Specialization

Digital Techniques and Instrumentation, Embedded and Real-time artificial intelligence-based systems

Email

dharmendra.kumar@thapar.edu

Biography

Mr. Dharmendra Kumar received a B. Tech degree in Electronics and Communication Engineering in 2013 from Himachal Pradesh University (Shimla), and an M.Tech. degree in Digital Techniques and Instrumentation from the Department of Electronics Engineering, Indian Institute of Technology, Banaras Hindu University, Varanasi, India, in 2018, where he is currently working toward a Ph.D. degree in the same department of IIT (BHU), Varanasi. Also, he is working as an Assistant Professor at Thapar Institute of Engineering & Technology, Patiala. His current research interest includes the development of an AI-based Intelligent Embedded system for gas-sensing applications. His research broad areas of interest include intelligent gas sensors and systems, sensor array-based systems (E-Nose), Embedded and Real-time artificial intelligence-based systems, Cyber-Physical systems, Pattern Recognition, Machine Learning, Internet of Things (IoT), Cloud Computing, and Deep Learning.

Education

1. Ph.D. pursuing in Digital Techniques & Instrumentation from /IIT (BHU), Varanasi / 2019 ----.
2. M. Tech in Digital Techniques & Instrumentation from / IIT (BHU), Varanasi / in 2018
3. B.Tech. in Electronics and Communication Engineering from / H.P.U, Shimla / in 2013

Experience: Total Teaching / Industrial / Research Experience (1.7 years)

1. Assistant professor, Thapar Institute of Engineering and Technology, Patiala, India, Sept. 2023 – Till Date
2. From 20^th December 2018 – 24^th July 2019: PAL-III, MMATD, CSIR-CIMFR, Barwa Road, Dhanbad-826015, Jharkhand, India.
3. From June 2015 - May 2016: System Administrator (Networking), Affimintus Technologies, Indore, India.

Teaching Interests:

1. Data Science/ Data Evaluation/ Machine Learning/ Data Wrangling/ Internet of Things (IoT).
2. Microprocessor/ Microcontroller/ Architecture Design/ Embedded System.
3. Basic Electronics/ Digital Electronics/ Logic Gates / Digital System Design.

Research Interest:

1. Embedded Systems, Real-time artificial intelligence-based systems, Cyber-Physical Systems.
2. Pattern Recognition, Machine Learning, Internet of Things (IoT), and Deep Learning.
3. Electronic Devices, Gas Sensor Array, E-Nose, and Gas Sensor Fabrication based on Thin film Technologies.

Publications:

Journals

1. N. K. Chauhan, A. Kumar, A. Jain, K. Singh, D. Kumar, S. S. Singh, and H. K. Shakya, "Optimizing cervical cancer diagnosis with a hybrid deep neural network and progressive resizing on pap smear WSIs," Scientific Reports, 2026.
2. D. Kumar, V. Jain, A. Mishra, R. Shrestha, M. Sahlabadi, and N. S. Rajput, "An intelligent cloud-integrated electronic nose system for non-destructive fruit ripeness monitoring in precision agriculture," Electronics, vol. 15, no. 12, p. 2502, 2026.
3. D. Kumar, A. K. Rabha, A. Mishra, R. Shrestha, and N. S. Rajput, “A novel E-Nose architecture based on virtual sensor-augmented embedded intelligence for a real-time in-vehicle carbon monoxide concentration estimation system,” Electronics, vol. 15, no. 8, Art. no. 1671, 2026.
4. D. Kumar, V. Jain, A. Mishra, R. Shrestha, and N. S. Rajput, “Smart exhaust analytics: A sensor-based way to identify the types of engines based on the composition of exhaust gas,” Sensors, vol. 26, no. 9, Art. no. 2863, 2026, doi: 10.3390/s26092863.
5. S. Singh, S. K. Meena, K. Singh, S. Kumar, D. Kumar, and R. K. Dewangan, "Quantum-inspired genetic algorithm for influence maximization on social networks," Concurrency and Computation: Practice and Experience, vol. 37, no. 25–26, p. e70332, 2025.
6. M. Kumar, D. Das, N. Singh, S. Mishra, D. Kumar, and N. Panda, "Ensemble-based disease prediction in medical image data," Procedia Computer Science, vol. 258, pp. 622–632, 2025.
7. M. Kumar, D. Kumar, D. Dash, R. B. Ray, N. K. Ray, and S. K. Mohapatra, “An ensemble based predictive analysis for chronic kidney disease with quantum neural networks,” in Proc. 2025 OITS Int. Conf. Information Technology (OCIT), Bhubaneswar, India, 2025, pp. 1–6.
8. M. Kumar, M. Azlan, Kanishk, K. Chatterjee, G. Satapathy, and D. Kumar, “FinReport: Explainable stock earnings forecasting via news factor analyzing model,” Procedia Computer Science, vol. 283, pp. 3570–3580
9. M. S. Mehrolia, D. Kumar, A. Verma, and A. K. Singh, "Fabrication and characterization of self-assembled low voltage operated OTFT for H2S gas sensor for oil and gas industry," IEEE Transactions on Electron Devices, vol. 71, no. 1, pp. 769–776, Jan. 2024.
10. M. S. Mehrolia, D. Kumar, A. K. Singh and J. S. Rana, "Simulation of CMOS Inverter Circuit and 1-Bit   Magnitude Comparator Circuit Utilizing Low-Voltage Flexible TFTs," 2024 IEEE 21st India Council International Conference (INDICON), Kharagpur, India, 2024.
11. Kumar, D., Kumar, M., Chaudhri, S. N., Kumar, P., & Dash, D. (2024, February). Enhancing security with microwave and lidar sensor integration. In 2024 International Conference on Emerging Systems and Intelligent Computing (ESIC) (pp. 130-135). IEEE.
12. A. Verma, D. Kumar, V. N. Mishra, and R. Prakash, "A self-assembled polymer nanocomposite-based low-voltage white light phototransistor with UV-cured synthesized LaZrOx dielectric," IEEE Transactions on Electron Devices, vol. 70, no. 7, pp. 3575–3581, Jul. 2023.
13. D. Kumar, A. Verma, M. Kumar, V. Maurya, and A. Mishra, "Utilizing machine learning for the assessment of mosquito repellent effectiveness and decision support in product selection," Journal of Sustainable Building Technology and Urban Development, vol. 14, no. 4, pp. 519–533, 2023.

International Conferences:

1. D.Kumar. S.N. Chaudhari and N.S. Rajput. " Air Quality Prediction and Monitoring Using Machine Learning-Based Forecasting Approach." Submitted & Presented in (ICICAT-2023), (BIT), Gorakhpur, India, 23-24^th June 2023.

2. D.Kumar, S.N. Chaudhari, and N.S. Rajput, "A Machine Learning-Based Disinfectant Type, Concentration, and Usage Monitoring System for Real-World Scenarios Submitted & Presented in (ICICAT-2023), (BIT), Gorakhpur, India, 23-24^th June 2023.

3. D.Kumar, S.N. Chaudhari, S. Gautam, and M. Kumar, "Intelligent Mosquito Repellent System: A Machine Learning Approach for Enhanced Effectiveness and Classification”, Submitted in (ICISE-2023), SVU, Kalyani (Kolkata), India, 09^th September 2023 accepted.

Achievements, Awards, FDP, Workshops and Recognitions

1. Smart electronics for Connected communities (SECC-2019), IIT (BHU), Varanasi
2. Machine Learning Concepts Application & Challenges from IIT (BHU), Varanasi
3. Machine Learning Trends, Perspective & Prospects from IIT (BHU), Varanasi.
4. Machine Learning Concept Application and Challenges, IIT (BHU), Varanasi.
5. International Symposium on Quantum Computing and Innovations (ISQCI-2023).
6. FDP on Artificial Intelligence and Machine Learning at IM-BHU, Varanasi.
7. Emerging trends in data science and IoT.
8. Attended several more FDP and Workshops at IIT (BHU), Varanasi, and also from other Premier institutions.

Message to Students & Community

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