Dr. Aman Sharma Assistant Professor (SG) (91) 01792-239348 aman.sharma@juit.ac.in, amans.3008@gmail.com For More Information Click here
Dr. Aman Sharma is a distinguished academic, researcher, and innovator in the field of Computer Science and Engineering. Currently serving as an Assistant Professor (Senior Grade) at Jaypee University of Information and Technology, Solan, Dr. Sharma has over a decade of experience in academia, research, and innovation. His areas of expertise include data science, machine learning, bioinformatics, and modeling and simulation. Known for his interdisciplinary approach, Dr. Sharma has made substantial contributions to advancing technology and solving real-world problems through research and innovation.
Born on August 30, 1991, in Mohali, India, Dr. Sharma's early academic excellence was evident during his schooling at Gian Jyoti Public School, where he achieved stellar results in both matriculation and intermediate examinations. He pursued his Bachelor of Technology in Computer Science and Engineering from Rayat and Bahra Institute of Engineering and Biotechnology, graduating with an impressive 85%. His thirst for knowledge led him to Thapar Institute of Engineering and Technology, Patiala, where he earned a Master of Engineering with a 9 CGPA and later a Ph.D. in Computer Science and Engineering.
Dr. Sharma began his teaching career at Thapar Institute as a Teaching Assistant, subsequently taking on roles as a Research Teaching Associate and Non-Tenure Lecturer. In 2019, he joined Jaypee University, where he has been instrumental in developing and teaching courses in Python, Artificial Intelligence, and Advanced Algorithms. Alongside his teaching, he has been deeply involved in groundbreaking research. His projects include developing machine learning frameworks like KSRMF for predicting anti-cancer drug responses, BE-DTI for drug-target interaction prediction, and C-HMOSHSSA for cancer classification using multi-objective metaheuristics. These contributions have been widely recognized and published in prestigious journals and conferences.
Innovation is at the core of Dr. Sharma's work. He holds numerous patents, including an AI-based medical diagnosis system and IoT-enabled health monitoring systems. His creative solutions extend to fields such as agriculture and road safety, showcasing his commitment to leveraging technology for societal benefit. Additionally, he has mentored student-led startups, such as "JOIE" and "POCKETRAVEL," which address challenges in education and tourism through AI-driven applications.
Dr. Sharma is a dynamic leader and community advocate, actively organizing workshops, faculty development programs, and international conferences. He has been a reviewer for leading journals and a guest editor for special issues on cutting-edge topics like sentiment analysis in multimedia data. His leadership extends to professional organizations such as IEEE, where he has served in various capacities.
Outside his professional pursuits, Dr. Sharma enjoys reading, cooking, and engaging in sports like volleyball and badminton. He is a lifelong learner and an active member of several professional and academic organizations. His unwavering dedication to research, education, and innovation continues to inspire his students, colleagues, and the broader academic community, making him a trailblazer in his field.
Research Interests:
Machine Learning
Bioinformatics
Artificial Intelligence
Deep Learning
Data Analytics
STARTUPS:
S. No. |
Startups |
1 |
Title - JOIE A friend you wish you had Team Members - Archit Kaushal and Prakhar Jain Mentor - Dr. Aman Sharma Brief about the project: The AI-based chatbot project designed to provide answers to any DSA (Data Structures and Algorithms) question is an innovative solution to help students and developers in their learning and problem-solving journey.
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2. |
Title: POCKETRAVEL Team members: Agam Raj and Ishan Sharma Mentor: Dr. Aman Sharma Brief about the project: * Creating a solution for the tourists who travel around. Showing them a designed path to travel on with a specific amount of time. * Creating a domain of new unexplored places with a specific designed path on which they can travel on. * A digital guide or a chatbot we call, that helps people find specific locations and find routes to reach their locations on. * Showing a visual glimpse of the places (explored and unexplored) in terms of video and photos and giving a brief of the place to travel. POCKETRAVEL will increase the average spent time of tourists.
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Major Project Open Titles:
AI for Heart Disease Prediction
Machine Learning can play an essential role in predicting presence/absence of Locomotor disorders, Heart diseases and more. Such information, if predicted well in advance, can provide important insights to doctors who can then adapt their diagnosis and treatment per patient basis.
AI for Plant Disease Prediction
Crop diseases are a major threat to food security, but their rapid identification remains difficult in many parts of the world due to the lack of the necessary infrastructure. The combination of increasing global smartphone penetration and recent advances in computer vision made possible by deep learning has paved the way for smartphone-assisted disease diagnosis.
Phycological Chatbot
Mental health has become one of the most overlooked, yet crucial, aspects of our entire well-being in today's environment. In this work, we propose a system for a virtual mental health assistant due to cost, time, and space constraints, as well as a lack of resources associated with inperson counselling. Disrupted mental health is typically the consequence of a snowball effect that necessitates continual attention and deliberate efforts to remediate. This is made possible with the help of a virtual mental health chatbot. The recommended chatbot will have a chat feature, many language voice input options, and a recommendation tool to improve the user's mood.
AI for Social communication: Speech and Language Deficits in Neurological Disorders
Certainly! Speech and language deficits in neurological disorders encompass a range of challenges, affecting communication abilities due to conditions like aphasia, dysarthria, and apraxia. These disorders can arise from strokes, traumatic brain injuries, or neurodegenerative diseases, impacting speech production, comprehension, and overall communication skills. AI interventions aim to assist in therapy, offering innovative tools for rehabilitation and communication support.
AI for Social Good: Social Media Analytics for Mental Health
AI-driven social media analytics for mental health involve using algorithms to analyze online behavior, language patterns, and sentiment to detect potential mental health concerns. By monitoring social media posts, AI can identify signs of depression, anxiety, or other issues, providing early intervention opportunities and support for individuals in need, ultimately contributing to mental health awareness and care.
Federated Learning for Natural Language Processing (NLP)
Explore federated learning applications in NLP tasks like sentiment analysis or language translation. Develop a system that learns from decentralized text data sources while preserving linguistic nuances and privacy.
Personalized Federated Recommender System
Create a personalized recommendation system using federated learning techniques. Tailor recommendations to individual preferences while ensuring user privacy across multiple data sources.
AI for Diabetic Prediction
Diabetes Mellitus is among critical diseases and lots of people are suffering from this disease. Age, obesity, lack of exercise, hereditary diabetes, living style, bad diet, high blood pressure, etc. can cause Diabetes Mellitus. People having diabetes have high risk of diseases like heart disease, kidney disease, stroke, eye problem, nerve damage, etc. Current practice in hospital is to collect required information for diabetes diagnosis through various tests and appropriate treatment is provided based on diagnosis. Big Data Analytics plays an significant role in healthcare industries. Healthcare industries have large volume databases. Using big data analytics one can study huge datasets and find hidden information, hidden patterns to discover knowledge from the data and predict outcomes accordingly.
Minor Project Open Titles:
AI for Social communication: Speech and Language Deficits in Neurological Disorders
Certainly! Speech and language deficits in neurological disorders encompass a range of challenges, affecting communication abilities due to conditions like aphasia, dysarthria, and apraxia. These disorders can arise from strokes, traumatic brain injuries, or neurodegenerative diseases, impacting speech production, comprehension, and overall communication skills. AI interventions aim to assist in therapy, offering innovative tools for rehabilitation and communication support.
AI for Social Good: Social Media Analytics for Mental Health
AI-driven social media analytics for mental health involve using algorithms to analyze online behavior, language patterns, and sentiment to detect potential mental health concerns. By monitoring social media posts, AI can identify signs of depression, anxiety, or other issues, providing early intervention opportunities and support for individuals in need, ultimately contributing to mental health awareness and care.
Federated Learning for Natural Language Processing (NLP)
Explore federated learning applications in NLP tasks like sentiment analysis or language translation. Develop a system that learns from decentralized text data sources while preserving linguistic nuances and privacy.
Personalized Federated Recommender System
Create a personalized recommendation system using federated learning techniques. Tailor recommendations to individual preferences while ensuring user privacy across multiple data sources.
AI for Kidney Stone Prediction
Using AI for kidney stone prediction involves leveraging machine learning algorithms to analyze various patient parameters like medical history, dietary habits, and urine composition to forecast the likelihood of kidney stone formation. By integrating these factors, AI models can assist in early detection, allowing for proactive measures to prevent kidney stone development and provide personalized medical guidance for at-risk individuals.
AI for Diabetic Prediction
AI in diabetic prediction utilizes machine learning models to analyze patient data including blood sugar levels, lifestyle factors, family history, and other health indicators to forecast the risk of developing diabetes. These AI algorithms aid in early identification of at-risk individuals, enabling proactive interventions, personalized care, and lifestyle modifications to prevent or manage diabetes effectively.
AI for Cancer Prediction
AI in cancer prediction involves leveraging machine learning algorithms to analyze medical imaging, genetic data, patient records, and biomarkers to identify patterns indicative of cancer risk or early-stage tumors. These models assist in early detection, improving prognosis, treatment planning, and potentially saving lives through timely intervention and targeted therapies.
Minor Project Groups guided (2023):
Project Group No. |
Minor Project Title |
Project Members' Roll No. and Name |
Project Members' Roll No. (Contact No.) |
Email address |
GP-01 |
Brain Tumor Classification |
191218 Ananya Joshi, 191226 Vipasha Rana |
191218 (7088344929), 191226 (7876175747) |
191218@juitsolan.in |
GP-02 |
Breast Cancer classification using deep learning model on image dataset |
191417 Abhimanyu Singh Anand |
7754075207 |
191417@juitsolan.in |
GP-03 |
Music Genre Classification using Audio Data |
1. 191220- Saksham Chaturvedi |
191220 - 9582064701 |
191220@juitsolan.in |
GP-04 |
Diabetes Prediction using Machine Learning |
191405- Shaswat Sahu & 191410- Akshat Gopal |
191405(9918779997) & 191410(9717350293) |
191405@juitsolan.in |
GP-05 |
Detection of brain tumor in humans using Machine Learning |
191225 Abhiti Labroo and 191228 Aman Gupta |
191225 - (9625085332) and 191228 - (8527528050) |
191225@juitsolan.in |
GP-06 |
Healthcare Systems |
191524 Dron Mehta; 191525 Ajay Tyagi; 191540 Devbrat Srivastava |
191524- 9111904188; 191525- 9368928743; 191540- 8127823251 |
191524@juitsolan.in |
Minor Project Groups guided (2022):
Project Group No. |
Minor Project Title |
Project Members' Roll No. and Name |
Project Members' Roll No. (Contact No.) |
GP-01 |
SLA (Smart lens audio) |
181348-Shreyansh Rawat,181325-Aditya narayan singh,181347-Mridul Pratap Singh |
181348-8527300370,181325-8544765605,181347-9027055414 |
GP-02 |
Cancer Detection of Lymph Node Metastases |
Astitva Shrestha-181404 & Navdeep Singh Hada-181405 |
181404 - 7619958609 & 181405 - 7374805281 |
GP-03 |
Emotion Detection Model using AI |
Ananya Srivastav-181417, Parth Sharma - 181439 |
9582102706, 8130306740 |
GP-04 |
Assistive Ball |
Mohammad Kounen Khan (181277), Sparsh Mittal(181272) |
181277(8871181950), 181272(9773760787) |
GP-05 |
Smart Monitoring and Controlling of Government Policies using social media and Cloud computing. |
Aditya Sharma(181395) , Abhay Suri(181389) |
Aditya -7018305219 Abhay-8091773310 |
GP-06 |
Braille Keyboard With Voice Output |
181488 - GOPESH CHAWLA 181375 - SHREYA DWIVEDI |
181488 - 7889005081 181375 - 9305323295 |
Major Project Groups guided (2023):
Project Group No. |
Major Project Title |
Project Members' Roll No. and Name |
Project Members' Roll No. (Contact No.) |
Email address |
GP-01 |
Predicting Breast Cancer by Applying Deep Learning to Linked Health Records |
181266 Divyanshu Tewari |
7983944297 |
181266@juitsolan.in |
GP-02 |
Brain Tumor Segmentation |
181335 PRADYUMAN SHARMA, 181344 CHANDAN DHIMAN |
9418781565, 8091723212 |
181335@juitsolan.in, 181344@juitsolan.in |
GP-03 |
Customer Marketing segmentation with Machine Learning |
181439 Parth Sharma, 34 181417 Ananya Srivastav |
8130306740 |
181439@juitsolan.in |
GP-04 |
Stroke Prediction |
181277 Mohd. Kounen Khan, 181272 Sparsh Mittal |
8871181950, 9773760787 |
181277@juitsolan.in, 181272@juitsolan.in |
Major Project Groups guided (2022):
Project Group No. |
Major Project Title |
Project Members' Roll No. and Name |
Project Members' Roll No. (Contact No.) |
Email address |
GP-01 |
Generate Cartoon Characters |
Aarushi Bharadwaj (171260), Adhishree Bansal (171233), |
9805582706, 8219870133 |
171233@juitsolan.in, 171260@juitsolan.in |
GP-02 |
An interactive web application using Angular and Google Firebase to review movies |
Abhishk Agarwal(171212) |
7007653256 |
171212@juitsolan.in |
GP-03 |
Streaming application with recommendation engine |
Shashank Shukla (171296), Shubham Singh (171305) |
9877339581, 9871358837 |
171296@juitsolan.in |
GP-04 |
Face Mask Detector with OpenCV, TensorFlow and Deep Learning |
Dawa Tenzin (171388) |
8629858962 |
171388@juitsolan.in |
Output of Projects Guided:
1. A. Sharma and S. Chaturvedi, "Mouse-Less Cursor Control for Quadriplegic and Autistic Patients Using Artificial Intelligence" In Artificial Intelligence for Accurate Analysis and Detection of Autism Spectrum Disorder, IGI Global. [DOI: 10.4018/978-1-7998-7460-7.ch008]
2. A. Sharma, A. Bansal and A. Bhardwaj, "Forecasting the Trend of Covid-19 Epidemic", In Proceedings of 6th International Conference on Parallel and Distributed Computing. (PDGC-2020) [DOI: 10.1109/PDGC50313.2020.9315795]
3. A. Sharma, K. Shah, S. Verma, "Face Recognition using Haar Cascade and Local Binary Pattern Histogram in OpenCV", In Proceedings of 2021 Sixth International Conference on Image Information Processing (ICIIP-2021) [DOI: 10.1109/ICIIP53038.2021.9702579]
4. Mohana R, Sharma P, Sharma A. Ensemble Framework for Red Wine Quality Prediction. Food Analytical Methods. 2022 Aug 19:1-5.
5. Joshi A, Rana V, Sharma A. Brain Tumor Classification using Machine Learning and Deep Learning Algorithms: A Comparison. In Proceedings of the 2022 Fourteenth International Conference on Contemporary Computing 2022 Aug 4 (pp. 15-21).
6. Tiwari A, Chugh A, Sharma A. Ensemble framework for cardiovascular disease prediction. Computers in Biology and Medicine. 2022 May 17:105624.
7. Agarwal P, Rastogi D, Sharma A. Face Mask Detection Alert System for COVID Prevention Using Deep Learning. InApplications of Machine Learning and Deep Learning on Biological Data 2023 Mar 13 (pp. 57-74). Auerbach Publications.
Patents/Copyright:
Australian Patent Application Number- 2020103509
Invention Title- An Artificial Intelligence Based System to Identity The Medical Condition Prior To Doctor Consultation |
German Patent Application Number- 202022102926.1
Invention Title: Internet of Things (IOT) Based Infrared Health Monitoring System For Newborn Babies
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Indian Patent Application Number- 202311029769
Invention Title: Method of Fabrication and Arrangement of Anti-Glare Glass for Avoiding Accidents on Road |
Indian Patent Application Number- 202311038968
Invention Title: Psychological Chatbot and Voice Bot System for the Treatment of Mental Illnesses |
Indian Patent Application Number- 202411040937 Invention Title: Agriculture System for Enhanced Soil Management and Crop Optimization Using IoT and Drone Technology
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Indian Patent Application Number- 202411050793 Invention Title: IoT and AI-Powered Robotic Arm System for Automated Plant Sowing and Weed Removal
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Indian Design Patent Application Number: 416819-001, Cbr no : 208187 Invention Title: Portable Barcode Scanner |
Diary number: 30957/2024-CO/L Date of filing: October 04, 2024 Copyright Title: AI-Powered Spiritual Intelligence App for Ethical Decision-Making and Employee Well-Being.
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Managed a Special Issue for a Scientific Journal:
Rajni Mohana, Anand Nayyar, Pradeep Kumar, Aman Sharma, "Introduction to the Special Issue on Sentiment Analysis and Affective computing in Multimedia Data on Social Network" Scalable Computing: Practice and Experience, 2023
Conferences Organized:
Conference Co-Chair , ICIIP-2021
https://www.juit.ac.in/ICIIP_2021/advisory_committee.php
Conference Co-Chair , PDGC-2024
https://www.juit.ac.in/pdgc-2024/index1.php