My recent CV (update on July 2019)

Soon going to organize Deep Learning at IIT Mandi) on "Deep Learning workshop cum crash course-2020" in support of (TIH-HCI) from September

Conference paper accepted in ACM-MM-2020, ECCV-2020, IJCB-2020, EMBC-2020, IJCNN-2020; Journal papers accepted in PRL, JASA and IET Biometrics

Recent Publications

Ranjeet R Jha, Gaurav Jaswal, Divij, Shrestha and Aditya Nigam, “PixISegNet: Pixel Level Iris Segmentation Network using Convolutional Encoder-Decoder with Stacked Hourglass Bottleneck” in Journal of IET Biometrics, IET (Impact Factor: 2.09) [Accepted in AUG]

Daksh Thapar, Gaurav Jaswal, Aditya Nigam and Chetan Arora, “Gait metric learning Siamese network exploiting dual of spatio-temporal 3D-CNN intra and LSTM based inter gait-cycle-segment features” in Journal of Pattern Recognition Letters, Elsevier (Impact Factor: 2.8) [Accepted in JULY]

Suraj Kumar, Aayush Mishra, Saiful Islam and Aditya Nigam, “VStegNET: Video Steganography Network using Spatio-Temporal features and Micro-Bottleneck” in 30th British Machine Vision Conference (BMVC-2019), 9-12 September 2019, Cardiff, UK

Anshul Thakur, Daksh Thapar, Padmanabhan Rajan, and Aditya Nigam, “Deep metric learning for bioacoustic classification: Overcoming training data scarcity using dynamic triplet loss” in Journal of Acoustical Society of America, ASA (Impact Factor: 1.9) [Accepted in JUNE]

Gaurav Jaswal, Aditya Nigam, Ravinder Nath, Amit Kaul and Amit Kumar Singh “Bring your own hand: how a single sensor is bringing multiple biometrics together” in Journal of Soft Computing, Springer (Impact Factor: 2.4)

Seema Kumari, Ranjeet R. Jha, Arnav Bhavsar and Aditya Nigam, “Autodepth: Single Image Depth Map Estimation via. Residual CNN Encoder-Decoder and Stacked Hourglass” in International Conference on Image Processing (ICIP-2019), 22-25 September 2019, Taipei, Taiwan

Daksh Thapar, Gaurav Jaswal, and Aditya Nigam, “FKIMNet: A Finger Dorsal Image Matching Network Comparing Component (Major, Minor and Nail) Matching with Holistic (Finger Dorsal) Matching” in International Joint Conference on Neural Networks (IJCNN-2019), 14-19 July 2019, Budapest, Hungary

Avantika Singh and Aditya Nigam, “Effect of identity mapping, transfer learning and domain knowledge on the robustness and generalization ability of a network: A biometric based case study” in Journal of ambient intelligence and humanized computing , Springer (Impact Factor: 1.4)

International Workshop on Deep Learning and its Application (IWADL2019) at IIT Mandi from 1st to 5th July 2019

CS671: Course on Deep Learning and its Application [2019-20] (Click here)

IWADL-2018 Report [Click here].

Tutorial Slides: The Journey from Shallow to Deep Learning at NCVPRIPG2017 [Click here].

[NOTE] The above tutorial has been created by collecting material from several online resources. All the copyrights are with the respective authors.

Recent Research Work

I have received my Masters (M.Tech) and Doctoral (Ph.D) degrees from Indian Institute of Technology Kanpur in 2009 and 2014 respectively. Presentely I am working as an Assistant Professor at IIT Mandi, HP in the School of Computing and Electrical Engineering (SCEE). I have joined this School during August 2014 as a Teaching Fellow. I am working in the area of Biometrics, Image Processing, Computer Vision and Machine Learning. I am looking for self motivated MS, Ph.D students willing to work in my research domain as mentioned below.

Research Interests

Deep Learning, Biometrics, Medical Image Processing & its Analysis, Image Processing, Computer Vision & Machine Learning.

Contacts

Office: Room No : 206, Academic Building A4 in Kamand, School of Computing and Electrical Engineering (SCEE), Indian Institute of Technology Mandi, (HP) INDIA, PIN: 175005
Phone: +91-1905-267152
E-mail: aditya[at]iitmandi[dot]ac[dot]in