Aditya Nigam

Assistant Professor (C)
School of Computer Science and Electrical Engineering (SCEE)
Indian Institute of Technology Mandi

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

sample image 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.


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