Assistant Professor, Department of Computer Science and Engineering
Delhi Technological University (DTU)

Phone: +91-8700721038
Email: anukritikaushal@dtu.ac.in
Verified Email: anukritikaushal@dtu.ac.in

Profile Summary

I am a highly motivated academic and researcher with over four years of experience in deep learning, machine learning, and image forensics. My work focuses on detecting manipulated images, uncovering GAN-generated content, and ensuring digital image integrity in a rapidly evolving technological landscape. Currently, as an Assistant Professor at Delhi Technological University (DTU), I am dedicated to contributing to academia through teaching, research, and supervision of graduate students. Alongside teaching, I am pursuing a Ph.D. with research centered on manipulated image detection using deep learning. I have actively participated in various faculty development programs and workshops, enriching the learning environment and contributing to the academic community.

Academic Qualifications

• Ph.D. (Pursuing) – Delhi Technological University (DTU)
  Research Focus: Manipulated Image Detection using Deep Learning
  Key Areas: Image Forensics, GAN-based Deepfakes, High Compression Detection
• M.Tech in Computer Science and Engineering – Delhi Technological University
  Thesis: A Comparative Study of Deep Learning Models for Image Manipulation Detection
• B.Tech in Computer Science and Engineering – Delhi Technological University

Professional Experience

Assistant Professor
Department of Computer Science and Engineering, Delhi Technological University
2020 - Present

• Teach and design course content for undergraduate and postgraduate students in key areas like Programming, Data Structures, Computer Networks, Distributed Systems, and Machine Learning.
• Supervise graduate student research projects focused on AI, computer vision, and image forensics.
• Lead research initiatives in the area of digital image authenticity, working on advanced techniques to detect image manipulation and Deepfakes.
• Published research in renowned international journals and conferences with a focus on machine learning and its applications in security and digital forensics.

Courses Taught

• Programming (C, C++)
• Data Structures
• Computer Networks
• Distributed Systems
• Machine Learning

Expert Talks and Faculty Development Programmes

• Delivered a two-day faculty development programme on the theme of Cloud Computing, Machine Learning, MATLAB, Reinforcement Learning, and Research Methodology at MMH College, Ghaziabad on 22-23 September 2023.
  • Shared insights into cutting-edge research and trends in machine learning and cloud technologies.
  • Conducted hands-on sessions on the integration of MATLAB and cloud-based tools for reinforcement learning applications.
  • Focused on practical applications and advancements in machine learning, cloud computing, and the use of MATLAB for research purposes.

Certifications

Certified ISO Auditor

• Acquired certification as an ISO Auditor, which equips me with the expertise to conduct internal and external audits of quality management systems (QMS) in alignment with ISO 9001:2015 standards.
• Responsibilities include assessing compliance with international quality standards, identifying gaps, and providing recommendations for improvement. This certification reflects my ability to ensure that academic and institutional processes meet stringent quality benchmarks, thereby promoting a culture of continuous improvement.

Research Interests

• Deep Learning
• Machine Learning
• Computer Vision
• Image Forensics
• Large Language Models (LLMs)
• Digital Security and Privacy

Selected Publications

• A review on deepfake generation and detection: bibliometric analysis
  Published in Multimedia Tools and Applications (2024), this paper offers a comprehensive review of existing techniques for detecting deepfakes, including their societal impacts and the future of AI-generated content manipulation.
• The societal impact of Deepfakes: Advances in Detection and Mitigation
  Presented at the 14th International Conference on Computing Communication and Networking (2023), this paper explores the ethical and technological advancements in mitigating the spread of deepfakes.
• A comparative study on DeepFake detection algorithms
  Published in Advances in Computing, Communication, and Data Science (2022), this study evaluates various deep learning algorithms for detecting synthetic media.
• Predictive Analytics of Stock Market as a Time Series
  Presented at the 4th International Conference on Advances in Computing, Communication, and Data Science (2022), this paper discusses time series models used in stock market prediction.
• Devanagari Character Recognition Using MLP-Mixer and CNN Extracted Features
  Published in IEEE World Conference on Applied Intelligence and Computing (2023), this paper investigates new approaches for Devanagari character recognition using neural networks.
• Face Manipulation Detection in Images using Inception Layers and Graph Convolutional Networks
  Presented at the International Conference on Innovative Data Communication Technologies (2023), this paper explores novel approaches for detecting face manipulations in images.

Skills and Technologies

• Programming Languages: Python, C, C++
• Tools and Libraries: TensorFlow, Keras, PyTorch, scikit-learn, OpenCV, MATLAB
• Software: MATLAB, Cloud-based platforms (AWS, Azure), Git, Jupyter Notebooks
• Auditing Skills: ISO 9001:2015, Quality Management Systems (QMS)