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Dr. Rohitesh Kumar
Assistant Professor
Profile Summary
Dr. Rohitesh Kumar is an Assistant Professor at the School of Computer Science, UPES, Dehradun. He earned his Ph.D. in Computer Science and Engineering from National Institute of Technology Patna in 2025 and completed his M.Tech in Information Technology from Tezpur University.
His research focuses on signal processing and machine learning–based approaches for biometric verification, with particular emphasis on detecting and mitigating spoofing attacks in voice-based biometric systems. His scholarly interests also include accent translation, language conversion, and deep learning applications in intelligent systems.
He is committed to combining research excellence with effective teaching and mentoring.
Work Experience
Dr. Rohitesh Kumar is currently serving as an Assistant Professor at UPES, where he contributes to teaching, research, and student mentoring in core computer science disciplines. His academic journey includes advanced doctoral research in pattern recognition, speech processing, and AI-driven security systems.
Research Interests
Pattern Recognition | Signal Processing | Deep Learning | Machine Translation | Speech Biometrics | Voice Anti-Spoofing | Artificial Intelligence
Teaching Philosophy
Dr. Kumar's teaching philosophy is grounded in the belief that strong conceptual understanding is the cornerstone of effective learning. He fosters an interactive classroom environment where students are encouraged to connect theoretical concepts with real-world applications and decision-making scenarios.
Through case-based discussions and analytical problem-solving, he promotes critical thinking, innovation, and curiosity. He strives to create a collaborative learning atmosphere that motivates students to engage deeply with the subject matter.
Courses Taught
Discrete Mathematics | Data Structures and Algorithms | Formal Languages and Automata Theory | Deep Learning
Scholarly Activities
Dr. Rohitesh Kumar is actively engaged in advancing research in pattern recognition, signal processing, machine learning, and deep learning. He has contributed multiple studies to reputable SCI, Scopus, and Web of Science indexed journals.
His research focuses on emerging technologies in biometric security, voice anti-spoofing systems, and intelligent speech applications. He continues to explore how modern AI techniques can strengthen authentication systems and language technologies.
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