Dr. Apeksha Mittal 

 Dr. Apeksha Mittal is a dedicated Computer Science educator and researcher with a Ph.D. in Computer Science Engineering. Her areas of interest include Artificial Neural Networks, Artificial Intelligence, Machine Learning, and Data Science. Her career journey includes serving as an Assistant Professor at GD Goenka University, where she spearheaded academic development initiatives as Curriculum In-Charge and Member Secretary for the Board of Studies. Driven by a teaching philosophy centered on holistic mentorship and real-world application, Dr. Mittal has successfully guided students across undergraduate, graduate, and doctoral levels, leading student teams to numerous podium finishes in deep learning hackathons. An active researcher, she has published extensively in esteemed international Science Citation Index (SCI) and Scopus-indexed journals, with a foundational research focus on weight initialization routines for neural networks. She is passionate about bridging rigorous technical research with innovative curriculum design to prepare the next generation of computing professionals.  

• B.Tech. (CSE), M.Tech. (CS), Ph.D. (CSE) 

• Assistant Professor in Computer Science Department, GD Goenka University from 17th September, 2021 to 17th October 2025. 
•  Computer Programmer in the research project “Evaluation of Development of Neurosurgery Skills by Hands-on Training and Interactive Virtual Training” All India Institute of Medical Sciences (AIIMS), Delhi from July 2015 to October 2015.  

• A. Mittal, A. P. Singh and P. Chandra, “Weight and bias initialization routines for Sigmoidal Feedforward Network” in Applied Intelligence, Springer, ISSN: 1573-7497, November 2020, pp. 1-21, Indexed in Science Citation Index (SCI), Impact Factor: 3.325. 
•  A. Mittal, A. P. Singh and P. Chandra, “Improving learning in neural networks through weight initializations” in Journal of Information & Optimization Sciences, Taylor & Francis, ISSN: 2169-0103, June 2021, Indexed in Emerging Sources Citation Index (ESCI).  
• A. Mittal, A. P. Singh and P. Chandra, “A New Weight Initialization using Statistically Resilient Method and Moore-Penrose Inverse based Method for SFANN” in International Journal of Recent Research Aspects ISSN: 2349-7688, Vol. 4, Issue 2, June 2017, pp. 98-105.  
• K. Middha and A. Mittal, “Discovery of type 2 diabetes mellitus with correlation and optimization driven hybrid deep learning approach” in Computer Methods in Biomechanics and Biomedical Engineering, Pre-Press, Pg. 1-13, October 2023. (SCI)  
• K. Middha and A. Mittal, “An effective feature selection method for type 2 diabetes mellitus detection using gene expression data” in Intelligent Decision Technologies, Pre-Press, Pg. 1-9, November 2022. (SCOPUS)  
• Savita, G. Rani and A. Mittal, “Detection of CAD using optimization approach with machine learning classification techniques” in International Journal of Systematic Innovation, Vol. 7, Issue 3, September 2022. (SCOPUS).  
• Savita, G. Rani and A. Mittal, “An Optimized Machine Learning Approach for Coronary Artery Disease Detection” in Journal of Advances in Information Technology, Vol. 14, Issue 1, Pg. 66-76, February 2023. (SCOPUS)  
• A. Mittal and P. Chandra, “Improving learning in Artificial Neural Networks using better weight initializations” in International Journal of Information Technology, January 2024 (Scopus) 
• A. Gupta, A. Mittal and R. Jain, “Sarcasm Detection on News Headlines, Twitter and SARC Dataset: A Detailed Evaluation of Shallow and Deep Models”, International Journal of Intelligent Engineering Informatics, 2024 (Scopus)  
• K. Midhha and A. Mittal, “Optimization Enabled Feature Selection and Hybrid Deep Learning Approach for Detection of Type 2 Diabetes Mellitus”, Biomedical Materials and Devices, March 2026 (Scopus)  

• A. Mittal, A. P. Singh and P. Chandra, ”Comparison of Random Weight Initialization to New Weight Initialization CONEXP,” Communications in Computer and Information Science, Vol 1230. Springer, 2019.   
• A. Mittal, P. Chandra and A. P. Singh, “A Statistically Resilient Method of Weight Initialization for SFANN” in proc. of Advances in Computing, Communications and Informatics (ICACCI), IEEE, 2015, pp 1371-1376.   
• K. Middha and A. Mittal, “Comparative Analysis of deep learning with different optimization techniques for Type 2 Diabetes Mellitus detection using Gene expression Data”, in International Conference on Innovative Computing and Communication (ICICC-2023), Springer, 2023   
• Gupta, A. Mittal and R. Jain, “Multimodal Sarcasm Detection: A survey of Methods, Fusion Techniques, Dataset Analysis and Open Issues”, in International Conference on Innovative Computing and Communication (ICICC-2025), Springer, 2025  

• Mittal, A. P. Singh and P. Chandra, “A Modification to Nyugen-Widrow Weight Initialization Method”, in Intelligent Systems, Technologies and Applications, Vol. 910, Springer, February 2019, pp 141-153, ISBN 978-981-13-6095-4.