide scalable revocation. The project will evaluate other constant-sized CP-ABE schemes for an efficient CP-ABE scheme with scalable revocation for mobile-based and IoT devices for selective access. The project looks into developing scalable revocation for a Lightweight ECC-based constant-sized CP-ABE scheme with scalable revocation on IoT and mobile devices.
Current Students: Raj, Lokesh, Ram Sandeep, Gaurav, Saksham and Sanchit
3. Mobile camera based attention feedback
Abstract: Tratak candle flame Meditation on improves Concentration and Memory level of all age groups. It all helps
decrease stress in the long term. The current digital apps only provide a candle flame for concentration. We
propose to develop a digital application that measures the gaze of a subject on the flame tip using the device
camera and provides a feedback to the subject on the level of gaze pf the subject in viewing the flame. The
feedback after such as session can help in further improving the cognitive functions of the subject.
Students: Aheli, Shivam, Deep, Rachit, Utkarsh and Tanish
4. Mobile-based Early detection of dementia using NLP
Abstract: Alzheimer’s Disease (AD) is an irreparable, progressive neurodegenerative disorder which deteriorates the cognitive and linguistic abilities of a person over time. Research has been going on for the early detection of this disease for quite some time. Currently, early detection of this disease is a challenging task. Doctors use the patient’s previous history, laboratory tests and change in behavioral patterns to diagnose the disease. In this project, we aim to use Natural Language Processing (NLP) techniques with the help of word embeddings, which in turn can interpret the relationships among words to detect AD.
Students: Rishabh and Vibhu, Arnav and Eshaan
5. EEG-based feedback with Treadmill for reducing stress and improving physical fitness
Abstract: The project will investigate EEG-based feedback for impact of treadmill training for long term stress reduction therapy and improvement for sports fitness. Students will get opportunity with real time data collection using wearable health devices and use data set for ML and Deep learning techniques.
Current Students: Mrigank, Harshit and Taksh
6. Traceability with Blockchains
Traceability is the ability to trace the history, application or location of an entity, by means of recorded identifications. Blockchain is a distributed, decentralized and immutable digital ledger which records transactions across a global network of computers where the information is highly secure. It can be used to secure Internet of Things. and retain a Digital Vault. In this project we look for solutions for traceability to secure a digital vault for healthcare and academic records.
Current Student: Perome (MTech), Ritick, Divit and Amar
7. Machine learning-based prediction to assess treatment outcome for Brain Stroke patients
Brain Stroke patients must seek timely medical treatment to prevent adverse effect of the stroke that causes paralysis. Many factors such as previous history of blood pressure and lifestyle may affect patients to be prone to such strokes. The project aims to develop a new smart prediction system to assist neurologist to develop intelligent models that can help indicate chances of improvement of a patient for the brain stroke treatment. The project will involve real time data of brain stroke patients under supervision of a neurologist.
Current Students: Achint (MTech), Hari, Hima Bindu and Varun (BTech)
8. EEG for sleep apnea and sleep disorders: This project aims to look into ML with EEG to predict sleep disorders such as sleep apnea.
Students: Hima and Diksha Chugh